Presentation (CTI)

OBJECTIVES: The requirements of the EU HTA Joint Clinical Assessment (JCA) necessitate that manufacturers plan for early, systematic identification and prioritization of PICO scenarios prior to submission. The 100-day timeline following receipt of the final scope is challenging, as submissions often demand multiple distinct PICO scenarios with robust evidence and indirect comparisons. We describe a systematic, evidence-based framework for identifying and prioritizing PICOs before the JCA process starts, by partly automating some tasks using artificial intelligence (AI) tools.
METHODS: A six-step methodology was implemented: (1) therapeutic context definition including indication analysis; (2) systematic evidence identification in bibliographic databases, ClinicalTrials.gov, guideline and HTA repositories; (3) data extraction focusing on appropriate populations, interventions, comparators, and outcomes; (4) PICO matrix development using frequency analysis and probability calculations; (5) scenario validation through expert consultation and JCA alignment; (6) implementation strategy including evidence generation planning. The AI tools integrated evidence curation and AI-assisted automation of generating PICOs using various freely available frameworks. Steps 1 to 4 of this approach were validated by demonstrating the systematic identification and prioritization of PICO scenarios for a hypothetical new drug for Type 2 diabetes mellitus (T2DM).
RESULTS: Applied to a new hypothetical drug in T2DM, our systematic approach identified 10 distinct sub-populations, 3 intervention dose levels, 5 comparator options, and one set of 6 clinically relevant outcomes, generating 150 (10 x 3 x 5 x 1) theoretically possible PICOs. Term frequencies were calculated and cross-referenced with national HTA bodies and diabetes-specific clinical guidelines. Probability determination through frequency multiplication and normalization identified 20 most probable and relevant PICOs.
CONCLUSIONS: Our integrated approach enables proactive and early alignment with EU HTA requirements by optimizing evidence generation and submission readiness. AI tools can serve as efficiency enablers managing the PICO workflow, ensuring adherence to JCA requirements, maintaining compliance standards essential for successful JCA submissions.