A collaborative approach to greater diversity in clinical trials

The need for diversity in clinical trial populations has been a topic of discussion across regulators and the industry in general for decades. Despite the introduction of US policies, beginning with the 1993 National Institutes of Health (NIH) Revitalization Act which called for the inclusion of more women and communities of colour in clinical trials, clinical trial data has remained largely based on healthier Caucasian subjects with minimal representation from minorities (African American, Latinx, Asian, Native Americans), the elderly, young, and those with co-morbidities.

To encourage more of a focus on clinically relevant populations, the US Food and Drug Administration (FDA) recently released “Enhancing the Diversity of Clinical Trial Populations – Eligibility Criteria, Enrollment Practices, and Trial Designs Guidance for Industry” to increase participant access to clinical trials and the enrolment of underrepresented populations to ensure clinical trial data reflects the population most likely to use the drug if approved1. The guidance encourages sponsors to remove overly restrictive and legacy exclusions, broaden protocol eligibility criteria, and improve trial recruitment practices so trial data is clinically relevant for the end user.

Historical performance data, like that provided in FDA Drug Trials Snapshots, has shown that using traditional recruitment practices by themselves does not enhance the diversity of clinical trial populations. Fundamental barriers and deeply rooted mistrust of medical research motives among communities of colour require a more thoughtful and deliberate approach to participant outreach. PPD has seen recent successes in the recruitment of more clinically relevant trial populations through the implementation of patient-centered trial solutions designed to address the most common barriers to clinical trial participation among these diverse patient populations – mainly trust, understanding, awareness, access, time, and cost, especially when delivered in collaboration with organisations focused on communities of colour and community leaders to ensure optimal receptivity.


• Read the full article in pharmaphorum’s Deep Dive digital magazine

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Kaiser Permanente to analyze CDC’s Covid-19 vaccine data, identify bad reactions

The CDC has engaged the California-based health system’s Vaccine Study Center to conduct an analysis of its Covid-19 vaccine data with the aim of pinpointing adverse events and reactions. The collaboration will continue for the next three years.

ViewPoints Interview: Janssen’s Andrew Greenspan Shares Insights on the Data Presented at ACR2020

In a recent interview with PharmaShots, Andrew Greenspan, MD, VP Medical Affairs of Janssen Immunology shared his views on Janssen’s commitment to advance research in rheumatic disease.


  • Janssen presented clinical trial results in 35 abstracts featuring findings across PsA, RA, and SLE at ACR Convergence 2020 Virtual Scientific Program
  • Sixteen abstracts focus on Tremfya in adults with active PsA, including 52-week safety and efficacy data, axial disease-related endpoints, and more.
  • Other presentations feature new research across Janssen’s portfolio of medications including Simponi Aria (golimumab), Stelara (ustekinumab), and Remicade (infliximab)

Tuba: How was your virtual experience at ACR2020? Can we have an insight on data presented at ACR 2020?

Andrew: Speaking on behalf of those who represented Janssen at the conference – we are so proud of the breadth of data presented at ACR this year. Even though the conference looked a little different than it has in years past, we were still thrilled to share our findings – including 35 abstracts highlighting our research across psoriatic arthritis, rheumatoid arthritis and system lupus erythematosus. Specifically, we presented 16 abstracts focused on TREMFYA in adults with active psoriatic arthritis, including 52-week safety and efficacy data, spinal disease-related endpoints, as well as analyses that highlight patient-reported outcome measures including fatigue. Other presentations featured new research across our portfolio of medications.

Tuba: As the focus of the presentation is Tremfya, give a quick review about the clinical data supporting the therapy?

Janssen’s Tremfya (guselkumab) Receives the US FDA's Approval as the First Selective IL-23 Inhibitor for Active Psoriatic Arthritis
Source: MPR

Andrew: As a company, we’re constantly striving to keep our foot on the gas to create new clinical evidence and innovation. As a testament to this, we were proud to expand our rheumatology portfolio this year with the U.S. FDA approval of TREMFYA for adult patients with active psoriatic arthritis, which was first approved to treat adults with plaque psoriasis in 2017. Let me share some additional information on the compelling data we shared at ACR:

  • Data from two Phase 3 clinical trials, DISCOVER-1 and DISCOVER-2, showed that TREMFYA improved fatigue in adult patients with active psoriatic arthritis and maintained response through 52 weeks of active treatment, as measured by the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) Scale. TREMFYA is the first and only treatment approved for active psoriatic arthritis to have an improvement in fatigue as measured by FACIT-F in the product label.
  • The positive outcomes in fatigue assessment add to the body of data for TREMFYA, which has shown improvements in multiple clinical outcomes including joint symptoms, skin symptoms, soft tissue inflammation, and physical function.
  • Fatigue is considered one of the three most important symptoms by patients with active psoriatic arthritis, and moderate to severe fatigue occurs in up to 50 percent of these patients.

Tuba: Can we have a glance at Janssen’s immunology portfolio as it is working in immunology over the past two decades?

Source: Janssen

Andrew: At Janssen, we have an unmatched track record of translating science into effective therapeutics. In the past two decades, my colleagues at Janssen have developed five advanced treatments for 31 indications resulting in the treatment of more than 5 million patients living with autoimmune disease. Treatments in our immunology portfolio treat a variety of conditions for various patient populations, such as plaque psoriasis, psoriatic arthritis, ankylosing spondylitis, polyarticular juvenile idiopathic arthritis, rheumatoid arthritis, ulcerative colitis and Crohn’s disease. These treatments include TREMFYA (guselkumab), SIMPONIARIA (golimumab), STELARA (ustekinumab), SIMPONI (guselkumab) and REMICADE (infliximab). Looking ahead to potential future treatments, we have a robust pipeline, with 21 first-in-class Phase 2 or 3 trials underway. We’re eager to explore treatment options for less common diseases like hidradenitis suppurativa and Sjogren’s syndrome, where there are fewer or no advanced treatment options currently available.

Tuba: What are Janssens’s efforts in developing biomarkers and co-diagnostics to personalize medicine in the field of rheumatic diseases?

Andrew: We are exploring the development of tools that will better allow us to measure disease activity in patients, including sensors (digital health, actigraphy), novel biomarkers, new endpoints and new patient-reported outcomes to better identify patients appropriate for our medicines and to evaluate the efficacy and safety of them.

 Tuba:  Apart from Tremfya, Simponi, Simponi Aria, and Stelara, what next can we expect from Janssen to transform the lives of patients with autoimmune diseases? What will be your next move (in terms of the combination of internal research and development, external collaborations, and industry consortia) to complement Janssen’s existing portfolio of immunology? Who are Janssen’s potential competitors in the field of autoimmune diseases?

Andrew: I’m very proud of where our research in immunology stands and where it is leading us. While treatments today have made a big difference in the lives of many patients, there certainly remains a significant need for medicines that work better, faster, and longer. Instead of focusing on the competition, we prefer to focus on unmet needs. By unlocking new pathways, mechanisms, and regimens in our treatment options, we strive to provide innovative treatment options to patients. Looking further ahead at our mid-to-late stage pipeline, we have 21 first-in-class Phase 2 or 3 trials underway and we’re eager to explore treatment options for less common diseases like hidradenitis suppurativa and Sjogren’s syndrome, where there are fewer or no advanced treatment options currently available.

Tuba: Can we have a glimpse of Janssen’s work in other therapeutics areas? Can you list out some key advancements for our readers?

Andrew: In addition to immunology, we focus on areas of medicine where we can make the most impact, including Cardiovascular & Metabolism, Infectious Diseases & Vaccines, Neuroscience, Oncology, and Pulmonary Hypertension, where we have delivered 18 new medicines in less than nine years. For more information about these specific therapeutic areas, I would be happy to put you in touch with a specialist on our team to learn more about the innovative work being done in these fields.

Tuba: Does the global pandemic affect Janssen’s ongoing as well as future clinical trials?

Andrew: As the world continues to navigate the new normal brought on by COVID-19, there has been an undeniable effort to ensure continuity of care and advance research by a wide range of experts, from healthcare professionals and clinical trial site teams to research partners and regulatory bodies. We at Janssen recognize and remain committed to supporting everyone involved in clinical research. To learn more about Janssen’s commitment to clinical trial research, visit: https://www.janssen.com/clinical-trials/janssen-global-development-leadership-commitment-clinical-research.

Image Source: MIMS Malaysia

About Author:

Andrew Greenspan, MD is a vice president of Immunology Medical Affairs at Janssen and has joined J&J in 2003.

Related Post: ViewPoints Interview: GSK’s Dr. Riju Ray Shares Insights on the Role of Community-Based Pulmonologists in Improving COPD Management Among PCPs

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True patient-focused research through decentralised and hybrid trials

How can pharma improve the patient-centricity of its trials during COVID-19 and beyond? Experts from across the sector give their thoughts on the key approaches and technologies that are driving patient engagement forward.

With COVID-19 presenting new barriers to running and recruiting for clinical trials, making studies patient-centric is more important now than ever before.

According to one analysis, conducted by Global Data, approximately 67% of trial disruptions during the early stages of the pandemic were due to the suspension of enrolment, followed by the delayed start of planned trials at 18.4% and slow enrolment at 14.4%.

Ensuring that trials are easy to access and don’t overly burden the patient is essential amidst these potential disruptions – but a truly patient-centric trial has benefits beyond enrolment.

Trials that are engaging and easy to partake in can lead to higher adherence, higher satisfaction, improved data quality and overall performance, and can even give participants a more positive view of the sponsor company in terms of their commitment to bring new treatments to patients.


• Read the full article in pharmaphorum’s Deep Dive digital magazine

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Elsevier to Work with Heel for Mechanism-based Drug Action Discovery

Elsevier, the data analytics business specialized
in science and health, and Heel, a pharmaceutical company specialized in
developing and manufacturing medicines made from natural ingredients, have
recently completed a series of research projects with a focus on improving
exploratory preclinical studies.

“We at Heel are pioneers in the field
of systems research and have a strong commitment to scientific excellence and
the generation of evidence. Our aim is to find out how these medicines work in
the body and to develop therapies which are tailored even more to patients’
medical needs,’’ said Dr. Kathrin Hemmer, a scientist at Heel. “We chose to
partner with Elsevier because of its expertise in scientific information search.
Assistance from the Professional Services group allowed us to get a single
access to all the Elsevier’s R&D solutions advancing our exploratory
research programs.”

“Research success requires connecting, combining
and harmonizing data from different sources. We are helping researchers to select
the best evidence-based strategy for mechanism-based drug action”, said Dr.
Taisiya Bezhaeva, Professional Services Consultant at Elsevier.

“Together with Heel, we designed a
series of projects to find preclinical models for drug action discovery,
identify key biomarkers, and research platforms validated by the international
research community. We focused on the broad range of disease areas, overall
covering more than 10000 literature sources, as well as FDA and EMA drug
approval documents. We also supported researchers by providing key opinion leaders
(KOL) and potential academic and commercial partners helping Heel to direct and
facilitate the course of their studies”, said Dr. Maria Shkrob, Senior Consultant
in Professional Services at Elsevier.  



