Notes05 · 2026-01-14 · 5 min

Bio & health systems

The bottleneck is not discovery. It is evidence.

The thesis

Computational tools have made candidate generation cheap and clinical validation relatively more expensive. Value therefore concentrates in whoever compresses trial cost and cycle time: site networks, recruitment, real-world evidence, and regulatory strategy as a product.

In health delivery, the buyer is a system with a budget cycle and a compliance function. Anything that does not reduce documented cost or documented risk does not get bought, regardless of accuracy.

The bear case

Better candidates against poorly understood biology still fail in the clinic, and the failure rate is the whole business model. Tooling companies get paid either way, which is exactly why their multiples deserve scrutiny.

What we'd watch

  • Phase transition rates for computationally-originated candidates
  • Trial enrolment time in the therapeutic areas being targeted
  • Reimbursement decisions on software-mediated care
  • Whether health systems renew after the first budget cycle

Case files

Situations the desk has followed end to end. Names are withheld; the numbers and the sequence are not.

A discovery platform with cheap candidates

2022 – 2026
Setup
Computational design cut candidate generation cost by roughly an order of magnitude and shortened the design-make-test loop from months to weeks. The pipeline filled fast and the platform narrative was clean: more shots on goal, cheaper.
What happened
Clinical validation cost and cycle time did not move at all. Trial recruitment, site contracting and regulatory review are governed by human and institutional throughput, not compute, so the bottleneck simply relocated — and the company's advantage stopped compounding at precisely the point where the expensive part of drug development begins. Cheaper candidates produced more parallel programmes and therefore more capital required, not less.
Where it stands
Value in this stream has concentrated in trial-cost compression — site networks, recruitment, decentralised monitoring, real-world evidence that can support a label — rather than in candidate volume. The platforms that partnered early for the evidence step are the ones still setting terms.
Candidate cost reduction
~10x
Trial cost and duration change
~0
Where value moved
evidence generation

Cheap candidates do not shorten trials. Underwrite the evidence step, because that is the business and that is where the cost is.

A diagnostic model that beat the radiologist

2024 – 2026
Setup
Peer-reviewed accuracy above the human baseline on a retrospective dataset, sold into hospital systems with an annual budget cycle, a compliance function, a clinical governance committee and an existing PACS vendor with contractual leverage over integration.
What happened
Accuracy did not clear procurement. Two years of enthusiastic pilots produced no system-wide contract, because no committee had a line item for accuracy and every one of them had a line item for staffing and throughput. The deal signed only after the vendor produced audited numbers showing a specific department reading more studies per shift with the same headcount.
Where it stands
Sales now open with the budget line the product reduces and bring the accuracy data as supporting evidence rather than as the pitch. The cycle has shortened by roughly half and the pilots convert, because the pilot is now designed to generate the throughput evidence procurement needs.
Pilots before first system contract
2 years
What unlocked it
throughput evidence
Sales cycle since
~50% shorter

The buyer is a budget cycle, not a clinician. Accuracy is table stakes; documented cost, throughput or risk reduction is the sale.

Next on this stream

In progress

Trial cost decomposition — Where the money actually goes in a phase-two programme, and which line items software has any claim on.

Next · Q3 2026

Procurement evidence bar — What health systems require before signing: documented cost or risk reduction, and who is producing it credibly.

Full roadmap →

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