?AI Impact on Drug Discovery Pipelines ?AI-assisted target identification and validation: Case studies: AI Startups and Drug Discovery Pipelines

?Clinical trial phases (I–IV), GCP (ICH-E6) and informed consent essentials, as context for AI applications ?Real-world data (RWD) and real-world evidence (RWE) analytics Regulatory perspective: CDSCO New Drugs & Clinical Trials Rules 2019 and ICH-GCP 2025

?Pharmacovigilance fundamentals recap: ADR/ADE classification, ?ICSR life cycle, and MedDRA coding, VIGIBASE Software overview ?Causality assessment approaches (WHO-UMC scale, Naranjo algorithm) and where AI-assisted triage fits in Regulatory reporting perspective: CDSCO PvPI, EudraVigilance, and US-MEDWATCH, WHO Global Survellience, CIOMS

?Emerging AI-linked career roles: Medical Information associate, Medical coder and Medical Scribing, Drug Safety associate, clinical data analyst, HEOR ?Entrepreneurship opportunities in AI-driven pharma, nutraceutical, and cosmeceutical start-ups ?Access to capital: hackathons, national/international scholarships, incubation support ?Activity: Preparation of a ‘Dream Company/Role’ profile aligned to AI-pharma careers Activity: AI-assisted CV/resume creation highlighting AI-drug-development skills

?Overview of regulatory perspectives on AI in drug development (CDSCO, USFDA, EMA – conceptual level) ?Ethical considerations: data privacy Law DPDC ACT 2023, accountability in clinical and pharmacovigilance data use Global certification and MOOC pathways in AI for healthcare/pharma (building on existing certification-landscape orientation)