Clinical trial protocols become overly complex because teams copy and paste from previous studies, accumulating unnecessary data points and criteria. Merck advocates for "protocol lean design," which starts from the core research question and rigorously challenges every data collection point to reduce site and patient burden.

Startups often rush to publicize their first patient enrollment. A better approach is to treat the entire first-in-human study as a rigorous experiment focused on learning and optimization, delaying major marketing until after the trial is successfully completed.

Many medtech companies design large trials where a tiny, clinically meaningless response can be statistically significant. Dr. Holman advises entrepreneurs to instead run rigorous trials that prove genuine clinical value, arguing that credible data is the ultimate moat, even if it carries a higher risk of failure.

Reflecting on a past failure, Isaac Stoner asserts that the costliest risk in drug development is ambiguity. A poorly designed study yielding a “thumb sideways” is worse than a well-designed one that produces a clear failure, as ambiguity prevents actionable decisions and wastes invaluable time and capital.

Testing for hundreds of biomarkers is not inherently better and can be harmful. With a ~95% accuracy rate per test, running more tests increases the odds of a false positive. This leads to chasing down non-existent issues with doctors, initiating diagnostic processes that carry their own risks.

A common failure in biotech is viewing patients solely as data sources rather than as human partners in the development process. This perspective leads to unnecessarily complex protocols with high patient burden. The most successful firms build relationships with patient advocacy groups and design trials that respect the patient's experience.

A major source of unproductivity in drug development isn't the time spent reaching a clinical milestone. Instead, it's the 'white space' after data is received—the delay in analyzing results and making a firm go/no-go decision, which stalls the entire program.

Before starting a trial, define specific safety and efficacy alarms or 'stop rules.' This disciplined approach allows a company to terminate a failing study early, preserving capital and resources, rather than waiting until the end to discover the results are not viable.

Scientists often design trials to answer every possible academic question, which adds complexity and patient burden. Drug development trials should be ruthlessly focused on two things only: safety and efficacy. All other extraneous research can wait for post-approval studies.