  • Connecting, combining and harmonizing data from different
  • Big-data & evidence-based approach to identify complex molecular
    mechanisms and biological networks for natural active compounds
  • Such approach combined with advanced text-mining technologies and
    statistics is a powerful, feasible
    and universal analytic method to select the best strategy for exploratory
    research to demonstrate pharmacodynamic actions, safety and efficacy
  • Support to strengthen scientific credibility and
    facilitate market positioning

Behind the scenes: How health systems, EHR vendors will give patients unprecedented access to their data

virtual care

Health systems and EHR vendors have been working for months to comply with the ONC’s final rule on interoperability and information blocking that goes into effect in April and is expected to grant patients unprecedented access to their health information. Here is a look at some of the issues they contended with.

Zydus Cadila Seeks Approval to Commence P-III Clinical Study of ZyCoV-D


  • The company reported that the COVID-19 vaccine is safe, well-tolerated & immunogenic in the P-I/II study & plans to initiate P-III clinical trial in ~30000 volunteers upon receiving necessary approvals
  • The P-II study of ZyCoV-D had been conducted in ~1000 healthy adult volunteers as part of the adaptive P-I/II dose-escalation study
  • The trial has been reviewed by an independent DSMB & reports have been submitted to CDSCO regularly for the update on safety outcome

Click here ­to­ read full press release/ article | Ref: Zydus Cadila | Image: eHealth Magazine

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Regeneron’s Antibody Cocktail Demonstrate Promising Results in Hospitalized Patients on Low-Flow Oxygen


  • The company reported encouraging initial data from an ongoing P-I/II/III trial of its casirivimab + imdevimab (8,000/2,400mg) in hospitalized COVID-19 patients requiring low-flow oxygen. The results passed the futility analysis as seronegative patients treated with the Ab cocktail had a lower risk of death or receiving mechanical ventilation
  • In seronegative patients, the cocktail reduced the time-weighted average daily viral load through day 7 by -0.54 log10 copies/mL & through day 11 by -0.63 log10 copies/mL, at day 5, the relative reduction vs PBO was -1.1 log10 copies/mL
  • Both the Ab cocktail doses were well-tolerated. The Ab cocktail is designed to block the infectivity of SARS-CoV-2

Click here ­to­ read full press release/ article | Ref: PRNewswire | Image: Knowledge Ecology International

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ViewPoints Interview: ViiV Healthcare’s Kimberly Smith Shares Insight on Data of Long-Acting Cabotegravir and Rilpivirine Presented at IDWeek 2020

In a recent interview with PharmaShots, Kimberly Smith, MD, MPH, Head of Research & Development at ViiV Healthcare shared information on the positive findings presented at the 2020 Infectious Diseases Society of America (IDWeek) and the impact of COVID-19 on the development of long-acting cabotegravir and rilpivirine.


  • The company reported the positive findings of a pooled analysis of six ongoing clinical studies which includes P-IIb/IIIb LATTE-2, ATLAS, ATLAS-2M, FLAIR, POLAR, and CUSTOMIZE studies evaluating long-acting cabotegravir and rilpivirine regimen in 1,744 patients with HIV-1 infection across 16 countries
  • The positive findings showed 93% of participants maintained their injection visits amid the COVID-19 with no instances of virologic failure or development of resistance and showed good tolerability
  • Long-acting regimen of cabotegravir and rilpivirine is indicated as a complete regimen for the treatment of HIV-1 infection in adults to replace the current antiretroviral regimen in patients who are virologically stable and suppressed (HIV-1 RNA <50 copies/mL) and has received Health Canada’s approval in Mar’2020

Tuba:  Showcase the ViiV’s positive findings presented at the 2020 Infectious Diseases Society of America (IDSA) IDWeek.

Kimberly: At IDWeek 2020, we presented data across our innovative portfolio, showcasing meaningful advancements and scientific breakthroughs that are currently challenging the treatment paradigm. We shared positive findings across our development program for long-acting cabotegravir and rilpivirine, including five-year findings from LATTE-2 and 48-week findings from POLAR that further established the durable efficacy and safety of long-acting cabotegravir and rilpivirine. Findings from the implementation science CUSTOMIZE study showed that long-acting cabotegravir and rilpivirine was both acceptable and appropriate among people living with HIV and their providers, and provided best practices to integrate the investigational regimen in US healthcare settings. Lastly, positive findings from an analysis of the entire long-acting cabotegravir and rilpivirine development program confirmed there were no antiretroviral therapy interruptions in spite of COVID-19, demonstrating strong implementation fidelity for this potential HIV treatment option.

Tuba:  What are the impacts of global pandemic COVID-19 on the development of the dual regimen?

Kimberly: The analysis showed that no antiretroviral therapy interruptions were found across the entirety of the ongoing clinical development program for long-acting cabotegravir and rilpivirine. When missed visits occurred due to the pandemic, they were manageable and successfully mitigated, primarily by switching patients onto short periods of daily oral therapy of cabotegravir and rilpivirine, with no resulting virologic failure or emerging resistance. These findings speak to how the regimen of cabotegravir and rilpivirine may be adapted to meet the needs of people living with HIV who have events in their lives that could cause them to miss an injection appointment.

Tuba:  As the approval in the EU is on track, when can we expect the availability of a combination regimen in the EU?  What are your other geographical targets for seeking approval?

Kimberly: The long-acting regimen of cabotegravir and rilpivirine is currently under review by the US Food and Drug Administration and other global regulatory authorities.

The Committee for Medicinal Products for Human Use (CHMP) of the European Medicines Agency’s (EMA) has issued a positive opinion recommending marketing authorization for long-acting cabotegravir and rilpivirine in both injectable and tablet formulations. The CHMP positive opinion is one of the final steps before marketing authorization is granted by the European Commission, which has the authority to approve medicines for use throughout the European Union.

Further regulatory authority submissions are planned in the coming months. We look forward to working with these regulatory authorities as part of our continued commitment to developing new and innovative treatment options for people living with HIV.

Tuba:  When can we expect the NDA submission of Cabotegravir and Rilpivirine complete long-acting regimen to the US FDA?

Kimberly: The long-acting regimen of cabotegravir and rilpivirine was resubmitted to the US Food and Drug Administration earlier this year and is currently under review. The PDUFA date is set for Jan. 28, 2021.

Tuba:  Is ViiV Healthcare working on any digital tool or planning to work on any digital initiative for changing the experience of people living with HIV?

Kimberly: ViiV Healthcare recently announced a new weekly podcast, Being Seen, which is an in-depth exploration of the role culture plays in resolving how we see ourselves and how we are seen by others. The first season explores current cultural representations of the queer and gay Black male experience and the impact on their lives and society.

Hosted and narrated by Darnell Moore, award-winning writer and activist, we hope that Being Seen can encourage more culturally accurate portrayals of the queer and gay Black male experience to reduce stigma and change perception. The podcast expands on insights and findings from our landmark ethnographic research conducted among Black gay men in Baltimore, Maryland and Jackson, Mississippi. We hope that this initiative will raise awareness to the impact of stigma on every aspect of these individual’s lives and underscore the collective responsibility to end discrimination among marginalized communities, including those living with HIV.

Tuba:  As ViiV Healthcare has a broad portfolio of medicines targeting HIV in adults, what are your efforts in pediatric HIV infection which is the most invisible population in HIV?

Kimberly: Age-appropriate formulations are essential to close the gap between treatment options available for adults and children and ensure children have access to life-saving medicines that give them the potential to be healthy, just like any other child.

On June 12, the FDA approved Tivicay PD tablets for oral suspension, which are used in combination with other antiretroviral agents for the treatment of HIV-1 infection in pediatric patients (treatment-naïve or -experienced but INSTI-naïve) aged at least four weeks and weighing at least 3kg. The FDA also approved the extended indication of already approved Tivicay 50mg film-coated tablet in pediatric HIV patients weighing 20kg and above.

In addition, we have worked in collaboration with the HIV community and our partners, DAIDS, NIH, IMPAACT, Penta, and MRC at UCL, who have been instrumental to our progress in generating and analyzing clinical data to optimize pediatric formulations and help improve the lives of children living with HIV.

About Kimberly Smith:

Dr. Kimberly Y. Smith MD, MPH is the Vice President for Global Medical Strategy and Head of Research and Development for ViiV Healthcare. She oversees the clinical development of the ViiV marketed and pipeline assets and works closely with the development teams in both GSK and Pfizer.

Related Post: ViewPoints Interview: Neoleukin’s Daniel-Adriano Silva Shares Insight on Novel Protein Designed to Treat or Block SARS-COV-2

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Cerner to snap up Kantar’s health division for $375M

The EHR giant is planning to buy Kantar Health, which provides data, analytics and research to the life sciences industry. Through the acquisition, Cerner aims to provide its clients with more access to data analytics and research expertise and engagement with life sciences companies.

Roche Highlights its Bispecific Antibody Portfolio Across a Range of Blood Cancers at ASH 2020


  • The company presented the new data of its T-cell engaging bispecific Abs, mosunetuzumab, glofitamab and cevostamab at ASH 2020, demonstrating encouraging activity across multiple types of blood cancer
  • Roche divulges that its mosunetuzumab & glofitamab showed promising responses across multiple types of NHL, including R/R FL & DLBCL, reinforcing from the P-I/Ib GO29781 study results in R/R FL, that showed 51.6% of patients achieved a CR when treated with mosunetuzumab
  • Beyond r/r setting, mosunetuzumab & glofitamab are also being evaluated in 1L DLBCL. Additionally, Roche has presented the data of cevostamab that showed a 53% ORR rate in heavily pre-treated patients with MM

Click here ­to­ read full press release/ article | Ref: GlobeNewswire | Image: Financial Times

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DispatchHealth adds to evidence backing safety, efficacy of hospital-at-home programs

Amid the Covid-19 pandemic and a growing interest in at-home care, DispatchHealth has published new data showing that its hospital-at-home program did not result in unexpected deaths, serious adverse events or patients being subsequently admitted to a skilled nursing facility.

Dual Eligibles’ Medicaid Policy Database

Poor, elderly individuals who may qualify for both Medicaid (for being poor) and Medicare (for being elderly, blind, disabled or have ESRD). In these cases, Medicaid serves as a supplemental insurer, covering Medicare coinsurance and deductibles. The generosity of this supplemental coverage for so-called ‘dual-eligibles’ varies across states.

These differences in Medicaid payments arise from two sources of policy variation. First, states differ in their adoption of so-called “lesser-of” policies, which are provisions for Medicaid to pay the lower of (a) Medicare’s cost sharing, or (b) the difference between the Medicaid fee schedule and Medicare’s payment for a service (net of cost sharing).1 Second, Medicaid fee schedules, which vary across states and over time, affect the amount of cost sharing that Medicaid will pay providers in lesser-of states.

In lesser-of states with low Medicaid fee schedules, providers can be paid substantially less when rendering services to duals vs other Medicare beneficiaries, who either pay Medicare’s cost sharing out of pocket or have private supplemental (ie, Medigap) insurance to
cover these expenses.

Unsurprisingly, providers are not as excited to provide care for dual-eligibles when they get paid less money for providing the same services they provide to Medicare beneficiaries (see Mitchell et al 2004, Haber et al. 2014, Zheng et al. 2017).

To measure variation in state Medicaid policies regarding dual eligibles, a paper by Roberts et al. (2020) describes the process of creating a database of these policies. The sources of the database were (i) state Medicaid plans and amendments filed with CMS; (ii) state laws from LexisNexis; (iii) and Medicaid provider manuals, program bulletins, and related online policy documents. Then the authors created a payment index using a nationally representative sample of claims data for evaluation and management services HCPCS codes. The database is publicly available here.

