In The Age Of AI, Data Is Still King

By Denise N Bronner, Ph.D., founder, Empactful Ventures

In today’s healthcare landscape, AI dominates the headlines, promising faster drug discovery, optimized trials, and personalized medicine at scale. But while AI continues to capture attention, the true power player behind the scenes is data. Proprietary data sets aren’t just valuable; they are the foundation of everything AI promises to deliver. And in the current economic climate, they’ve become a lifeline.

Economic Uncertainty Is Forcing A New Kind Of Strategy

With capital tightening and uncertainty rising, many healthtech startups and biopharma companies are confronting the same existential question: How do we survive long enough to scale? For some, it means delaying expansion plans or trimming teams. For others, it means exploring strategic alternatives, and in many of those conversations, the most attractive and monetizable asset on the table is their data set.

M&A Activity Is Already Shaped By Data Acquisition

The demand for differentiated data is already reshaping the healthcare landscape. Regeneron’s acquisition of 23andMe’s genetic data business wasn’t about consumer DNA kits, it was a strategic play to supercharge their drug development pipeline with a massive, diverse genomic data set. Even Datavant’s $7 billion merger with Ciox Health created a new ecosystem to link fragmented medical records and enable more powerful real-world evidence generation.

These aren’t outliers. They're indicators of where the market is heading.

The Expanding Definition Of “Valuable” Data

Data’s value is not just in its volume but in its specificity and context. Genomic and biomarker data power the development of targeted therapies and diagnostics. Electronic health records (EHRs) and claims data inform market access strategies, payer engagement, and clinical trial site selection. Real-world outcomes, e.g., adherence, complications, and even patient-reported quality of life, are increasingly critical to proving value in a shifting regulatory environment.

Even more interesting is the expanding definition of what counts as valuable data. Consider how consumer health data from wearables and remote monitoring tools, like what Oura Ring and Whoop have captured, is now of interest to medtech and diagnostics companies looking to validate digital biomarkers. Or the behavioral data embedded in clinical trial recruitment platforms (who clicked, who pre-screened, who enrolled, and why), which is being mined to optimize recruitment funnels and personalize outreach.

Social and behavioral data are gaining traction as pharma and biotech companies increasingly utilize social media platforms to engage with patients and healthcare professionals. These platforms offer real-time insights into public sentiment, treatment adherence, and emerging health trends, which are crucial for shaping effective communication and marketing strategies.

For instance, Ogilvy Health has established a dedicated health influencer unit to assist pharmaceutical companies in navigating platforms like TikTok and Instagram. This initiative aims to combat misinformation and connect with audiences seeking authentic health information online. Platforms like Aissel help life sciences companies identify and engage digital opinion leaders (DOLs) by analyzing real-time social media activity across healthcare communities. This enables more targeted outreach and strategic collaborations.

These examples illustrate how integrating social and behavioral data into healthcare strategies can lead to more informed decision-making, improved patient engagement, and ultimately, better health outcomes.

Consolidation Is Inevitable

Traditional acquirers — pharma sponsors, CROs, and insurers — are still in play. But new players are entering the space with different motivations. Amazon’s acquisition of One Medical gave it not only clinical data from primary care visits but also behavioral and logistical data that powers its retail-health strategy. Walmart Health is following a similar path, blending EHR data from its clinics with pharmacy and retail behavior to build a new model for community-based care. These players don’t just want patients, they want patient patterns.

Private equity firms are also getting smarter about data as an asset class. Many are rolling up specialty clinics or digital health tools and looking to bundle data sets that offer payer insights, compliance patterns, or patient lifetime value. And increasingly, players from the ad-tech and creator economy are eyeing health, not for clinical claims but for audience engagement metrics that could power influencer-driven health campaigns or new health commerce models.

For Founders, It’s Time To Rethink The Value Of Your Data

For founders with limited runway, this presents a critical window of opportunity. Even if a full acquisition isn’t on the table, a well-structured data partnership or licensing deal can extend operational life while raising your visibility in the market. But it starts with understanding your strategic positioning.

If your data fills a gap (e.g., access to a rare disease population, a historically underrepresented demographic, longitudinal outcomes across a specific therapeutic area, or high-fidelity data on social determinants), you have something the big players don’t. Larger firms often struggle to collect niche or hard-to-reach data sets on their own due to regulatory, reputational, or operational barriers. If you’ve already done that legwork and can demonstrate your data’s integrity, consent provenance, and potential use cases, you’re no longer just a struggling startup. You’re a missing piece of someone else’s road map.

What founders often overlook is that the value of a data set is not just in what it is but in what it enables. Are you able to de-risk an upcoming launch, validate a predictive model, or unlock access to a new patient segment? Don’t wait for someone to tell you your data is valuable. Know who needs it, show how it shortens their timeline or reduces their cost, and make the first move.

The Bottom Line

While AI may be the flash, data is the fuel. And in this market, those who control the right data sets won’t just survive — they’ll define the future of healthcare innovation.

References:

1. https://www.fiercebiotech.com/medtech/regenerons-256m-bid-wins-23andme-bankruptcy-auction
2. https://www.datavant.com/press-release/datavant-and-ciox-health-announce-merger-creating-the-largest-neutral-and-secure-health-data-ecosystem
3. https://www.ogilvy.com/ideas/ogilvy-launches-global-health-influence-offering
4. https://www.healthcaredive.com/news/amazon-closes-39b-buy-of-one-medical/643245/
5. https://corporate.walmart.com/news/2021/09/27/walmart-selects-epic-to-help-customers-simplify-their-health-care

About The Author:

Denise N Bronner, Ph.D., has roughly 15 years of organizational thought leadership experience within the global healthcare space and has held various roles in academia, consulting, pharma, and venture capital. During her career, she has specialized in health equity, data-driven global therapy program strategy development, pitch and storytelling refinement, and identifying business opportunities within pharma. Beyond her professional endeavors, she's passionate about enhancing diversity in STEM fields, serving on advisory boards, participating as a judge in pitch/business competitions, and mentoring young professionals. She holds a bachelor’s degree in biological sciences from Wayne State University, a Ph.D. in microbiology & immunology from the University of Michigan - Ann Arbor, and certification from the Venture Capital Executive Program from UC Berkeley Haas School of Business. She is the founder of Empactful Ventures, which currently consults healthcare-focused startups and venture funds, and she is a member of the Clinical Leader editorial board.