Comment from GATC Health Corp

GATC strongly supports FDA’s AI-Enabled Optimization of Early-Phase Clinical Trials Pilot Program as an important opportunity to define how AI can be responsibly applied to improve the evidentiary foundation of early clinical development. The most meaningful contribution of AI in this context is not the substitution of computational outputs for scientific expertise, clinical judgment, or regulatory oversight, but the generation of timelier, integrated, and biologically informed evidence to support those judgments. Properly governed AI-enabled approaches can help reduce uncertainty in first-in-human and early dose-finding studies, improve identification of biologically responsive patient populations, strengthen biomarker-driven development strategies, and support more reliable Phase 1-to-Phase 2 advancement decisions. GATC believes the pilot will have the greatest public health and regulatory value if it focuses on use cases where AI can materially improve decision quality, rather than merely accelerating existing processes. Measures of success should therefore include not only operational efficiency, but also improvements in predictive performance, biological interpretability, patient selection, safety signal detection, dose optimization, endpoint selection, and concordance between early-phase predictions and subsequent clinical outcomes. By emphasizing prospective validation, transparent performance evaluation, robust governance, human oversight, and alignment with trustworthy AI principles, FDA can help establish a durable framework for AI adoption that is scientifically credible, regulatory-ready, and clinically meaningful. Through continued engagement among FDA, sponsors, technology developers, investigators, and patients, this pilot can advance a practical model for integrating AI into early-phase clinical development in a manner that improves development decisions without diminishing accountability. GATC appreciates FDA’s leadership in this area and supports a pilot structure that advances responsible AI use, strengthens confidence in early clinical evidence, and ultimately helps identify the right therapies for the right patients, on the right development pathways earlier in the lifecycle.