Where to next for Pharma and Healthcare?

2021 was a year of tumultuous and rapid digital change for the healthcare industry and the world at large. New digital technologies have led to revolutionary transformations among providers and rapidly evolving expectations among customers and patients, while the Covid-19 pandemic reshaped the way businesses operate and individuals seek and receive care.

Artificial intelligence (AI) played a significant role in enabling the industry to not only adapt but also continue innovating and better responding to the needs of healthcare professionals (HCPs), patients, and stakeholders. 2022 is set to be another year of accelerated digital transformation and promising innovations amidst shifting expectations, ongoing operational disruptions, and the as yet unabated pandemic.

What did we predict last year?

Last year our predictions centered around seeing more of the following. You can read the full article here.
1. Omni-channel next best action modelling (also called context marketing or ‘moment’ marketing ) based on predictive AI .
2. Voice Recognition (a type of AI)
3. Generative Adversarial Networks (a type of AI)
4. GPT-3 (a type of AI)
5. Wearables and the Internet of Things
6. Digital Twins
7. Non-Traditional Players’ Disruption of Healthcare
8. New Business Models Coming
9. 3D Drug Printing becomes more common
10. Blockchain will begin to Transform Industries
11. Nanobots
12. Driverless Cars and Autonomous Vehicles (Electric of course) will be the Norm
12. Value Disruption throughout Healthcare
13. Customer Experience Competition
14. Competing More Strategically with Data
15. Innovation becomes more mainstream

Eleven of these came true and the other 4 have yet to be realized. I still maintain that these will continue to gain more traction in 2022.

But beyond these, where is pharma, and healthcare in general heading in 2022?

6 Healthcare AI Predictions for 2022

1. Augmented intelligence will play a greater role in decision-making at all levels in pharma.

Augmented intelligence (AuI) refers to the use of AI to make data-driven decisions more easily and effectively. Whereas AI is capable of efficiently assimilating, organizing, and analyzing vast quantities of data, humans are far more judicious high-level decision-makers. Augmented intelligence bridges the gap between artificial and human intelligence.

Already in 2021, the Covid-19 pandemic helped bring AuI to the forefront of epidemiology, but the benefits extend well beyond this context. “Aggregation of social media, news media, rapidly evolving health reports, and other disparate data is a daunting task which AI is poised to overcome” (Long & Ehrenfeld, 2020). AuI helps ensure the most relevant information is delivered to decision-makers on time, in a format that’s easy to access and understand, and in such a way as to free humans from time-consuming, error-prone tasks.

In 2022, AuI tools are likely to become more sophisticated, but perhaps more importantly, more widely adopted. It’s likely the biggest impacts will come from C-level use of AuI early on, but more general operational benefits should be expected from businesses whose transformation strategy includes AuI.

2. AI will become better at understanding written, spoken, and visual information and find powerful uses in healthcare.

Natural language processing (NLP) has improved in leaps and bounds in recent years (just ask Siri), but NLP algorithms still struggle with clinical notes, which are dense, use complex terminology and sentence structure, and vary in quality (especially, albeit stereotypically, when handwritten). According to data consultancy firm Starschema, so-called clinical language models are poised to have a big impact in 2022 by offering the same benefits other industries have enjoyed from NLP to the healthcare industry:

“In the healthcare industry, clinical language models can be used to structure clinical notes and extract information, with applications in EMR/EHRs, HIMS, pharmacovigilance, clinical trials recruitment and medical billing. As is the case in other industries, these applications can automate – with appropriate human oversight – tedious manual tasks to optimize costs and enable personnel to focus on higher-value activities.”

Such technology can be combined with more traditional uses for NLP, like chatbots, to provide a smart, natural-language interface for patients and practitioners. A chatbot might, for example, inform a patient that their doctor has found reduced levels of hemoglobin and then arrange for a follow-up, all without the practitioner’s intervention.

