SKIM INSIGHTS — Issue 03

As the FDA shift into real-time clinical trials representing an immense regulatory upgrade, the ongoing story is the decoupling of drug discovery from the legacy labor-heavy infrastructure.

For decades, the pharmaceutical industry operated on a "brick and mortar" model of biology: build a physical lab, run a physical trial, hire an army of human monitors to transcribe data, and wait years.

We are literally now attesting the transition to "Cloud-Native Biology."

If so-called real-time trials are the "high-speed internet" of drug development, we are now seeing the emergence of the data centers.

Traditional Contract Research Organizations (CROs) were built to manage human logistics. The next generation of partners such as Formation Bio and Insilico Medicine are built as software-defined entities. They treat trial data as a continuous data stream.

And when data hits the FDA, it doesn't just benefit the regulator; it creates a closed-loop system for the AI models that are powering the drug. If an AI predicts a molecule will fail, but real-time trial data shows it succeeding, the model is retrained instantly. This basically reduces the learning rate of drug development from years to weeks.

Wall Street has historically valued big pharma based on their pipeline (the number of drugs in late-stage trials). We are moving toward a world where investors value "Compute Capacity.” This is when a company can run the most high-fidelity, high-speed simulations and trials concurrently without being hindered by a human-centric delay or obstacle.

The industry is experiencing a structural repricing of Time-to-Value.

In the old model, the capital intensive nature of long trials acted as a moat that kept smaller, more agile innovators out. You needed a billion dollars and five years of runway to survive the trial process.

This changes everything. If you can validate a safety signal in six weeks rather than six quarters, the amount of venture capital required to reach a "go/no-go" decision drops by orders of magnitude.

We are likely to see a great unbundling of Big Pharma. The big integrated firms will increasingly act as the distribution and manufacturing layer, while the discovery and validation layer is rapidly taken and captured by tech-native biotechs that uses real-time data pipelines.

The biggest risk is not just to the legacy CROs. It’s actually to the traditional R&D budgets of the giants that cannot adapt their corporate nervous systems to move as fast as the data streams they are now mandated to produce.

Are we approaching a point where software-defined biology makes the traditional clinical trial infrastructure obsolete or will human clinical oversight always remain the ultimate challenge?

Generate:Biomedicines notched the largest biotech IPO since 2024 at $425M — with a lot riding on whether its AI-designed drug GB-0895 succeeds in late-stage trials as a proof of concept for the entire AI drug discovery model.

Hengrui Pharma licensed 13 early-stage oncology programs to Bristol Myers Squibb for up to $15.2 billion — one of the largest licensing deals in biotech history.

2026 is on pace to be one of the most active M&A years in biotech history with Merck, Eli Lilly, and Biogen alone committing over $12 billion across acquisitions in a single week.

Trump bought up to $680K in Eli Lilly stock. President Trump earlier this year bought as much as $680,000 in stock of Eli Lilly, the maker of blockbuster obesity drugs. Make of that what you will.

Isomorphic Labs raises $2.1B. DeepMind's drug discovery spinoff Isomorphic bags $2.1B and it’s the second largest biotech round ever.

Zealand Pharma opens US HQ in Cambridge. Denmark's Zealand Pharma is setting up a new research hub in Cambridge, Massachusetts as its US headquarters to increase AI drug discovery and next gen molecule creation.

Phase III Trial: The final and largest stage of clinical testing before a drug goes to the FDA for approval. Usually involves thousands of patients across multiple sites. This is where most drugs fail. When you see a biotech stock spike or crash, it's because Phase III data just came out.

This is Issue 03! If this was useful, forward it to one person in biotech, pharma, or finance who would find it interesting.

See you next week.