You have experienced it. If not yourself, someone you know has been impacted.
Companies are shutting down.
Teams getting laid off.
What has been a shared experience is now well supported by macro data and trends.
Following several years of challenges within (trial failures, expensive clinical studies, bankruptcies, etc.) and external factors (rise of AI, rate hikes, political uncertainty, geopolitical dynamics, etc.), the U.S. biotech sector is enduring what might be its sternest stress test in decades.
In 2025 alone, industry layoffs rose another 3%1.
Pipeline assets have dropped.
Market caps shrank.
Over the past five years, the XBI has fallen 14% (aggregate), while the S&P 500 has risen 89%2. Nearly 200 listed biotechs now trade below their net cash.
Far too many friends and peers have been impacted and are looking for a thriving environment to practice their craft of translating science to therapies for patients in need!
The title of this newsletter borrows from a traditional proclamation made following the accession of a new monarch in various countries. The seemingly contradictory phrase simultaneously announces the death of the previous monarch and asserts continuity by saluting the new monarch3.
Differences between monary and
One unmistakable movement has been where the action has shifted across the world. China’s biopharma sector has gained ground by executing faster and cheaper—not by reinventing the model, but by optimizing it.
Lower labor costs, more efficient workflows, fewer regulatory hurdles4.
Closer at home, companies and organizations are rethinking discovery and its traditional paradigm.
Translation gaps in the current drug discovery framework lead to high failure rates, with only ~10% of candidates reaching approval5.
Key issues include poor preclinical predictability (just 37% of animal studies translate to humans6), inadequate target validation (50% of Phase III failures stem from wrong targets7), and rising costs (~$2.6B per approved drug8).
Limited biomarkers and patient stratification further hinder success, as seen in Alzheimer’s trials, where 75% fail due to mismatched subgroups9,10.
Crisis often accelerates the adoption of some trends.
I see a game changing movement is afoot in the industry. Companies are tapping into plasma, blood, and tissue samples much earlier in the pipeline to generate stronger, more relevant biological signals11.
Success of companies like Tempus and value of data assets like TCGA and UKBiobank have created enough proof points for an accelerated adoption of human data in the discovery process.
We need to rebuild the discovery pipeline itself—with human data at the center, not at the margins.
And that's where human data enters the story.
This isn’t a theoretical future.
One of our partners, a biotech company, bypassed traditional preclinical steps by leveraging human data and samples in an academic medical center, launching a Phase 2 trial based on robust human data.
Their total cost? ~$50M—not $500M.
That’s not just a leaner process—it’s a fundamentally different one.
Academic Medical Centers (AMCs) sit on a gold mine.
At any given time, an “average” AMC handles12, 13, 14:
Each data point—whether a lab result, imaging scan, or gene panel—is a real-world snapshot of human biology, embedded in clinical workflows.
Not generated by design, but accumulated organically, reflecting the full complexity of disease.
Yet today, the majority of this data is fragmented, siloed, and underutilized.
Data lives in EMRs that weren't built for discovery.
Biobanks are disconnected from clinical notes.
Molecular profiling is often disconnected from longitudinal patient outcomes.
And because of these barriers, AMCs today primarily struggle to leverage the gold mine of human data and samples.
As federal funding tightens and philanthropy becomes less predictable, AMCs are under increasing pressure to find new, sustainable revenue streams.
At the same time, life sciences companies are hungry for real-world data: datasets that can drive target discovery, inform trial design, or validate biomarker strategies.
This creates a once-in-a-generation opportunity:
to turn AMC datasets into engines of discovery, not just records of care.
The institutions that seize this moment—those that invest in federated data models, AI-augmented cohort builders, and live metadata registries—will become the hubs where the next wave of biomedical innovation happens.
Not just repositories.
Not just care providers.
But full-stack research engines built to fuel translation at scale.
We often talk about "signals" in this industry—biomarkers, patient subtypes, preclinical readouts.
But lately, I’ve found myself looking for a different kind of signal: the ones that don’t come from a wet lab or a model, but from behavior.
The quiet shifts in where people choose to work.
The rising demand for data assets instead of just IP.
The questions early-career scientists are asking about how and where to build.
The fact that AMCs are beginning to think like data stewards, not just care providers.
These are weak signals—but they matter.
They suggest that we’re not just in a moment of market correction. We’re in a moment of redefinition.
The future of discovery won’t be built on demos or decks.
It will be built in institutions that know how to handle messy human data with rigor and care.
It will be led by teams that don't treat AI as a shortcut—but as a scaffold for reasoning.
And it will reward the organizations that can build systems—technical and cultural—that make data reliable, reusable, and real.
Because here's the truth:
We don’t lack for ambition.
We don’t lack for technology.
What we lack is usable infrastructure—and a shared understanding of what ready really means.
If you're an AMC leader, a translational scientist, or a biotech founder:
This is the time to invest in your data the way you’d invest in a pipeline asset.
Because it is one. And increasingly, it’s the one that will determine what survives and what stalls.
The old playbook is fading.
Discovery, as we knew it, is gone.
But a new one is being written—in code, in cohort builders, in consent forms, in partnerships, in patient metadata.
It won’t look the same.
It won’t be built by the same tools.
But it might just be better!
Long live discovery- with human data as its cornerstone.
Abhishek Jha | Co-Founder & CEOElucidataScoop from Elucidata
Upcoming Webinar on 22nd May 2025In this session, we’ll discuss how top organizations are unifying data and code with real-time, scalable, and accurate clinical data pipelines that transform raw, siloed data into governed, AI-ready data products. Register here!
Latest Case Study6X Faster Clinico-Genomic Data Integration & Analysis with PollyRead More
Thank you for taking the time to explore our updates!We’d love to hear your thoughts or help you discover how Elucidata can support your goals—feel free to share feedback or talk to our data expert. P.S.: For more insights, updates, and upcoming events—follow us on LinkedIn and join the conversation!Warmly, AJ(Abhishek Jha)CEO- Elucid
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