We can also expect to see advancements in “computer vision”, i.e., intelligent image processing. As with clinical notes, medical imaging tends to be more complex compared to other industries. It’s often three- or even four-dimensional, and acceptable margins of error are much slimmer. Nonetheless, advancements here have enormous potential in diagnostics and beyond, and computer vision start-ups are already having an impact on the healthcare industry. We can expect to see more of the same in 2022.

3. Wearable devices and the Internet of Things (IoT) will become even more important and beneficial for researchers, providers, practitioners, and patients and pharma will be able to utilize these for stronger insights and stronger customer engagement.

Wearables like smart watches have already impacted healthcare in a big way, providing a platform and sensors for applications that modify behavior (encouraging, for example, more exercise, healthier food choices, and smoking cessation), monitor chronic conditions, alert rescue crews of falls and trauma, and more.

Deloitte predicts that 320 million healthcare consumer devices will ship in 2022. With the widespread adoption of wearables from providers like Apple, Samsung, Garmin, FitBit, and more, paired with better sensors and more sophisticated on-device AI, wearables will perform better, provide more useful recommendations to users, and more granular and precise data to practitioners and researchers. In addition, we can expect to see innovations in smart pills and smart patches, with a greater number of start-ups and healthcare incumbents entering the market.

As it has year-on-year, the production, sophistication, and adoption of connected devices (IoT) will increase in 2022. IoT is already being leveraged by the healthcare industry to provide more services outside the hospital, a trend that’s sure to continue and grow in 2022. We can expect to see more connected at-home medical devices, like inhalers, glucose monitors, insulin pumps, as well as heart-rate monitors and pacemakers.

4. AI-powered self-serve tools and digital innovations will help practitioners deal with burnout.

An existing trend that was greatly exacerbated by the pressures placed on practitioners during the (ongoing) Covid-19 pandemic, more and more nurses, doctors, researchers, and healthcare employees are suffering from burnout than ever before.

Burnout refers to a state of physical, psychological, and emotional exhaustion caused by excessive or prolonged workplace stress. Fortunately, AI is well positioned to provide precious aid and improve conditions for healthcare workers up and down the chain of command. There are a few ways this will manifest in 2022:

● Virtual and augmented reality will allow for more comfortable and effective telemedicine. The sudden shift to virtual consultations due to Covid-19 was a source of stress for many, but healthcare providers are now “shifting from leveraging virtual care as a substitution to in-person care to identifying new virtual care business models and transforming the entire clinical care journey” (Gartner) in a way that makes sense for practitioner and patient.
● Hospital-at-Home interventions are likely to increase. Forbes predicts that the number of hospitals delivering home care will triple in 2022, thanks to more portable devices with better connectivity that allow for x-rays, EKGs, IV antibiotics, infusions, and more, all from home. Patients show better outcomes, while practitioners are finding the new, out-of-hospital environments stimulating and uniquely rewarding. It also significantly reduces the number of individuals in hospital beds and allows for constant monitoring without a physician being physically present.
● Intelligent self-service tools, powered by AI, will make it easier for patients to access basic levels of care without doctor intervention, freeing HCPs from the more mundane tasks of everyday medicine to focus on more interesting and intellectually stimulating cases. Advances in machine learning and machine vision will do the same by providing intelligent diagnostic tools that are more than sufficient for straightforward cases (which take up the lion’s share of most practitioners’ time).

5. Precision medicine will become more accessible, widespread, and beneficial.

Easily one of the most exciting advancements made possible thanks to AI and other novel technologies, precision medicine will become more accessible and normalized, leading to widespread adoption. Precision medicine looks at the genetic, environmental, and social factors of an individual to allow for more precise diagnoses and far more personalized interventions. The genome generation will be better informed about their genetic profile, the diseases they have or might develop, and the effectiveness of health interventions and that they will be “more engaged in improving their own health.

