Bridging the green skills gap: a framework to align the pharmaceutical workforce with sustainable drug discovery

Background The pharmaceutical industry’s R&D model faces unsustainable costs and environmental impact, yet educational pipelines lag in integrating AI and green chemistry skills essential for modern drug discovery.Methods We conducted cheminformatics analysis of 50,000 bioactive compounds from ChEMBL v35 to quantify AI-driven discovery advantages. Natural language processing with BioBERT embeddings systematically analyzed international accreditation standards (ACPE, EAFP).Results AI-driven approaches achieved 99.998% reduction in experimental burden and 32% lower endocrine disruption potential versus traditional high-throughput screening. Accreditation analysis revealed a critical deficit: mean Sustainability Integration Score of only 18.3% (range: 9.5–27.1%; SD = 6.2). The observed reductions in endocrine disruption potential and predicted E-factors for AI-designed compounds should be interpreted as signals of favorable computational toxicology profiles within the dimensions assessed, rather than comprehensively validated environmental safety.Conclusions We introduce the Accreditation-Aligned Sustainable Education (AASE) framework and GreenMedSim computational sandbox - an experiential platform virtualizing wet-lab activities for iterative molecular design. GreenMedSim is presented as a theoretically grounded and computationally specified educational prototype; empirical user trials and learning outcome data are planned for Phase 1 implementation (2026–2027).This work provides an actionable strategy aligning pharmaceutical workforce training with sustainable drug development, directly supporting UN Sustainable Development Goals 4.7, 9, and 12.