BioNTech may be deeply ensconced in the latter stages of its bid to bring a COVID-19 vaccine to market, but it’s still pushing forward on other fronts, including a partnership with InstaDeep to deploy artificial intelligence and machine learning across its business.
The two companies have been working together in this area since 2019, but BioNTech has opted to double down on the alliance with a revised agreement focusing on new immunotherapies for cancer and infectious diseases.
The headline news in the new agreement is the formation of a joint AI Innovation Lab – split between InstaDeep’s headquarters in London in the UK and BioNTech’s site in Mainz Germany – that will focus on drug discovery and design, protein engineering, manufacturing and supply chain.
One of the main research areas for the new lab will be the development of new vaccines and biologic drugs for the treatment of cancer and prevention and treatment of infectious diseases, including COVID-19.
InstaDeep – which was founded in Tunisia – has built its business across a range of sectors, mainly helping small- and mid-sized companies to develop bespoke apps harnessing computer vision, predictive analytics, 3D imaging, augmented and virtual reality, and deep learning. It was recently nominated by CB Insights as one of the 100 most promising AI start-ups in the world
With BioNTech, the company will focus on three main areas. The duo will apply InstaDeep’s protein design platform – called DeepChain – to engineer new mRNA sequences against protein targets, and also collaborate on sifting through anonymised patient data to identify new drug targets and biomarkers.
They will also use AI and machine learning to find ways to make manufacturing and supply chain processes more efficient, tapping into technologies like robotics and autonomous decision-making algorithms.
“Pairing BioNTech’s deep knowledge of the human immune system and scientific data-driven development approach with our AI platform could transform the way we discover and develop new drug classes for patients all over the world,” said Karim Beguir, InstaDeep’s chief executive.
A recent study by Kearney revealed that 68% of global industry leaders in the healthcare sector see AI and advanced analytics as major value drivers.
All attention at the moment is on BioNTech’s Pfizer-partnered coronavirus vaccine BNT162b, but it has a packed pipeline of earlier-stage projects, including a Roche-partnered mRNA-based drug for melanoma in phase 2 and several other cancer therapies in phase 1.
“We see a significant opportunity at the intersection of AI and immunology by computational design of new precision immunotherapies,” said BioNTech chief executive Ugur Sahin. “This collaboration will expand our digital capabilities and optimise our operations across the value chain.”
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“It’s important to provide our patients with the absolute best access channels to quickly and seamlessly connect with the care they need. Experian Health’s solution guides our patients to the right care and digitally connects them with a confirmed appointment.” – Kaci Husted, Vice President, Benefis Health System
It’s shouldn’t come as a surprise that patients today want their healthcare experience to mirror the flexibility and convenience that they are now accustomed to with other industries. Notably, patients want easier and faster access to care, and preferably without having to pick up the phone to call and make an appointment.
Benefis Health System knew it needed to provide patients with a new and improved access experience. Patients were required to call the office during business hours to book an appointment, and while some may have been immediately connected with a scheduler, others would have to leave a voicemail or be placed on hold. The process was not only taking valuable time out of patients’ days but carried the risk of delaying care.
With online self-scheduling in place, patients can schedule an appointment online with any of Benefis Health System’s 300+ providers, regardless of time of day. The solution leverages powerful decision support, which guides patients directly into the appointment type and provider necessary for the treatment they need. It’s good for patients and providers, as the solution’s accuracy prevents any misplacement of patients to the wrong provider or appointment type.
Patients started using the self-scheduling solution almost immediately after it was available. Benefis Health System has since experienced the following results:
- Improved access to care. Patients of Benefis Health System have used the system to book many appointments outside of office hours, with 50% of its patient base booking after hours.
- Better access to urgent care. One of Benefis Health System’s urgent care centers has seen a large uptick in online self-scheduling. In fact, 52% of patients are scheduling appointments online for that location.
- Ongoing improvements with analytics. Benefis Health System is leveraging analytics to track how many patients use online self-scheduling and can identify when and where they might fall out. They can see the pitfalls and where improvements may be necessary and make those changes in real time to drive better conversion rates. Currently, 23.6% of patients who start the process are converting to a booked appointment.
Interested to see how online self-scheduling can help your organization improve access to care?
The post Success at a glance: online self-scheduling after hours appeared first on Healthcare Blog.
Good data practices lead to better research outcomes. To learn more about why clean, reusable data is critical to R&D, take a look at this helpful new infographic that demonstrates how Entellect is centered around the importance of reusable data, irrespective of scientific domain.
