Industry Predictions For 2023

PREDICTION #1: In 2023, the chasm will widen between those companies investing in analytics-based, digital-first commercial models and those still sitting on the fence and taking a measured approach

Alan Kalton

Life sciences companies are notoriously cautious. However, COVID-19 put many companies in the uncomfortable position of forcing new ways of working, engaging with customers, and new technologies. For many companies, the changes are sticking, ushering in the digital-first era.

We have started seeing the impact of the adoption of new technologies, such as platform intelligence solutions, ‘on the ground.’ In fact, 89% of companies surveyed by DHC Group reported that they are successfully executing an AI-driven omnichannel strategy across sales and marketing and scaling up.1

Gone are the days when digital and analytics technologies were merely a shiny new toy to test-run in isolated markets. Today, many companies understand the impact of AI and recognize that it needs to be powering engagement across all markets. As the global director of field force AI enablement at Novartis noted recently during our Omnichannel AI Masterclass, “in three to five years, I hope that our industry has moved to where AI isn't a buzzword, but rather, it’s baked into the mainstream of our go-to-market strategies because it's so essential.”

The organizations delaying investment in scaling intelligence platforms across the organization will see a widening gap between them and their competitors in terms of influence, customer engagement and ultimately, financial success.

PREDICTION #2: Companies will connect data science models to day-to-day operational activities to execute on strategic business goals across the entire organization

David Ehrlich

Next year, we will see the start of the next chapter in AI for life sciences commercial organizations.

Traditionally, AI has lived in one of two places–either with headquarters teams, analyzing massive amounts of data to generate ‘smart’ conclusions, or within discrete applications, helping to tune the application’s impact (i.e. marketing automation systems). At headquarters, AI is used to strategically assess business opportunities on a broad scope whereas the tactical AI embedded into individual applications is very specific and application limited.

Both are valuable, but what’s missing is the connective tissue between HQ’s broad-scope AI to the various operational systems required to execute HQ’s strategic business goals. Such connective capability would reach into the multiple operational systems required for execution and guide the appropriate actions. As a result, operating teams could agilely deploy data science models to guide a wide range of day-to-day activities.

Ultimately, companies will be both more effective (more good decisions) and more efficient (less bad decisions that waste resources), cycling through the “try it, fix it” rhythm much faster to continuously improve AI’s outputs across the entire organization.

PREDICTION #3: AI-driven identification of digital opinion leaders (DOLs) will accelerate evidence dissemination

Deepak Patil

Medical Affairs teams are racing to provide a personalized “Netflix-like” engagement for ever-expanding targets, predicting needs and preferences and then delivering unbiased scientific information in the most useful formats and channels. Field medical affairs or medical science liaisons (MSLs), work to engage with physician key opinion leaders (KOLs), but also have a new target: digital opinion leaders.

DOLs, in essence, are KOLs active on digital platforms. DOLs may be practicing or non-practicing HCPs but have major influence over consumer behavior and informing other physicians. Some rise to near-celebrity status, such as Dr. Mikhail Varshavski–better known as Dr. Mike–who has a combined social media following of over 21 million people. He has been featured in Time, Men’s Health, Business Insider, and People Magazine, to name a few. Also, Dr. Don Dizon is a professor at Brown University and director of medical oncology at Rhode Island Hospital who shares cancer research via video primarily on TikTok. He has 38,000 followers.

In addition to doctors, nearly 90% of all adults in the U.S. search for health information on Facebook, Twitter, YouTube, and other social media sites. From doctors to patients, MSLs can multiply their influence by engaging with the right DOLs. AI and natural language processing technologies can help by mining available information–based on specialty, therapeutic area expertise, followers, outreach network, and posts–to help identify the right influencers to engage and cultivate a relationship.

Next year, as the role of the MSL continues to expand and evolve, MSLs will demand new smart technologies to help them engage with the growing fleet of digital influencers. And when these relationships are formed, MSLs will increase education and information dissemination faster and farther than they have ever done before.

PREDICTION #4: Decentralized clinical trial market will continue to grow, even in economic downturn

Joel Morse

Industry leaders are debating whether or not decentralized clinical trials (DCTs) will become the norm rather than the exception across therapeutic areas–but, it’s neither. In 2023, the question will no longer be an “either/or” scenario. There will always be some trials and some elements of a trial that should not be decentralized. In 2023, however, the first question all sponsors will consider at the start of protocol design will be “what aspects of the trial can be decentralized.”