Based on these data, the share of states with <80% coverage of Medicare coinsurance and deductibles has grown over time, from 24 states in 2004 to 29 states in 2018. Further, the number of states that provide full reimbursement fell from 11 in 2004 to 7 in 2018.

One limitation of the data used for this evaluation is that it ignores managed care. Medicaid managed care organizations (MCOs) and MCOs are have grown–relative to Medicaid fee-for-service–over time.

Lesser-of policies function similarly under Medicaid managed care, except that Medicaid MCOs pay the lesser-of (a) the difference between their negotiated provider rates and Medicare’s payment amount, and (b) Medicare’s cost sharing. However, to the extent payment rates negotiated by Medicaid MCOs differ from those in fee-for-service Medicaid, our payment index will not accurately reflect provider payments for duals enrolled in Medicaid MCOs.

Further, the analysis also does not include Medicare Advantage beneficiaries. In 2018, Medicare Advantage plans covered 33% of dual-eligibles with full Medicaid.

Nevertheless, the creation of this dataset to track changes in Medicaid dual-eligible generosity is certainly a useful contribution to the literature.


Takeda to partner on patient-centric data with Seqster

Takeda has partnered with patient data firm Seqster in a drive to improve care through better access and understanding of patient-level data.

The partnership follows Takeda’s investment in the US startup earlier this year. The pharma firm said it wants to leverage the company’s technology across its business

San Diego-based Seqster has developed a portal that gathers together a patient’s data – such as electronic health records (EHR), genetic information, fitness results from wearables etc – and keeps it in a secure format that gives control over its collection, ownership and sharing.

Takeda hopes Seqster can help expand its external data and digital collaboration ecosystem, with better access to real-world evidence, and generate powerful data and insights for research and patient services. 

The company says it wants to activate 12 distinct use cases across our business “in a matter of weeks”.

One use of Seqster’s decision support system and research platform is to reduce the time for consenting and onboarding patient data during clinical trials. The aim is to enhance patient engagement and compliance through a single-entry point for EHRs and integrates with partners enterprise data backbones.    

At the time of Takeda’s investment in Seqster, Bruce Meadows, head of investments at Takeda Digital Ventures, said it was “a cornerstone of our digital health strategy,” and that the key element is “interoperability” for health data sharing.

Seqster’s platform “addresses interoperability on not only a nationwide scale but also globally,” according to Meadows, who notes that interoperability “is one of the biggest barriers to applying precision medicine to clinical trials and patient engagement.”

It is also a key objective for the Centers for Medicare & Medicaid Services (CMS) and Office of the National Coordinator for Health Information Technology (ONC) in the US.

The two agencies have a pair of proposed rules on interoperability and patient access to health information under review at the Office of Management and Budget (OMB) that could come into effect later this year.

A key part of those proposals is to allow patients easy, electronic access to their personal health information at no cost.

The Seqster Research Portal (SRP) can be used to speed up recruitment into clinical trials, as well as the consent process, and can work with a broad range of study types including patient registries used to generate real-world evidence, says its developer.

“Seqster provides clinical trial participants a secure platform to consent and share their data with investigators and study personnel in real-time,” according to the company’s chief executive Ardy Arianpour.

In turn, that creates “a longitudinal health record that facilitates patient clinical trial onboarding, monitoring and post-trial follow-ups,” he adds.

Seqster says the SRP platform currently connects users to more than 3,000 healthcare providers and over 100,000 hospitals and clinics across the US.

Listen to our podcast interview with Ardy Arianpour here.

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Dermavant Presents Results of Tapinarof in Pivotal P-III PSOARING Program at the 29th EADV Virtual Congress


  • The pivotal P-III clinical program for tapinarof in adult with PsO consists of PSOARING 1 (NCT03956355) and PSOARING 2 (NCT03983980) PSOARING 3 (NCT04053387), an ongoing long-term safety study. Positive results of P-III studies were reported in Aug’2020
  • Tapinarof previously met the 1EP in separate P-IIb trials for PsO & AD, both studies were published in JAAD. The company anticipates its NDA filling in 2021
  • Tapinarof (qd) is a steroid-free, cosmetically elegant, TAMA topical cream being developed for the treatment of PsO and AD. To date, 2200+ subjects have enrolled in 18 clinical trials of tapinarof

Click here ­to­ read full press release/ article | Ref: Businesswire | Image: Dermavant

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Why 72% of patients don’t feel listened to by pharma

Claus Møldrup explores research showing that patients want their voice to be heard more by pharma, and asks what a truly effective feedback loop for medicines might look like.

The democratisation of data opens up improvements to virtually every product and service across virtually every sector — bar one. Pharma remains stubbornly closed to feedback, with potentially damaging consequences for the industry, healthcare systems and patients.

The most obvious iteration of democratisation is the rise of online experience sharing platforms. From highly specific sites such as Trip Advisor to all-encompassing platforms such as Trustpilot, the modern consumer’s voice carries weight. While negative reviews can sink a business, forward-thinking organisations see this accountability as a driver for continuous improvement.

The omission of medicines from the feedback revolution is curious and potentially damaging. Data defines modern therapeutics, but this is almost uniquely confined to the clinical trial stages of drug development. Identifying, recruiting, retaining and monitoring patients during this part of the cycle is estimated to cost pharma US$19 billion a year as companies seek to harvest patient experiences.

Once a drug is licensed and launched, however, there is a deafening silence. Millions of patients are prescribed often complex drugs and are expected to follow equally complicated regimens. While clinical outcomes are of course monitored through healthcare systems, the patient’s experiences, such as the reality of their drug administration and day-to-day effects, are ignored by the very companies that developed — and continue to develop — them.

“As most other sectors have long recognised, if a business isn’t taking part in the conversation then others will fill the void to tell their story instead. That narrative, for many patients, is that pharma companies just don’t care”

Pharma is swimming against the tide and can’t pretend that the democratisation of medicines data doesn’t exist — because it’s already here. As most other sectors have long recognised, if a business isn’t taking part in the conversation then others will fill the void to tell their story instead. It means pharma has lost control of its own narrative – and that narrative, for many patients, is that pharma companies just don’t care.

Research supports this conclusion, showing an alarming lack of patient trust. A 2020 survey from DrugsDisclosed.com of 3,346 users of prescription and over the counter (OTC) medicines from the UK and the Nordics revealed that:

  • more than three-quarters of patients do not trust advice from pharmaceutical companies about their medication;
  • 81% feel the pharmaceutical industry influences prescription decisions; and
  • 72% do not feel listened to by pharmaceutical companies.

These are startling statistics, and this overwhelmingly negative perception must be of concern. Pharma is an industry that should have a hugely positive story to tell as it develops the medicines and treatments that bring benefits to billions of people around the world. Yet it is widely mistrusted.

If pharma companies listened more, they would hear that the users of their medicines often feel confused and alone. In direct opposition to the emerging era of personalised healthcare, medicine information leaflets are one-size-fits-all documents that fail to reflect a patient’s individual circumstances and experiences, and are obligated to list every possible side-effect (which can make them virtually meaningless). In addition, patients have no opportunity whatsoever to feed back or pose questions to the company or — as critically — other users.

As one Crohn’s Disease patient describes in a DrugsDisclosed user case study, “It can be difficult getting useful and reliable information on your medication, and leaflets that come with them can be scary. They have to list all of the possible side effects, even the rarest. It is reassuring to read about other people’s real-life experience… It is important because it is by the people that actually take the medications. It makes me feel less alone.”

Shared experience — the power to improve

There is a better way. Healthcare (as distinct from pharma) has evolved with society and its technologies. Go back just a few decades and patients were passive bystanders to their own healthcare. Medicine took a patrician approach: it knew best and patients should lie still whilst they were poked, prodded and prescribed until they (hopefully) got better. This has changed — and changed for good.

Many healthcare systems are well advanced in listening to patients. In the UK, for example, every NHS hospital has a ‘patient panel’ made up of service users. These panels provide real-time feedback on experiences, from food to hygiene to clinical care, and members often sit on the main hospital Board to ensure that actions are informed by patient insight. This isn’t a PR exercise — it improves hospital environments, focuses decision-making and ultimately benefits clinical outcomes.

We are now seeing this evolve further as a new and distinct discipline emerges, known as Public Engagement (PE). PE isn’t traditional ‘communications’ where organisations talk to try and change patient behaviours, rather it’s about listening to patients to change corporate behaviours.

This evolution is particularly prevalent in emerging medicines, with organisations such as Genomics England and The Wellcome Trust supported by Understanding Patient Data recognising the huge and largely untapped value of patient experience — and that the success of new forms of medicine depends on public understanding, acceptance and consented participation.

The way back

Some of these issues fall out of well-intentioned codes and regulations to protect patients, but this can no longer be cited as an excuse for pharma’s continuing lack of engagement with its ultimate end users.

Technologies — specifically a sophisticated form of ‘Trustpilot for medicines’ — exist to bridge the gap between pharma and patients responsibly. Using this kind of technology will see significant improvements to healthcare generally and medicines specifically.

Research again backs up this conclusion, with a study that reviewed patients who had used an anonymised — regulatory compliant — medicines feedback app. After two months:

  • 79% experienced an improvement in remembering to take their medications;
  • three quarters experienced an improvement in taking their medications as prescribed;
  • close to half felt they better understood their medications;
  • 69% felt more motivated to take their medications; while
  • more than a third felt the effect of their medication actually improved.

In calling for further research, another study concluded that use of these apps improved clinically relevant indicators of adherence and impact and benefits were related to level of app usage.

Asking patients how they feel about medications can also benefit wider healthcare systems. In the UK, for example, more than half the public expressed an unwillingness to take a vaccine unless it had been tested for at least a year. Further, close to three quarters would be unwilling to allow their children to receive such a vaccine. This is priceless public insight during a pandemic as pharma races to find a COVID-19 vaccine — allowing the industry to better support governments as they prepare populations should a vaccine become available.

Beyond improvements to patient well-being, health outcomes and pandemic response, listening to patients can also improve pharma’s business operations. Understanding, for example, the factors that heighten the risk of poor adherence to medication regimens can lead to solutions designed to mitigate them — and reduce patient drop out. Further, with insight direct from users, pharma companies can optimise their Patient Support Programmes and patient support materials, while they also have access to a continuous, near real-time market research resource made up of hundreds of thousands of highly engaged patients willing to share experiences.

From bad medicine to good

The democratisation of data is here, and it’s here to stay. Pharma’s longstanding reluctance to join the conversation simply isn’t sustainable. The choice is whether the industry engages quickly and willingly or continues to resist and is dragged into the 21st century under duress. The former will go a long way to restore patient trust, while the latter will further undermine it.

Pharma needs to capture deep patient insight into its medications, which it can apply from product development to marketing to patient support. At the same time, this will allow users to feel empowered in helping to shape a medicine environment that reflects, recognises and responds to their daily experiences.

The tragedy is that a continuing failure to join the conversation hurts pharma companies, health systems and millions of medicines users around the world. Now is the time for pharma to join the feedback revolution and turn bad medicine to good.

About the author

Claus Møldrup is co-founder of DrugsDisclosed.com and CEO of DrugStars.

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What can we learn from women’s health data?

Analysing real-world health data could help overcome the bias towards men in traditional medical research, says Sensyne Health’s Dr Lucy Mackillop.