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.
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.
The post Next wave: how pharma analytics can be improved with new technologies appeared first on .
Under the ter
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COVID-19 has changed the way millions of Americans access care during COVID-19, leading to the widespread adoption of virtual health and other consumer-centric technologies. Without online self-scheduling however, technologies like telehealth may not reach their full potential. Incorporating a self-scheduling solution that reaps long-term success takes a specific strategy, and with the number self-scheduling vendors growing every day, it can be hard to know what to look for in a self-scheduling solution.
How can you be sure that you are choosing the
best solution for your organization? Here is a snapshot of what to look for:
- Automated Business Rules.Online self-scheduling that automates scheduling protocols with customized business rules drives efficiency while ensuring bookings are accurate. Providers can maintain control of their calendars while filling existing gaps, designating which days and times are available for which specific type of patient or appointment. This is particularly vital during a pandemic like COVID-19 where to avoid further exposure and spread of the virus providers may only want to see patients experiencing those symptoms at certain times of day. The benefits are three-fold: schedulers, including call center agents and patients, see only appropriate appointment availability for a provider in real-time allowing them to book on the spot, providers can experience a more predictable schedule as they know their rules are being maintained, and patients can be assured that their health and safety is a top priority for in-office visits.
- Integration. Direct integration with any EMR/PM system is a key component for any successful scheduling solution as it provides everyone (patients, providers, health plans, and call center agents) with a continually up-to-date, real-time view of appointment availability. These integrations improve workflows and behind the scene while enabling the patient-centered aspect of the technology, which is the ability to book an appointment from a computer, phone, or tablet. Additionally, being able to provide a non-integrated scheduling experience for affiliated providers and other services is a vital additional offering that needs to be available outside the integration so that systems can open scheduling to all services. Having a solution that can do both is ideal.
- White-Labeled Experience.Customers remember and go back to brands they love, and that couldn’t be truer in healthcare. That is why it is important for organizations to deliver a consistent brand experience across the board—even with a self-scheduling solution hosted by an outside vendor. Leveraging a white-labeled scheduling solution promotes a strong brand experience and builds trust while saving patients the hassle and confusion of leaving the organization’s website to schedule via another. Moreover, many scheduling vendors require logins to their system in order to schedule, this is an unnecessary barrier to access – it’s best to find a solution that needs no additional logins.
- Real-Time Scheduling (Not Just Request an Appointment).Unfortunately, what you see with self-scheduling isn’t always what you get. So many times, patients go through the entire online scheduling process only to find out that they’ve only requested an appointment, and still have to wait for the provider to confirm and book – often with a phone call which is what they were trying to avoid. Real-time scheduling means patients have the ability to view and actually choose their preferred appointment day and time and book right there on the spot. This also means that patients can book an appointment at all times of the day (or night), not just during the provider’s business hours. This is particularly helpful during times of social distancing and stay at home orders when schedules are completely thrown out of whack and patients may not even have the opportunity to schedule an appointment until odd hours of the night or morning when a provider office is closed.
- Calendar Reminders.The act of booking an appointment isn’t always enough to make a patient show up for scheduled care. Automated calendar reminders sent to patients immediately after the booking process, however, increase the chances that patients will show for their scheduled appointments and dramatically reduce patient no-shows. Specifically, ones that include .ics calendar files that can be added to smartphone calendars have been proven to be effective.
- Automated Outreach. Many health systems send automated phone and text campaigns to patients about their healthcare needs, but all of them still require a patient to call in to schedule an actual appointment. Healthcare organizations looking to effectively close more gaps in care while also simplifying the outreach process should look to a solution that provides patients the ability to book appointments in real time via IVR and text.
- Analytics. Do you know where your patients came from before they arrived at your website? What did they do after arriving? Are they dropping off and when? And maybe the most important question, what is your conversion rate? The answers to each of these questions can refine and improve the scheduling process, and a sophisticated self-scheduling solution will come with real-time analytics dashboards and data science capabilities to help determine opportunities for improvement.
The rise of consumerism in the healthcare
industry is no doubt influencing the creation and adoption of self-scheduling
solutions, among other digital technologies that improve patient access. As
these technologies are more seriously considered, providers need to be aware of
what to look for in a self-scheduling solution. Smart technology that
incorporates the components above will stand out from the crowd, ready to fit
the unique needs of any provider organization.
Download our free guide to learn more about and how it fits within an omni-channel access strategy.