Avoiding Pitfalls When Every Patient Becomes a Readout

The 2025 biotech downturn intensified a shift already underway. Investors who once waited for study-level readouts now want patient-level data as it emerges, thinking it can help them reassess risk before committing the next tranche of capital. This demand can sharpen development decisions or distort them.

Speed can kill: Understand the risks

Phase I is not a miniature confirmatory trial. With a small N, an exceptional first responder may be an outlier, while a weak early signal may reflect patient selection, dose, or assay performance rather than the molecule. Two responders and two nonresponders do not establish a trend, and no drug should be judged on four patients. Without biological context, patient-level updates can lead investors to abandon a viable asset or place too much confidence in noise.

Near-real-time evidence comes at a price. Drug-specific specialty assays are often run on one or two samples rather than in batches, raising per-sample costs and tying turnaround to coordinated collection and analysis.

Combine capital discipline and scientific strategy

Sponsors can address these pressures by building a lean but robust evidence package around the decisions the trial must support. In early development, that usually means solid pharmacokinetic data, a target-engagement measure such as receptor occupancy, and a focused pharmacodynamic assay demonstrating a downstream biological effect. These data show that a drug reaches and affects its intended pathway without overclaiming clinical efficacy.

Being lean does not mean sacrificing flexibility. Where feasible, sponsors should bank additional, fit-for-purpose biospecimens. The incremental cost is modest relative to repeating a Phase I study, and retained samples allow the team to investigate an outlier, test an alternate marker, or rescue an ambiguous dataset. Collection, processing, stability, and consent must be planned prospectively so the specimens are informative.

Science and operations must be planned in tandem. Biomarker-enriched enrollment requires validated screening assays and lab capacity wherever patients are, and a global specialty laboratory can avoid sites or regions with competitive studies and shorten timelines. In adaptive designs, where pharmacodynamic readouts are staged, an early clinical signal in one arm can be confirmed quickly and used to redirect the study to enroll patients most likely to show efficacy.

Sponsors should also define how data will be reviewed and communicated, ideally before enrollment begins. Each update should identify the number of evaluable patients, dose and exposure, assay performance, and relevant clinical context, keeping observed data separate from interpretation and comparing findings with prespecified thresholds whenever possible. This gives investors real visibility without overinterpreting data from a few patients.

Investors reward programs that know which question to answer and design for it. The goal is not the fastest datapoint. It is the earliest reliable evidence that carries a program to its next value inflection, preserving the options needed when the first answer is incomplete. In this context, the capital discipline imposed by the market becomes the development discipline behind better drugs.

Deborah Phippard, PhD, chief scientific officer, Precision for Medicine