Collecting and analysing anonymised patient data has the potential to generate valuable insights that can catalyse research, lead to improved patient care, and power the development of new treatments.

Being able to analyse large data sets can provide a better understanding of how some patients will respond to a treatment or predict who may develop a disease based on data collected during clinical care.

Medical research has often focused on men, meaning that the insights gained have not always been reflective of how women would react to a treatment or disease. Women are likely to have different symptoms to men for the same illness and do not necessarily have the same reactions to certain drugs or respond to the same doses as a male counterpart.

Therefore, it is important to increase the collection and analysis of women’s health data so better insights can be gained for supporting their care.

“The effect of failing to include women proportionately in clinical trials may have consequences for the quality of medical care women receive, with therapies, doses and risk assessment tools being tailored to the male population”

The impact of underrepresenting women

Research from the Allen Institute for Artificial Intelligence found that over the past 25 years, although women have made up nearly half (49%) of participants across drug trials, for many types of disease the proportion of female participants did not match the gender breakdown of real-world patients. In trials for cardiovascular, HIV, kidney disease and digestive diseases, women have especially been underrepresented.

The effect of failing to include women proportionately in clinical trials may have consequences for the quality of medical care women receive, with therapies, doses and risk assessment tools being tailored to the male population. The use of real-world medical data from women may change this – and more broadly, ensure that representative samples of data are used for the disease or issue.

What we can learn during pregnancy

As well as collecting more representative samples of data from women for conditions like cardiovascular disease, accurate data collected during pregnancy could offer a valuable information.

This is because typically, ‘real-world’ medical data is collected from patients who are ill. However, pregnancy is a unique time when large quantities of data are collected in otherwise ‘healthy’ women.

Pregnancy can also act as a cardiometabolic stress test for women and reveal underlying susceptibilities to conditions such as diabetes or hypertension.

Therefore, by analysing the data collected during a woman’s pregnancy, clinicians can view a window into future health risks and understand who is most at risk. This helps develop better preventative strategies and also prioritises care.

Last year it was estimated that 20% of pregnant women in the UK were affected by gestational diabetes, while each year, up to 15% of pregnancies are affected by hypertension. Developing therapeutic strategies and individual care pathways may allow for prevention or delay in these diseases, both for the mother and her offspring.

Improving health of future generations

Research has found that the environment in which a baby grows has a significant impact on its health throughout its life. This means that being able to improve the way we care for pregnant women through collecting and analysing data can also significantly influence the health of their offspring.

While collecting data from patients is important in development of new treatments, clinical research, and patient care, there must be a greater focus on ensuring that women are well represented in trials.

For pregnant women in particular, the information that their medical records can offer must be recognised, and databases that can be used to support the improvement of care and outcomes has the potential to provide important insights.

About the author

Dr Lucy Mackillop is a consultant obstetric physician at Oxford University Hospitals NHS Foundation Trust; honorary senior clinical lecturer, Nuffield Department of Women’s and Reproductive Health, University of Oxford; and chief medical officer at Sensyne Health.

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Data hackathon analyses truth behind TB vaccine and COVID-19

Is a century-old vaccine a ‘game-changer’ for COVID-19? Anita de Waard from Elsevier and Radoslav Kirkov from Estafet tells us how a hackathon is harnessing data science to look beyond the hype and seek definitive clinical evidence.

Today, the notion of ‘data science’ has permeated almost every area of society. Words like machine learning, artificial intelligence and deep learning have entered the everyday business lexicon. From government agencies to online retailers, a ‘big data strategy’ is a must-have. This year, as the COVID-19 pandemic has spread, there has been increased talk of statistics, modelling, predictive analytics, and using data to solve the serious issues we face.

But often, what purports to be data science is actually just a random correlation between different data sets. The phrase ‘data science’ is often used to represent any form of data analysis, however rudimentary, and regardless of whether it is based on scientific understanding. Given the amount of faith we increasingly put in algorithms to make decisions on our behalf, whether in our hospitals, our courts, or our education system, we need a much deeper understanding of how these correlations are drawn, and what they are based on, in order to apply data science for good.

This is especially true in the search for effective therapies to fight COVID-19, and a vaccine. Speed is truly of the essence, but at the same time, the integrity of the science underpinning any clinical recommendations must be maintained. With so many research projects, collaborations and clinical trials taking place in an attempt to limit and prevent the virus, we have to be clear on how decisions are being made and what the data behind an apparent breakthrough is really telling us.

“In a worst-case scenario, misplaced hype could lead to a sudden rush to buy doses of the BCG vaccine. In nations where TB is widespread, this could put many lives at stake”

Understanding the link between COVID-19 and the BCG vaccine

A good example of this phenomenon is the sudden hype around the Bacillus Calmette–Guérin (BCG) vaccine, which is primarily used against tuberculosis (TB). This century-old vaccine came to prominence recently, when a number of early ecological studies (those which study population factors in epidemiology) seemed to show a strong correlation between receiving the vaccine and having immunity against COVID-19.

Some studies suggested the link was a “game-changer” and a “silver bullet”. The studies claimed to show a strong correlation between the BCG vaccination and protection against COVID-19, but closer examination revealed a tenuous correlation, from which clear conclusions can’t be drawn. Indeed, the World Health Organization said that, “Such ecological studies are prone to significant bias from many confounders, including differences in national demographics and disease burden, testing rates for COVID-19 virus infections, and the stage of the pandemic in each country.”

The world-leading TB researcher Prof. Madhukar Pai was also quick to warn of the serious limitations with this approach and the need to be cognizant of confounding variables. In a worst-case scenario, misplaced hype could lead to a sudden rush to buy doses of the BCG vaccine. For developed nations with low TB rates, this would have little impact. But in nations where TB is more widespread, such as India, the potential implications of a sudden shortage of BCG vaccine could put many lives at stake.

The aim now must be on providing stronger clinical trial evidence of the link between the BCG vaccination and incidence of COVID-19, to enable data-led decisions to be made. There are clear shortcomings with current ecological studies, which take aggregated data and look to make inferences at an individual level. If the data are not representative or confounders are not taken into account, the results will be inaccurate.

Establishing an evidence-backed link

The only way to truly understand the correlation between COVID-19 and the BCG vaccine is to conduct randomised trials combined with deep analysis of existing data. To that end, Estafet and Elsevier have initiated a two-stage hackathon. The groups are working together with the BCG World Atlas team, which is led by an infectious disease specialist at the University of Ottawa, Dr Alice Zwerling. The BCG Atlas is an open-source database of global BCG vaccination policies and practices, founded in 2011.

Many of the aforementioned ecological studies were based on data from the BCG Atlas, so the first stage of the hackathon aimed to augment and improve the Atlas; with additional data and health records available on BCG vaccinations. These have been found through natural language processing (NLP) methods. With thirty volunteers globally, including judges, organisers, and data gatherers, prizes were awarded to those deemed to have extended the data most. The winner was Dimitrina Zlatkova of Sofia University, who contributed 57 additional data points, followed by developer Marouane Benmeida of Morocco who added 33 additional data points.

The hackathon now moves to stage two, where the volunteers will seek to answer a series of questions, such as whether the BCG vaccination is causally related to reduced COVID‐19 mortality, or if other factors like lockdowns and average age of the population are responsible for the different mortality rates. If the BCG vaccination does reduce COVID-19 mortality, what are the key factors. For example. how long does the immunity from BCG last after that vaccination? Does the strain of BCG vaccination impact immunity? The team is now looking for more volunteers to get involved as the hackathon progresses. Once complete this most valuable insights from the task will be shared with the ongoing BCG COVID-19 clinical trials.

Data science for good

When it comes to COVID-19, data science will certainly be critical – but it is the blend of scientific understanding and technical acumen through data science that is vital.

It is a job for all of us engaged in data science projects – whether in academia or commercial or government research – to stem the hype. It is important to assess the veracity of a claim before accepting any conclusions, and empower the public to do the same. This habit of mind is important not only in the development of treatments and vaccinations, but paramount to establishing a broad public trust in data-led decision making.

About the authors

Anita de Waard is VP research collaborations at Elsevier and Radoslav Kirkov is technology director at Estafet.

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How real human experiences can power a healthier future

As part of our series of opinion pieces from leaders at Janssen, the company’s Maria Raad looks at how we can embrace tech and data science to overcome increasing pressures on healthcare systems.

For the next generation born in the western world, living to be the age of 100 will be the norm. While this seems like a desirable aspiration for our grandchildren, it adds new pressures on our healthcare systems. The number of people living with chronic illnesses will rise year-on-year, and the ongoing management of  illnesses like diabetes and cardiovascular disease will require ever increasing resources.

This is nothing new. Healthcare expenditure is growing faster than GDP the world over, a trend that has been amplified by the COVID-19 pandemic. Together, these forces have accelerated technological transformation, acceptance, and adoption across our industry, reinforcing my belief in the ‘triple aim’.

The triple aim considers how we balance the needs of the individual with pressures on our health systems and, in a phrase coined by Berwick, Nola and Whittington in 2008, it is defined as:

  1. Improving an individual’s experience of care
  2. Improving the health of populations
  3. Reducing the per capita costs of care

Changes to any one of these goals can affect the other two, negatively or positively. In order to succeed, we must shift the paradigm of healthcare and drive towards more objective measurements of value and improved experiences for everyone, to create a truly patient-centric system of care. ​

In the past, our collective adoption of, and trust in, digital technology has been incremental and often reluctant. All too often approached with a narrow mindset, such technologies have been regarded as simply tools to reduce costs or lessen the need for human interaction, when they have the potential to do so much more.

As the scientific evidence behind digital solutions has grown alongside our accelerated need for changes, we’re starting to see the full potential that data science might offer – a potential to create more efficient disease management solutions, reduce the economic burden of healthcare and, most importantly, empower patients to be integral decision-makers in their own care.

Real-time digital solutions for real-world evidence

Two billion people have access to mobile health data, but simply having access is not enough. It is how we use health data that will drive us forward. The emergence of big data, smartphone adoption and cloud storage technologies means that information can be captured in real-time, and then aggregated and analysed to develop new insights.

Collaborations such as HONEUR (Haematology Outcomes Network in Europe), which brings together a partnership of universities, hospitals and institutions across Europe, can help with this by bringing together multiple stakeholders to analyse real-world data (RWD), quickly and at scale, from as many sources as possible. By answering research questions in real time, partners can extract real-world evidence (RWE) that informs their conclusions and accelerates their work.

While acceptance varies between countries, we believe RWE is a key component in moving towards a more value-based healthcare model, as it is one of the few under-utilised resources left in our field.

Healthcare companies are now working with tech companies to put innovative, data-capturing tools directly in the hands of the individual. Wearable tech and mobile health apps can provide patients with information, allow them to manage medication, and help them to become experts in their own condition. This personal depth of knowledge can complement the quantitative data on which we currently rely, so we must ensure it’s integrated into treatment pathways going forward.

