Neonatal neuroprotection research faces persistent challenges: animal models are imperfect, pediatric drug development is commercially unattractive, and promising preclinical candidates frequently fail in clinical translation. Barks et al. address one important aspect of these limitations, not by correcting the ubiquitous rat hypoxic-ischemic encephalopathy model’s inherent biological flaws, but by extracting greater decision-relevant information through an adaptive Bayesian randomization design. By comparing four repurposed agents simultaneously within a single framework incorporating within-litter controls, composite outcomes, and inflammation-sensitized cohorts, the study prioritizes candidates more efficiently than conventional single-agent designs. Key limitations include rodent-to-human translational gaps as well as underappreciated variability between generic drug preparations that may confound cross-laboratory comparisons. Broader progress requires bridging a deep “valley of death” through coordinated ecosystems uniting academic science, industry operational expertise, regulatory innovation, and novel financing mechanisms. The study’s adaptive comparative framework may ultimately prove as significant a contribution as any individual drug finding.