How Does AI Change Drug Development? Evidence from Clinical Trial Phases and Drug Types

Kwon, Angela Eunyoung, Jaecheok Park, Gene Moo Lee. “How Does AI Change Drug Development? Evidence from Clinical Trial Phases and Drug Types,” Working Paper.

  • Presentations: KrAIS (2025), INFORMS (2025)

We examine how the AI capability of pharmaceutical firms affects drug development processes, with a particular focus on clinical trials. Clinical trials test the safety and efficacy of drug candidates on human subjects across four phases. While early phases (Phases I & II) assess preliminary safety and efficacy in smaller populations, later phases (Phases III & IV) investigate thorough effectiveness in larger populations. To examine the effect of the AI capability of firms on clinical trial outcomes (total trials, new trials, and retrials), we utilize job postings data and ClinicalTrials.gov. Our preliminary findings suggest that AI capability has significant effects on clinical trial outcomes in the early phases of clinical trials, but not in the later phases. Moreover, we find the heterogeneous effects across drug types, where the effect of AI capability on retrials is greater for biologics. This study contributes to the healthcare IS literature by empirically demonstrating the business value of AI in enhancing drug development processes. Our study also provides practical guidance on AI investment and implementation for pharmaceutical firms, regulatory agencies, and policymakers.