Combining digital therapeutics with pharmaceutical innovations

The pandemic has prompted a significant uptake in the use of data technologies. Clinicians, patients and payers are utilising the potential of these platforms, and many are doing so for the first time. We will, however, need to embed such changes across all parts of our healthcare systems, and I believe there are four foundational elements to this:

  • Evolving from sick-care to well-care: healthcare systems are struggling to provide care via traditional models, which are largely based on treating illness rather than preventing it. This means moving on from just products and treatments, to platforms and solutions focused on prevention and real-time, outcomes-based care. Digital technology will be a major contributor to this transformational shift from diagnosis and treatment to prediction and prevention.
  • Data science: harnessing data networks, artificial intelligence and real-world evidence, and the interdependence between all three, can help move us towards agreeing an objective measure of value for any given therapy. That’s essential if we are to build a new healthcare ecosystem, and if we get it right, everyone will benefit.
  • Long life care: ageing populations are growing in size and increasing the pressure on healthcare systems. Without digital technology, the amount of resources required to manage long-term, non-communicable diseases will be unsustainable.
  • Personalised care: digital therapeutics, when certified as medical devices, can enable clinicians to prescribe a treatment system that goes beyond the pill. They can also engage patients more effectively in their own care, through real-time symptom monitoring, for example, or by providing physiological support for those dealing with the burden of disease.

These are not short-term solutions. The ultimate goal is healthcare that’s thriving, sustainable and accessible to all. And we can drive towards that goal by harnessing and sharing the benefits of the ever-evolving technologies within our reach. But it’s a team sport – the days of any individual, organisation, government or industry attempting to change the world on their own are gone.

Data science actually has the potential to make healthcare more human. And, as we look to the next 100 years, with all this technology available to us, perhaps there’s reason to hope that we will yet see a world where fewer people get sick and more people live longer, healthier, happier lives.

About the author

Maria RaadMaria Raad is vice president, customer & digital strategy, EMEA at Janssen. In this capacity, Maria is responsible for the functions of business intelligence, advanced analytics, digital acceleration, and patient healthcare solutions. She has held various positions, since joining Janssen in 2006 – prior to her current role, Maria was Global VP & Chief Information Officer of Actelion, and a member of the Actelion leadership team based in Basel, Switzerland.

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Rare diseases, repurposing and the role of AI

In the age of artificial intelligence, no trial data should be going to waste. Findacure’s Rick Thompson looks at how these technologies could bring us closer to treatments for underserved rare diseases.

The repurposing of drugs is becoming more common, especially in the field of rare diseases.  In the past, repurposing has mostly been driven by academics looking for new possibilities in generics. Now, as part of lifecycle management, pharmaceutical companies are looking more closely at drugs they have on their shelves. These might be licensed drugs that could hold potential for a patent extension, or drugs which failed efficacy trials for an intended indication.

In the quest to repurpose a drug for a rare condition, there is a need to look at any and all available data. The wealth of published scientific literature forms one crucial source of data, with the ever-expanding pool of ‘omic data forming another.

A third pool of clinical evidence is formed by trial data, which will probably only be considered through the published literature. By definition, however, trial master files represent a much richer and more detailed source of data on a drug and how it performs. Published literature tends to catalogue successful clinical trials, but value can also lie in a trial that did not lead to a positive and viable outcome: the data it produced could still provide evidence for repurposing. For instance, provided a drug has not failed a trial on safety, the side effects it caused in one population could constitute on-target effects in another.

With large datasets crucial to gaining an understanding of rare diseases and opening the door to drug development, digital technology is proving transformative. It enables careful collation and organisation of information, but the innovations of artificial intelligence (AI) are now taking things further, facilitating the effective analysis and interrogation of big data to create new treatment hypotheses.

“Patient associations are working to develop registries (some using wearable technologies or apps) and natural history studies, which means that ever-greater volumes of data are being produced”

These techniques make the production of and access to high-quality data on rare diseases the gateway to treatment identification, and so are proving more crucial than ever for organisations in pharma.

Digitised, rigorously controlled data lends itself to techniques of processing and analysis which characterise both drug discovery and drug repurposing.

Raw text can be analysed by Natural Language Processing (NLP) techniques which form connections between studies that could otherwise take thousands of hours of human time to identify.

When combined with analyses of ‘omic approaches, and an appropriate level of disease-specific knowledge from patient groups, you can create a powerful resource for the identification of new treatment hypotheses for rare diseases – and an opportunity to address severe unmet needs.

Findacure is a charity that works directly with rare disease patient groups to help them grow and professionalise. Over the last five years we have focused on the power of drug repurposing for rare genetic diseases. It is estimated that, worldwide, just 400 treatments are licensed for 7000 known rare conditions, which tend to be determined by a very specific genetic factor.

As a consequence, most patients are being left with no hope of a treatment in their lifetime. Luckily, patient associations are working to fill the void by uniting patients and driving research forward for their conditions. Many are working to develop registries (some using wearable technologies or apps) and natural history studies, which means that ever-greater volumes of data are being produced.

This drive to generate data on and interest in their condition – along with the collated knowledge of their community’s lived experience of rare disease – can prove transformative to the treatment landscape. We are now seeing patient associations involved in several collaborative efforts that are identifying drugs which, as candidates for repurposing, stand to deliver treatments to rare disease patients more quickly and cheaply.

In 2020, the pharmaceutical industry has not by any means proved immune to the disruption caused by COVID-19. But, as in other industries, the pandemic has accelerated the process of digital transformation that was already underway.

A recent survey of more than 200 life sciences professionals, conducted on behalf of digital archiving specialists Arkivum, found 70% of respondents saying that COVID-19 has triggered a change in the way clinical trials will be conducted. There can be no doubt that digital technology will play a key role in that change. The survey reports that over 90% of sponsors and CROs have already adopted an eClinical application to improve study execution and data collection in live trials.

When a trial is completed, the valuable and extensive data it has produced must be archived – an exercise crucial both to regulatory compliance and to any future efforts at repurposing. 70% of sponsors reported that they use a digital archive rather than the traditional paper-based option, and 45% of respondents cited the role that clinical trial data plays in finding new indications and formulations. Yet at the same time, 38% of sponsor organisations described their ability to access archived clinical data and records as ‘extremely or very inadequate’.

This percentage rose to 65% amongst QA, compliance, legal and regulatory professionals. Moreover, just 31% of life sciences organisations seem to run a digital archive of sufficient sophistication to ensure that data can be managed in accordance with the FAIR data principles.

These were established to further scientific study through keeping data Findable, Accessible, Interoperable and Re-usable – all key attributes when it comes to exploring the new potential of an existing drug.

In the search to repurpose drugs, readier, more reliable access to archived trial data – including trials that produced negative results – can clearly prove highly beneficial.

If data has been well stewarded before and after it reaches the archive, and if its integrity has been maintained through careful curation, it facilitates the application of AI techniques. Natural language processing can be used in conjunction with, say, analysis of ‘omic-level data and patient group insights in order to work through the problems and side effects encountered in the full spectrum of trials. This can open the way to repurposing for different populations, and to new approaches to the design of clinical trials.

The success of these endeavours will also be favoured by the availability of comprehensive rare disease registries which collate patient-level data on disease natural history while also bringing together a pool of patients who could participate in trials.

Meanwhile at the pre-competitive stage of drug development, researchers are adopting a more open, collaborative approach to data. Now is the time to enable further collaboration by increasing access to historical data and releasing its full value. Success in finding treatments for rare disease is above all the product of collaboration, as technological innovation complements and amplifies a compassionate, patient-centred approach.

In all this, it is worth remembering that the people who participate in clinical trials – especially in the field of rare disease, where recruitment of patients is a particular challenge – would appreciate knowing that their participation will have a lasting value, whatever the outcome of the trial.

Trial participants take on a burden by putting in time, effort, hope and commitment. They also put themselves at some degree of risk whenever they take an experimental drug. In the field of rare diseases, trial participants are hoping to help the next generation of patients even more than themselves.It is crucial to maximise the potential value of data they are helping the professionals to collect.

With repurposing on the table, and improved access to all trial data, we can better unlock this potential.

About the authors

Dr Rick Thompson is CEO of Findacure, a UK charity dedicated to building the rare disease community to drive research and develop treatments.

Tom Lynam is head of Marketing at Arkivum, specialists in digital preservation of valuable data in life sciences and global scientific institutions.



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J+D Forecasting, known as the experts in pharmaceutical forecasting, has today announced the launch of EpiCube; the latest addition to its comprehensive suite of pharmaceutical forecasting products.

Unlike most standard epidemiological databases available, EpiCube is the first database where the user can choose how to build their own data set; be that by country, disease, or a specific attribute such as a bio marker.

Using Microsoft’s latest technology, data can be interrogated, analysed, and shared. Underpinned by J+D’s forecasting expertise, EpiCube aligns to pharmaceutical forecasting structures and helps pharmaceutical companies explore risk factors and underlying causes affecting the size of the patient pool for their new and existing products.

EpiCube is an epidemiology database for multiple therapy areas, including Oncology, multiple diseases, attributes, countries, age groups and genders. There are over 9,500 sub-groups and over 200 diseases across 50 countries. Click here for more information: https://jdforecasting.com/software/epicube/

David James, CEO, J+D Forecasting:

“We have developed EpiCube to help clients understand diseases better, so they have more time to think. To think about the forecast, to look at the assumptions, to test hypotheses better and to spend the time creating a good forecast.

We want to help pharmaceutical companies create maximum shareable insights in their forecasting approach, speed it up, visualise insights instantly and focus on what really matters.”


Pharma’s digital transformation journey and the role of customer reference data

Better management of customer data could help pharmaceutical companies’ digital transformation, according to Veeva’s Rebecca Silver. pharmaphorum’s Richard Staines spoke to her about how the use of customer reference data can transform pharma companies, increase competitiveness, and benefit the bottom line during these challenging times.

Precision medicine is emerging as a key approach for disease treatment and prevention, which makes it even more critical to get the right medicine to the right patients. But according to OpenData’s general manager Rebecca Silver, the industry is often challenged with having accurate data on the doctors and the organisations they work for.

Times are changing, though, and with the advent of COVID-19 the use of digital technology has increased considerably. One of the noticeable effects of this has been a massive uptake of remote working across the industry, which has accentuated difficulties in conducting remote sales engagements due to poor customer data quality.

The changing pharma environment during COVID-19

According to Silver, the coronavirus pandemic changed the pharma industry’s priorities overnight, and several other factors are transforming the way that pharma companies are interacting with doctors.

Speed to market is all-important in accelerating innovation, she notes, adding that using customer data well is crucial to get the kind of targeted approach needed when interacting with healthcare professionals.

“Personalised medicine is driving the need to get more information to more physicians. It’s targeting the right medicine to the right patients, so giving very specific information to physicians is really important”

“Personalised medicine is driving the need to get more information to more physicians. It’s targeting the right medicine to the right patients, so giving very specific information to physicians is really important.”

But Silver identified some challenges that must be overcome to allow pharma companies to make the most of their customer reference data. For example, data is often siloed in different parts of the company, instead of a centralised database that allows company-wide access.

Quality of data is another issue identified by Silver as being detrimental to a coordinated approach to customer relations management. She pointed to the Veeva European Customer Reference Data Survey that showed 41% of companies are not satisfied with the quality of their third-party legacy providers of customer data.

“Complexity comes in when data’s in silos and fragmented. If the data is in silos within a pharmaceutical company, you’ll find multiple people that are buying the same data assets and storing them and managing them in various systems completely disconnected from each other.

“It’s almost impossible to get a single, comprehensive view and an actionable view of their customer. It makes it really difficult to derive insights from that data because they’re not getting the full picture of their customers.”

Real-time updates

Ensuring that customer data is accurate and up to date is a priority, no matter what size a company is.

One way of making sure that the data is also useful to reps is having technology that allows customer data to be updated in real-time, whether they are looking to engage with healthcare professionals directly or via remote detailing, according to Silver.

