Unicure's experience reveals a significant regulatory risk: the FDA can reverse its position on a pre-agreed Statistical Analysis Plan (SAP). Despite prior alignment on using a natural history control, the agency later told the company this approach was merely 'exploratory,' invalidating their filing strategy and shocking investors.

While former FDA official Vinay Prasad was known for his stringent reviews, the continued institutional skepticism towards Capricor's drug after his departure suggests the concerns were widespread among FDA staff. This indicates that attributing the FDA's recent restrictive stance solely to one individual's leadership style is an oversimplification of the agency's internal consensus on data quality.

The FDA receives raw and cleaned datasets from sponsors, not just summary reports. Their internal teams conduct independent analyses, which can lead to findings or data presentations in the official drug label that differ from or expand upon what's in the published paper.

The FDA panel's stringent data requirements for Capricor's Duchenne drug for older boys highlights a perceived regulatory inconsistency. This tough stance contrasts with previous accelerated approvals for Sarepta's Duchenne therapies, which were granted despite unproven efficacy. This raises questions about whether the agency applies different standards to similar patient populations over time.

Gossamer's Phase 3 drug for PAH failed after being designed around a promising subgroup identified in a post-hoc analysis of a less-than-stellar Phase 2 trial. This outcome serves as a cautionary tale for clinical development, highlighting the high risk of basing expensive pivotal studies on retrospective data mining rather than robust, pre-specified endpoints.

After reacquiring a "failed" ALS drug, Neuvivo's team re-analyzed the 200,000 pages of trial data. They discovered a programming error in the original analysis. Correcting this single mistake was a key step in reversing the trial's outcome from failure to success.

In the CREST trial, the FDA's critique heavily emphasized an overall survival hazard ratio above one. Though statistically insignificant and based on immature data, this single figure created a powerful suggestion of potential harm that overshadowed the positive primary endpoint and likely contributed to the panel's divided vote.

The FDA's current leadership appears to be raising the bar for approvals based on single-arm studies. Especially in slowly progressing diseases with variable endpoints, the agency now requires an effect so dramatic it's akin to a parachute's benefit—unmistakable and not subject to interpretation against historical data.

The CREST trial's positive primary endpoint, assessed by investigators in an open-label setting, was rendered negative upon review by a blinded independent committee. This highlights the critical risk of confirmation bias and the immense weight regulators place on blinded data to determine a drug's true efficacy, especially when endpoints are subjective.