While much of the groundwork has been laid, 2022 is likely to see more basic research being translated into practical, marketable results. As the number and types of sources continue to increase, artificial intelligence will be needed to “combine input from multiple structured and unstructured sources, reason at a semantic level, and use these abilities in computer vision, reading comprehension, conversational systems, and multimodal applications to help health professionals make informed decisions (e.g., a physician making a diagnosis, a nurse creating a care plan, or a social services agency arranging services for an elderly citizen).”

6. AI will unlock the secrets of existing, untapped, unstructured data.

Finally, it’s no secret that there exists an enormous quantity of patient and industry data that remains unstructured and untapped. Information firm Wolters Kluwer believes that up to 80% of healthcare data remains unstructured, and that the focus moving forward should be placed on unlocking the benefits within. Artificial intelligence, and in particular, machine learning and natural language processing will be key in doing so (see above regarding, for example, clinical notes).

Indeed, the common thread in the above predictions is the value of data collected from patients, practitioners, and researchers. As AI tools for organizing, analyzing, and drawing insights from that data become more sophisticated, affordable, and widespread, we are just now starting to realize its enormous potential.

6 AI Trends in the Pharmaceutical Space

1. Digital therapeutics (DTx) will continue to grow in sophistication and adoption, and may be frequently paired with traditional interventions.

DTx often rely on AI to provide a personalized therapeutic experience. As AI—and especially on-device AI—becomes more powerful, so too will the benefit of using such devices. We may also see DTx being paired with traditional molecules for a more holistic approach to drug interventions.

2. AI will be used to even greater effect in drug development and clinical trials.

We can expect to see advances in virtual laboratories, biosimulation, organization, and analysis of data, as well as larger investments from incumbents and an acceleration of startups entering the market.

3. Pharmaceutical companies will collaborate closely with Big Tech.

It’s no secret that Big Tech is eager to enter the healthcare space. Moving forward, pharmaceutical companies that act as an entry point and guide for such newcomers in pharma’s competitive, tightly regulated, newly disrupted space have much to gain. Whether that is a sensible idea for pharma is up for questioning. I personally feel that is not great for pharma but excellent for big tech…but time will tell.

4. Pharma supply chains add NFTs (non-fungible tokens).

The main function of NFTs use in the pharma supply chain is in authenticating products, ensuring their quality and verifying their origin. NFTs on blockchain are suitable for logistics applications because of their immutability and transparency, which keeps supply chain data authentic and reliable. Something we as an industry had some difficulty with in 2020 with the supply chain disruption due to covid. Since NFTs can help trace the movement of goods along the supply chain it can also eliminate counter fitting, something we have also seen I the pharma industry. NFTs can also provide information regarding each material and component in a particular product.

5. AI will be used to even greater effect in commercial for more personalized customer engagement.

Much work from Eularis is about using AI in pharma commercial to help make smarter, actionable insights that power stronger results.
The work we have done encompasses so much (read detailed examples in these blogs below)
Examples of Successful Applications of Artificial Intelligence in Pharma Marketing Part 1
Examples of Successful Applications of Artificial Intelligence in Pharma Marketing Part 2
Examples of Successful Applications of Artificial Intelligence in Pharma Marketing Part 3

From AI-powered patient journeys, finding rare disease patients, market access insights, faster reimbursement, value pricing, precision physician targeting, modifying patient adherence, personalized marketing, and customer engagement, plus a load more, we are seeing private and public data being combined and analyzed with AI to improve pretty much every aspect of commercial and we are seeing a lot of traction (as predicted last year) in implementation of AI-powered omnichannel marketing messaging and channels and personalized sales and marketing.

6. AI in Pharmacovigilence

With the covid vaccinations roll out, the pharma industry discovered how unprepared it was to handle the volume of AE reporting that comes with this kind of scale. Fortunately some AI companies have created very powerful tools that combine NLP (conversational AI) and machine learning to both capture and report AEs. This is highly accurate and for pharma pv departments under strain, this is the perfect solution so we anticipate more take up of this kind of service.