Good data governance will help to get the information accurate and up to date – but making a case for improving it isn’t always an easy task.

But Silver said it’s possible to make the case for strong data governance by outlining the productivity benefits it can bring by taking steps to identify who owns the data and ensuring a single department is responsible for curating it.

“People don’t like the term ‘governance,’ but it’s the reality of it, and there is a strong impact. If companies have data governance issues and undertake initiatives to improve data management, they’re more likely to be satisfied with the ability of their data to support their analytics.”

Properly curated customer data allows reps to make fast decisions, as they have confidence in the information available to them.

Silver said: “Customers want their reps in the field to be able to react with speed and they want to maximise the value out of their investment of those reps. So, it is important to empower the sales rep with the most accurate data updates while they’re standing in a hospital and can still effectively execute on a call, for example.”

C-suite taking notice

Despite these challenges Silver said pharma companies are more likely to overcome them now that the C-Suite is starting to notice the issue.

Companies are increasingly realising that their customer data is an important strategic asset that can have a real impact on the bottom line. Driving this is a realisation at executive level that getting customer data right is crucial to keeping a company competitive.

Pharma companies that don’t use data as an asset risk falling behind, whether they are competing in a tight market where there are many other therapeutic options available or whether they are launching a new product and under pressure to bring in sales.

Silver said: “All of that pressure and that stress has increased the awareness around data in the C-suite. So, what I’m seeing is many business leaders are re-examining their data organisations and searching for opportunities to reduce wasted time and effort, while at the same time increasing productivity.”

Data is ‘cool’

The digital revolution has moved far beyond fascinating gadgets and devices, and promises to profoundly change the way pharma companies operate.

Pharmaceutical companies are starting to adopt a business model with data as a foundation for the company’s strategy.

Customer data and helping reps on a day-to-day basis will be at the heart of this, but companies will also be guided during crucial projects such as launching new drugs, when pharma must maximise opportunities in the often-crucial initial window for sales.

According to Veeva, the COVID-19 pandemic is likely to fundamentally change the way pharma companies operate as they are forced, at least in the short term, to move away from conventional sales operations based on face-to-face meetings with doctors.

These will still have their place, but the future is expected to favour a hybrid approach as the importance of digital support for physician interactions grows, driven by innovations in multi-channel materials and remote detailing.

To guide this hybrid approach, pharma companies should look to the insights that can be found through a sophisticated analysis of CRM data – the advantages of which are increasingly being recognised by those at the very top of their organisations.

Silver concluded: “Customer data is the foundation of companies’ success; data is now cool.”

About the interviewee

Rebecca SilverAs general manager, Veeva OpenData, Rebecca leads a dedicated team of product managers, data stewards, engineers, and services professionals to deliver a superior reference data experience for Veeva customers. Before leading the global OpenData team, Rebecca was vice president of Veeva OpenData North America, where she led the launch and growth of Veeva’s data offering. Earlier, as VP, professional services, North America, she directed successful implementations of Veeva’s suite of commercial products for many of the world’s most prominent pharmaceutical companies.

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The value of good data to patients

Better patient care pathways and models of care can be leveraged from the use of data, and the ability to collate and assess this information will drive more sustainable models of care, whilst unlocking the value of ‘longitudinal, real-world data’ as a resource for healthcare organisations, research and academia, policy advisors and pharma.

There is a societal shift that is required though, to educate patients on the value of this data and how it can be used to improve the outcome of patients globally. Samir Dhalla, head of THIN and Richard Ballerand, co-chair of THIN’s Patient Advisory Committee, explore how ‘good data’ can power this.

The benefits for public health

Data has been essential in the fight against COVID-19, with records used to identify and notify 2.2 million individuals who were at significant risk from the virus, and to advise them to shield. Ongoing tracking and data analysis of the virus has also allowed for data profiles to be built up around the types of conditions that result in COVID-19 posing a greater threat, for instance Type 2 diabetes. The NHS has proven the value of public health data in this way, and globally it has been a powerful tool to assess risks and treatments.

It’s also helped to drive research – for example the European Health Data & Evidence Network’s (EHDEN) took part in the OHDSI COVID-19 Virtual Study-a-thon which rallied 330 researchers with very different backgrounds and from thirty different countries. It also launched its COVID-19 Rapid Collaboration Call in a bid to plug the gaps in fragmented, siloed and poorly interoperable real-world health data in order to characterise patients, manage their care and assess treatment safety.

“The public are generally comfortable with anonymised data from medical records being used for improving health, care and services. However, there is still worry around this health data being accessed by commercial organisations”

These forms of national and international collaboration have shown the power of data in managing the pandemic, as the importance of population health data in identifying and containing the virus has not been overstated. The NHS has created its own COVID-19 Data Store for instance, and on top of this, analysis of 16.2 million anonymised longitudinal patient records revealed a significant increase in the proportion of lower respiratory tract infections diagnosed by late 2019 compared to previous flu seasons, raising the odds of UK COVID-19 cases having appeared earlier than previously thought.

By harnessing the information in electronic health records, such findings clearly open the path to near real-time tracking of large-scale population health events that can support public health bodies to detect, investigate, and respond timely and effectively to them.


Patients are becoming more content for their data to be used in this way, however it must be anonymised to tackle privacy and trust concerns. The public have reported they are generally comfortable with anonymised data from medical records being used for improving health, care and services, for example through research. However, there is still worry around this health data being accessed by commercial organisations, and so the privacy and broader benefits of patient data must be emphasised.

For instance, data can be used to improve diagnosis speeds and anonymous data can be overlaid onto NICE guidance, as well as within local and national patient pathways to provide better insight into the types of treatments that might work more effectively for certain patients. ‘Cohorts’ of patients can be created as well as effective treatment profiles based on these individual characteristics, to ensure the most effective treatment pathway is selected and faster. These can be based on existing health conditions, for example diabetes, and co-morbidities. Information such as age, weight, sex, faith, ethnicity and lifestyle choices can also be included to help specialists get closer to the best treatment the first time around to improve patient outcomes.

A prime example of the value of this type of data is in the case of pancreatic cancer, a disease that is often diagnosed late and progresses exceptionally quickly. It’s the deadliest common cancer, and by the time a diagnosis is achieved, many individuals are at stage three or stage four, with 75% not surviving a year after diagnosis. Symptoms are vague and often confused with other conditions such as pancreatitis, gallstones, irritable bowel syndrome (IBS) or hepatitis.

For both GPs and patients, embedding detailed symptom information within clinical systems would be hugely beneficial, enabling far earlier diagnosis and hospital referral. The GP would spend far less of the budget on one specific patient and it would ensure that the patient receives the best treatment possible for that diagnosis and faster referral to the right clinician.

Predictive modelling

Data analytics can also be used to better understand patient responses to specific treatment types and surgeries, by using predictive modelling to map out likely outcomes – enabling pharma to work closely with healthcare professionals and services to get closer to ‘the right medicine, to the right patient, first time’.

Modelling based on real-world data allows for tailoring and marketing specific medicines to specific groups of patients with specific predispositions or health conditions, and it reduces the ‘trial and error’ process that clinicians sometimes have to follow to find the appropriate treatment.

For example, analysis of cardiac surgery patients has evaluated the risks for certain types of heart surgery as well as post-surgery, taking into consideration a number of factors, including age and ethnicity to improve recovery. This can be extended to provide individual patients with information about their health conditions and risks to empower and encourage them to make changes to lifestyle or behaviours. This Predictive, Preventive and Personalised Medicine (PPPM) explores a complex mix of personal and population health data to avoid future health deterioration or detect problems before they arise.

Utilising datasets

Ultimately, PPPM will help patients to take control of their own health issues. Retaining individuals within primary care will both save money by reducing the pressure on secondary care and release investment in other areas of high demand healthcare. On a broader level, this detailed predictive model will allow the healthcare system to potentially predict population health issues over the next three to four years, helping to allocate resources to the correct specialties at the right time.

The key to this process is early identification of potential health issues, which requires proactive collection of patient health data – from weight to cholesterol and blood pressure readings. Understanding the trajectory of these readings over the past year, combined with predictive modelling as to the potential outcome if no preventative measures are taken, will help clinicians to present personalised patient advice.

The other important factor is the volume of the datasets used in analysis. The pool of reliable patient data must be detailed and vast in order to provide a complete picture and inform decisions. Globally it’s known that there is significant value to be had, but many researchers are still relying on synthetic datasets which mirror real-world data. This data simply fails to deliver the depth of insight delivered by real-world patient data.

It’s clear that the analysis and use of global health data can drive better patient diagnosis, treatments and ultimately outcomes. There has been a societal shift around the use of personal health data in recent months, as the value of it has been shown in the fight against COVID-19, and this change can continue to leverage benefits.

Primacy Care data is being utilised to inform patient pathways across a range of disease areas and enable better understanding of local health economies, while GPs have a chance to inform life-changing medical research, supporting research crucial to gaining insights and developing policies, and helping to highlight trends in clinical effectiveness within the NHS.

Patient data can achieve significant changes in preventative care and improve global health for the better; but it has to be the power of good data.

About the authors

Samir Dhalla is Head of THIN and Richard Ballerand is co-chair of THIN’s Patient Advisory Committee.

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COVID-19 is Bringing Data Privacy into the Spotlight – This is How Healthcare Companies Should Respond


Privacy concerns across the country continue to increase, and consumers expect their healthcare information to be private. Headline-making data sales, skepticism of Silicon Valley privacy practices, and COVID-19 contact tracing concerns compounded with a general lack of consumer awareness have continued to generate an ongoing storm ofnegative press and political scrutiny.

With COVID-19 continuing to rampage throughout the country, there is a need for the contact tracing and other technology applications to assess public health. At the same time, changing HHS rules are giving Americans more access and control over their own health data. Both availability and the promise of positive impact of data on people’s lives has never been greater.

Despite the critical need and incredible potential, there is still a great deal of confusion, lack of awareness and heightened concern among consumers. Studies show that the vast majority of Americans think the potential risks of data collection outweighs the potential benefits.

Clamping down on data privacy stifles innovation, and moving forward as we’ve been doing presents a potential privacy minefield. So, what should the healthcare industry do about it?

It is clear that data privacy, and particularly health data privacy, is crucial to consumer trust. Yet we also know thatconsumers are unclear who may be collecting their health data, or how it is being used.

That said, a recent study has shown that consumers want privacy protection, informed choice, and control over their data. It also revealed that people are more willing to share health data for altruistic reasons – either to advance their own health or to help advance public health and medicine in general.

Consumers believe that their health data is private information, yet they are more willing to share their data for the right reasons, with the right levels of communication, and with privacy protection. However, one thing is lacking: Thehealthcare industry does not do a good job of providing education or communication to consumers on the critical need that health data can fulfill. 

What can healthcare companies do

To accelerate innovation through the use of patient data, healthcare organizations need to start taking consumer privacy expectations seriously.

Educate and communicate: Most people do not understand how health data can be used to develop new therapies, and only 29% believe it is being used to improve healthcare outcomes. Yet many consumers would share their health data if they knew it would be used to improve healthcare outcomes for others. Altruism is a stronger motivator for sharing health data than even paid compensation.