For some trials, the answer may be “all of them,” and for other trials, such as highly complex oncology trials, the answer may be “very few of them” as each trial has unique needs. However, with the rapid maturation of digital technologies and increasing comfort level with digital tools by patients and doctors, sponsors will adopt a digital-first mindset for every trial.

Digital technologies will be considered from the start rather than force-fitting them into a trial mid-way, which will ensure a more successful trial design overall. The financial and time savings of the DCT model, coupled with the remarkable patient benefits of greater access, increased convenience, and optionality, are too compelling for sponsors not to lead with it for each trial they invest in.

PREDICTION #5: Digital therapeutics companies will focus on the difficult last mile to commercialization

Dave Hanaman

Historically, digital therapeutics (DTx) companies have directed about 95% of their effort into gaining FDA approval and 5% into market access strategy. In 2023, this will shift to a 60%/40% split, with DTX companies having an earlier focus on the commercialization process, while simultaneously working toward earning FDA approval.

This ‘last mile’ is completely unchartered territory for DTx companies.They face new obstacles bringing their therapeutics to market. For example, physicians’ lack of awareness of the DTx and their inability to easily prescribe them. There are still many unknowns around getting DTx products on the formulary and how to prescribe them to patients–doctors can’t just write a prescription and send patients off to the local drugstore when prescribing the use of an app.

And, whereas traditional drug companies may spend up to $300 million to launch a product, most DTx startups don’t have the budget to spend on commercialization strategies such as building a field team, equipping marketing teams with supporting analytics technology, and initiating patient support programs to help patients learn to use these software-based therapeutics.

PREDICTION #6: Clinical trial sponsors will drive a new framework for DCT technology and services (rather than the other way around)

Even with nearly nine in 10 sponsors saying they will use some elements of DCT technologies in their trials, we still have a lot to learn. We’ll continue to see a lot of experimentation in trying to understand the most effective new methods, technologies, and processes for designing and executing DCTs and improving various aspects of clinical research. But, with business models in flux and an uncertain economy, we’ll see more disruption in the DCT software space, as technology providers pivot to meet industry needs.

For instance, technology providers will work to resolve the complexities of DCT software integration, and drill down to solve specific trial problems rather than offer ‘end all be all’ solutions to sponsors that prefer a hybrid approach. Until recently, the progress of DCTs has been largely driven by providers – often, working in a bubble without collaborating closely with trial sponsors.

In 2023, sponsors will take the lead. Rather than technology providers dictating what their product/services can do to improve clinical research, sponsors will seek technology providers that solve their specific challenges. As they become more researched and familiar with DCT technologies, sponsors will define what trial improvements are required, and successful technology manufacturers will pivot accordingly.

PREDICTION #7: Next year, decentralized and hybrid clinical trials will become simply “clinical trials”

Sanskriti Thakur

The decentralized clinical trial (DCT) model works and works well. It’s no longer a leap of faith, as a 2022 study from the Tufts Center for the Study of Drug Development shows that DCTs can achieve net financial benefits ranging from five to 13 times for Phase II and Phase III trials, equating to roughly $10 million and $39 million ROI, respectively. COVID-19 made DCTs a necessity. Positive returns will make DCTs the de-facto standard.

Expect 2023 to be a pivotal year, capping a year or more of strong growth² in decentralized and hybrid clinical trial deployment. The next evolution of DCTs will involve self-service tools that enable sponsors and sites to deploy and operate global studies on a common platform using standardized processes. We see evidence of this pivot from customers and partners who aim to leverage digital tools across their pipeline. The industry is no longer dipping their toes in the DCT water; rather, leading pharmaceutical companies like GSK and AstraZeneca, are expanding its use.^{2, 3}

We are living the evolution of clinical trials – similar to how consumers migrated to online banking without even realizing that a major shift was taking place in their everyday lives. Sponsors, sites, and patients will expect digital tools to drive clinical trial performance, superior experience, greater diversity, and better outcomes.

Sources:

1. The DHC Group, “The State of Omnichannel HCP Engagement in Pharma,” (November 2022).
2. 2022 forecast: decentralised trials to reach new heights with 28% jump, https://www.clinicaltrialsarena.com/analysis/2022-forecast-decentralised-trials-to-reach-new-heights-with-28-jump/
3. https://www.astrazeneca.com/r-d/digital-health-revolutionising-healthcare-for-patients.html
4. https://www.businesswire.com/news/home/20220907005594/en/Medable-Selected-by-GSK-to-Power-Decentralized-and-Hybrid-Clinical-Trials-Across-Global-Product-Portfolio