Provide informed choice: The vast majority of people believe that their health data should either not be shared or only shared with their permission. In addition, privacy legislation and consent requirements are getting more complex world-wide. An opt-in mechanism ensures that organizations have the opportunity to educate consumers on the amazing work that their health data can contribute to. This approach of including patients more directly in data collection will also create additional health research opportunities beyond the data recorded in medical records.

Address the generation gap: Boomers are well known to be more distrustful of technology and data collection. The same study showed that less than 30% of those ages 55 to 75 (an age group that might benefit most from COVID-19 interventions) indicated a willingness to download a contact tracing application compared to about 65% of Millennials (ages 25 to 39). Again, education is key – lack of communication about data access and storage significantly decreases the likelihood of downloading.

Let’s get on this

Data is essential to driving progress and innovation in healthcare, and the COVID-19 pandemic has placed the spotlight directly upon privacy. Interventions such as contact tracing and related technology applications in digital health have created an urgent need for companies to provide greater clarity around how health data is used.

To achieve the advances necessary to tackle COVID-19 and other healthcare challenges, organizations must proactively consider and respond to these privacy concerns. Addressing expectations and spending the time and money needed to educate the general public, particularly on the altruistic reasons for sharing data, is key to ensuring that data-driven insights continue to add value to the healthcare industry.

Dan Linton is the Global Data Privacy Officer at W2O, where he supports internal and client data privacy and protection practices with a specific focus on GDPR, CCPA and the impact of global privacy legislation on healthcare marketing and communications.

CMS to penalize hospitals, labs that don’t report Covid-19 data

New rules by the Center for Medicare and Medicaid Services would penalize hospitals and laboratories that report Covid-19 data. Hospitals would be required to report the number of confirmed or suspected Covid-19 patient, occupied beds, and availability of ventilators and other critical supplies.

Next wave: how pharma analytics can be improved with new technologies

Pharmaceutical companies have always had access to a steady stream of data to look at what has happened in the past and to try to predict future prescribing trends.

Business intelligence (BI) departments have supported this throughout with timely and effective reporting, within an environment that has seen in recent years a bit of an ‘arms race’ with BI tools adding an increasing array of chart types and functionalities.

To date this has been typified by the visual approach of the ‘fish tank’ chart. But now technology – specifically artificial intelligence (AI) and machine learning – is poised to offer new ways of analysing and processing data, allowing the pharmaceutical industry’s use of analytics to step up a gear.

Business intelligence analytics today

BI provides key metrics for pharma companies to track sales performance over time, whether through market share, contact rates or other endpoints.

You absolutely do need to know what worked in the past when you’re making your future plans, but the various retrospective figures that have been available to pharma to date can only show occurrences that have been and gone.

Different metrics have come into fashion and then departed, with some even coming back around again. However, they only look at the traditional questions companies ask of their sales teams: Are we doing well? Are we hitting our targets? Are we growing? How do we compare with the competition?

Meanwhile, recent years have seen some major changes in the types of information that is available to those in pharma who assess sales and marketing performance.

Traditional NHS prescribing data has been augmented by information on biosimilar uptake across the health service, real-world data and other sources, while the data sets available to pharma have also increased in size. The advent of this big data means the typical pharma sales rep might now receive up to 4,000 data points a month, depending on the size of their territory and the number of competitor products or packs in their markets.

But there are limits to the insights that such large data sets, on their own, can bring to the industry – not least because diving fully into all of the data that is available would be a full-time job in itself.

Why we need to improve current BI tools

To make the most of modern-day analytics requires a new approach. The users of these data sets fall into a number of different types, all of whom must be catered for, but typically they’re all non-analysts. Our core users come from pharma sales and marketing, and it’s important we give them as much value from the data in the time they can spare from their regular duties.

In this way we can help up everyone’s game so that they can in turn have a bigger impact on business performance. What we’re trying to do as a consultancy is shift that curve a little bit, so that everyday users – as much as super users – benefit from these tools.

Timeliness is another area where improvements are needed. The worth of current business intelligence tools has long been proved, but they’ve had to focus on what has happened in the past and, within this, deal with time lags with the data.

Even the most up to date mainstream sales and market data will only arrive at the end of the following month, which in practice means a one to two-month lag on the period it covers. It’s great to learn from the past, and an important part of how analytics should be used, but it’s also a side of business intelligence that can be further enhanced.

New BI technology for pharma

To date, technology has been a limiting factor for development. Business intelligence has always been haunted by this to some extent, but tech’s continual advances mean that it will get better. As it does pharma should be looking for improvements to come from the insights it can uncover from the data, and particularly by combining large datasets.

With the ever-increasing size and number of datasets that are available, new technology can provide a hugely valuable ‘noise cancelling for BI’ role, allowing those in pharma to cut through the white noise to get to the relevant information. It’s here that machine learning can come into its own, doing some of the heavy lifting that your data requires; if the thousands and thousands of data points it offers are to be made sense of.

At the same, applying AI to the data can start to reveal the hidden patterns from the data sets in a way that just isn’t possible when an individual has to click through 100 bricks or 200 practices and look at every pack or product prescribed to try and decide if something has happened that’s interesting. There are a wealth of different hidden patterns in the data that the human eye won’t know are there, while the machine won’t rest until they are found.

“Further value might be found as we start to assess what the post-COVID future might look like, and combining AI and advanced analytics will allow pharma companies to measure, monitor and predict this”


Advancing analytics to provide future value

Looking for patterns in the data, and at what might happen in the future, is all about helping pharma to ‘find the interesting’ in the data, and the technology that facilitates this can also free up users’ time by providing them with quicker answers.

Among those answers might be directions to redirect the marketing strategy based on the data, or to institute a wider adjustment in sales and marketing team behaviour to drive tactical change on the ground.

Further value might be found as we start to assess what the post-COVID future might look like, and combining AI and advanced analytics will allow pharma companies to measure, monitor and predict this. Certainly no AI predicted COVID-19 and the devastation it would cause, but it could assess the virus’ impact on different diseases, therapies and NHS locations.

However, as with any use of new technology, it’s vital that pharma benefit from it and, with so much talked about in AI, there is a real need to avoid ‘AI atrophy’ when solutions are built and implemented before any assessment has been conducted of where they will add value.

Answering pharma’s big questions with tech-enabled BI

How will COVID-19 change prescribing patterns, what impact will a new formulary have on physician decision-making and how will market dynamics change when a new product is launched? These are some of the big questions that a tech-enabled approach to BI analytics might answer.

At the centre of this process will be the use of machines to guide and power-up human decision-making so that pharmaceutical sales and marketing teams can look to the future, as well as the past, processing more data, more quickly than ever before.

Technology is going to do a lot of the heavy lifting for BI professionals in the future and they will also be able to give it more lifting to do as they seek to solve specific problems for their organisation. As this happens it will also provide a welcome dose of ‘de-risking’, removing elements of human error that can sometimes creep into the data.

The future of pharma analytics is about getting people to answers – and questions – quicker, so the time they spend using the next wave of BI tools can have a positive impact on the future performance of their organisation.

About the interviewee

Lee Ronan is commercial director at CSL. Lee has worked in healthcare business intelligence since 2002, beginning as an analyst and CRM admin before spending time in an SFE role as well as working on secondment as a medical rep.

He has a passion for helping clients use data and visualisations to make informed decisions – Lee’s experience in the field gives him a unique insight into the challenges and opportunities offered by the healthcare sector.

Having previously served on the British Healthcare Business Intelligence Association (BHBIA) board, Lee is now a member of the Best of Business Intelligence (BOBI) committee with a focus on organising the BHBIA Analyst of the Year competition, as well as the Newcomer awards.

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Brits more comfortable sharing data with pharma since COVID-19 – survey

New research from MHP Health and ComRes looks at what impacts COVID-19 has had on the public’s health data sharing concerns, and asks how the industry can maintain confidence in data usage after the pandemic.

In April, at the beginning of the COVID crisis, the Health Secretary Matt Hancock issued a six-month order for the NHS to share confidential patient data. Under Health Service Control of Patient Information Regulations, the Secretary of State issued four emergency notifications which inform GP surgeries, local councils, executive agencies of the DHSC, and any other “organisations providing health services” throughout England that, until 30 September, they are required to “process confidential patient information… to support the Secretary of State’s response to COVID-19”.

This effectively clears the way for the sharing of patient data with any relevant organisation, providing the purpose of doing so is solely for “research, protecting public health, providing healthcare services to the public and monitoring and managing the COVID-19 outbreak and incidents of exposure”. These notifications were put in place to support initiatives including the Test and Trace app, discovery and development of a COVID vaccine, and managing the capacity of ventilators and critical care beds.

The use of personal health data by the Government and NHS, not to mention the pharmaceutical and diagnostic industries and technology companies, is a contentious area. Under normal circumstances people need to give their permission before their data can be shared between different parts of the NHS, and with other organisations. Previous attempts to have a national conversation about health data-sharing, like Care.data, failed. Therefore, the Government’s approach to requiring data-sharing during the pandemic inevitably raises questions about privacy and personal choice.

With this in mind, MHP Health worked with ComRes to poll 2,072 members of the public to better understand their comfort with sharing their health data and to investigate if this has changed since the outbreak of the pandemic.

“The majority of people (57%) said that they are comfortable or very comfortable sharing their health data for the purpose of developing new treatments and vaccines”

The public are coming around to the value in sharing their data with the pharmaceutical and diagnostics industries

As the pharmaceutical and diagnostics industries continue to step up to the mark in the race to tackle COVID-19, 26% of people said that they are more comfortable sharing their health data with the pharmaceutical industry and 25% with diagnostic companies since the outbreak of COVID-19.

Just one quarter (25%) of people surveyed said that they would be uncomfortable sharing their health data with the pharmaceutical industry and only 23% said the same about diagnostics companies. The only organisation, out of the options we tested, where people reported lower levels of being uncomfortable in sharing their health data was with NHS bodies (16%). Given previous high levels of mistrust of the pharmaceutical industry this is a positive step forward.

Going some way to explain this may be that the majority of people (57%) said that they are comfortable or very comfortable sharing their health data for the purpose of developing new treatments and vaccines. This was the second highest rating of the options we tested, behind ‘Improving NHS structures and services’ – 59% of people were comfortable with their health data being shared for this purpose. The support for health data sharing for the purpose of developing new treatments and vaccines suggests that if a clear medical and societal case can be made for its use, the public is more comfortable sharing their health data.

The pharmaceutical and diagnostics industries have always existed to help patients. These industries can now demonstrate that they are leading society out of the pandemic. Focusing on why work is being done, as well as what work is being done is a core part of demonstrating purpose. Social value and purpose should be at the heart of pharmaceutical and diagnostic company communications to increase public confidence that their data are being used for the greater good and to build trust.

The charity sector was second on the list of organisations the public feel uncomfortable sharing their health data with

Almost one third of people (31%) said that they would feel uncomfortable sharing their data with the charity sector, out of all the options tested. This was second only to ‘big technology companies’ (38%). This finding aligns with previous polling commissioned by KPMG in 2018 which found that, in a survey of 2,000 people in Britain, only 11% said that they were willing to share their personal data with charities.[1]

Our survey did not break down the charity group to specifically focus on medical, health and research charities, so one possible reason for people being uncomfortable sharing their health data may be that they are not clear what charities would do with their health data. It is therefore possible that there may be a concern that this data would be used to make fundraising requests as opposed to playing a role in furthering research efforts that will lead to new treatments or supporting patients’ healthcare needs. For the people who feel less comfortable now, this may be a consequence of the economic backdrop of reduced incomes and job losses.

“The insight could be useful when considering ‘beyond the pill’ initiatives. Communicating how patient data is used is key to building trust in digital tools”

We know that COVID has had a huge impact on the charity sector itself. As reported by the Institute for Fundraising in June this year, 47% of charities surveyed (all charities, not specifically health or medical charities) reported an increase in demand for their services since the outbreak of COVID-19, but voluntary income on average is expected to fall by 42% per charity.

To turn the tide and ride a wave of positive sentiment, charities should consider using this period to re-assert their purpose and talk passionately and succinctly about the services they provide, the benefits of the medical research they conduct, and their wider role in the ‘health ecosystem’.

Developing digital tools and apps for patient support was the second least popular purpose for sharing health data

Given the strains on the charity sector there is a strong case for innovation in patient support. However, less than half (46%) of people were comfortable sharing their health data for the purpose of ‘developing digital tools and apps for patient support’, and more than one in five people (22%) said they were uncomfortable with their health data being used for this purpose. This purpose had the second highest amount of people saying they are uncomfortable, with ‘Informing the Government’s lockdown strategy’ the only area where people reported higher levels of being uncomfortable. It would be useful to pose this question to patients rather than the general public to see if the response differs and to determine if there are any condition areas where attitudes diverge significantly, either positively or negatively.

The insight we do have could be useful when considering ‘beyond the pill’ initiatives. Communicating how patient data is used to power patient support apps and how data collected in apps is controlled and used appropriately is key to building trust in digital tools.

Addressing the public’s health data-sharing doubts

There is a critical communications job that needs to be done in winning the hearts and minds of the public regarding the benefit of their health data being used to inform health strategies. The National Data Guardian conducted polling on public attitudes to organisations innovating with NHS data and concluded that “supporting and extending this public conversation [on how benefits from patient data can be shared to the benefit of the NHS] is crucial if we are to gain from the rich information held safely in the health and care system and retain public trust.”

Organisations like the pharmaceutical and diagnostics industries need to be open and transparent about how data is used and build on the public interest in the development of tests, vaccines and treatments for COVID-19. This is a useful route in to a conversation about the value that sharing health data has in fast-tracking patient access to vaccines, diagnostics and treatments.


About the author

Rachel Rowson is head of health innovation at ENGINE MHP.


[1] This survey did not specify health data, but used the broader term ‘personal data’

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The Dawn of a European Health Data Space – Challenges

The European data strategy aims to construct common data spaces for all, create a single EU market for data, and catalyze a dynamic data economy. In a previous post, we briefly described the essence of the envisioned heath data space and pointed at opportunities and possible starting points to transform this vision into reality.

However, several questions have also emerged in exchanges with
thought leaders and collaborators. Borne from gray areas around data, systems
and mechanisms for common use, these questions serve as food for thought
to structure an open, cross-sector discussion.

What data

We need to talk honestly about data quality and data bias. In our
experience with AI, efforts to make data reliable, transparent and reusable go
a long way in catalyzing new, machine-based data exploration. Part of that
effort is to define the amount and type of bias permissible in data for a
particular purpose because there are no data without bias.

Which system

Vast amounts of data on biology, chemistry and health need to be
machine-readable on a massive scale. Manual curation is not an option, but in a
framework that spans from big data in populations to patient-centric care –
where data are personal and private by definition – how do we verify the
fidelity of automated processing and build trust in the system?

Where to guide

Central guidance is essential for unified empowerment, but
individuals should participate in a common data space because they understand
the benefits and not just because there are safeguards against risks. Robust
but flexible guidance can address seemingly insurmountable differences among
sectors in the way data are generated and valued, while ensuring that abuses
are not rewarded. We need to understand the interests and objectives of all
parties. Only so can these spaces be truly inclusionary.

It is time for a dialogue – time to openly define the needs,
interests, objectives and differences of participants in an EU health data
space. We want to hear your thoughts; not only about the nature of these data
spaces but also about the forum in which clinical researchers and data
scientists can access unified research, literature and clinical data in one
secure environment. To join the discussion, please email my colleague Xuanyan
Xu at [email protected].

The Dawn of a European Health Data Space – Opportunities

At the beginning of 2020, the European Commission introduced a “European strategy for data.” The document proposes to bolster and advance the data economy in Europe with a view towards capturing “the benefits of better use of data, including greater productivity and competitive markets, but also improvements in health and well-being, environment, transparent governance and convenient public services.”

Salient was the announcement’s inclusionary language, that “data should be available to all – whether public or private, big or small, start-up or giant.” Also revealing was its concurrent release with a White Paper on artificial intelligence (AI). The EC recognizes that diverse data come from across sectors and are intimately entwined with AI – one cannot exist without the other. Just as abundant, high-quality data are an absolute requisite for meaningful AI, the potential of AI drives today’s value and use of big data.

One pillar of the EU data strategy is the establishment of common
European data spaces in domains of public interest. Among those is health data,
with two broad action items carefully embedded in the context of GDPR:

  • Create legislature to strengthen citizen access to and portability of their own health data, as well as a code of conduct for processing those data in the healthcare sector.
  • Deploy infrastructure that supports interoperability of electronic health records, federated data repositories, genomic information, medical images, laboratory results, prescriptions and other documentation to not only ease healthcare administration, but also foster research and innovation toward discovering, regulating and legislating effective therapies that prevent, diagnose and treat diseases.

Altogether, this as an opportunity. The EC envisions constructing an ecosystem of experimentation, creativity and differentiation to produce new businesses (think: BenevolentAI) and data-based tools that, for example, yield novel antibiotics, predict synergistic combination therapies for cancer, or discover drug candidates to repurpose for rare diseases.

Recently, we’ve developed and nurtured open data aggregations as our contribution to the global response against SARS-CoV-2. The COVID-19 Mendeley Data and Coronavirus Research Hub may offer ideas on how to institutionalize data spaces. We are looking for partners to develop this concept and start a dialogue from which an EU data space can evolve. Please contact my colleague Xuanyan Xu at [email protected] if you are interested in participating.

Readying Your Workforce for Digital Transformation

Seeing it as key to
innovation and competitive advantage, many businesses in the life sciences are
learning to embrace digital transformation these days—in fact, with good
reason, most view it as necessary for survival. But whether or not the process
of adopting rapidly-evolving digital-age technologies will actually result in
business success can really depend on how you do it.

Unfortunately, it is
easy to fall too much in love with the technology itself and put a
disproportionate emphasis on shiny new digital tools, when there is much more
to it than that. In order to truly undergo a digital transformation as a
company, you also need to transform culture, attitudes and available skillsets.

Winning hearts and

A digital transformation needs a holistic approach. First, a top-down approach where the people at the head of the organization fully support the adoption of new digital processes and technologies and, second, a bottom-up approach where employees question the old ways and commit to this transformation. It is vital to transform minds, not just tools. People should really understand the wider goals coming with these changes, so they are excited by the prospect. Because implementing new technology can sometimes be difficult, and change is by nature difficult, it’s better if they are genuinely open and eager to take on those challenges.

There may still be some
resistance against digitization in the organization, but there are ways to
overcome this problem. Be sure to provide thoughtful, thorough trainings and
offer easily accessible technical support, so that people are more comfortable
with the changes and feel confident that not only can they adapt to them, but
also that it does not threaten their jobs. It’s also best not to overwhelm them
by making several huge changes at once—give employees a chance to become
familiar with each new process or technology at a reasonable pace.

People are your best

There is a need for digital pros but also a need to enable your employees to successfully engage with them. Your employees have inside and domain knowledge necessary to develop relevant digital tools. This means that you need to really invest in your people and support them in developing new digital skills as necessary.

So when you’re hiring,
don’t only look for digital pros who have mastered a wide array of digital
skills but also make sure that you are looking for people who are curious,
quick learners, and are able to think and talk about data. You want talented
and motivated individuals who can’t wait to discover and gain proficiency in
newly developing technologies.

The big picture

Willingness to
cooperate, collaborate and accept a “systems thinking” approach where you
consider the bigger picture is important. For instance, subject matter experts
need to be able to articulate their problems from a data perspective to successfully
create tools which actually change the way they work. Digital transformation
will not come out of any single department—every part of the organization must
work together to support the endeavor if it’s going to be successful.

Do you need some guidance or assistance in your pursuit of digital transformation? Elsevier’s Professional Services Group supports customers with data integration, harmonization and analysis. Contact me and we’ll discuss how we can help.

The FAIR Toolkit Helps Researchers with Data Challenges

Since the spread of COVID-19 was first reported, researchers
of all types have mobilized to meet the challenges its causative agent,
SARS-CoV-2, presents to the world. Data scientists in particular have been
quick to apply their expertise to the problems of identifying, tracking and
predicting outbreaks; diagnosing COVID-19; identifying infected individuals and
detecting non-compliance with virus countermeasures; discovering new
therapeutic interventions or repurposing existing ones; and searching for a
safe, effective vaccine.

We’re learning more about SARS-CoV-2 and COVID-19 every day,
and researchers are becoming more sophisticated in their exploration of
everything from the virus’s basic biology to improving patient outcomes. Almost
every question they ask requires information from multiple sources to be found
and integrated, and almost every time a question is answered, it prompts
another question that requires information from yet another source.

The process of assembling data and information to answer
significant research questions usually begins with researchers assessing:

  • What data are available? Do the required data exist at all?
  • How can the data be accessed once we find them? What rights do we
    have to use the data?
  • Are the data and metadata understandable? Can we put them all
    together in a meaningful way?
  • Are all the data valid, or are there outliers or duplicates to

This iterative process of finding information in all of the places it resides, bringing it together, cleaning it up and organizing it can take up much of a data scientist’s time, perhaps as much as 80% of their time according to a 2016 survey. The remaining 20% is spent more productively by actually using the data for analysis or for training predictive models. The diagram below depicts a typical data science workflow on a timeline.

Press, Gil. Forbes, March 2016. Cleaning Big Data: Most Time-Consuming, Least Enjoyable Data Science Task, Survey Says,

This process of putting data together to enable the analysis and modeling that lead to insight is usually slow and tedious because the majority of the data available to researchers today is not FAIR, meaning that the data and metadata typically do not adhere to the FAIR Guiding Principles of Findability, Accessibility, Interoperability, and Reusability. Adherence to the FAIR Principles makes data more easily reusable, so that they efficiently can be applied to any purpose, even unanticipated ones, compressing time-to-insight and increasing the inherent value of the data. Putting the effort into FAIRifying data to make them efficiently reusable allows for quicker results over a broader range of applications.

At Elsevier, we’re committed to helping scientists and clinicians find new answers, reshaping human knowledge and tackling the most urgent human crises—and we believe that data and information are the keys to success. We are proud to support efforts to help researchers make use of the FAIR Principles to be the best data stewards they can be. We are particularly proud to have participated in the development of the Pistoia Alliance’s FAIR Toolkit, freely available to all data stewards, laboratory scientists, business analysts and science managers.

The FAIR Toolkit contains use cases to help life sciences researchers better understand FAIR Data and how to FAIRify their own data. It also provides access to FAIR tools and training, as well as containing information to help organizations manage the change that adherence to the FAIR Principles requires. Like many of the organizations we serve, we at Elsevier, and within the Entellect team, have made a commitment to FAIR Data and encourage researchers to check out the Pistoia Alliance’s FAIR Toolkit to learn more.