Systematic risk identification and assessment using a new risk map in pharmaceutical R&D

•Based on our in-depth experience on biopharmaceutical R&D, we have identified R&D-related risks by systematically analyzing scientific, peer-reviewed publications in terms of dedicated uncertainties described for drug discovery, preclinical development, clinical phases 1-3, post marketing activities, innovation management and intellectual property (IP) management using PubMed.•Thereby, we have identified 123 key R&D risks and grouped them into five R&D value chain segments and 27 respective process domains.•Next, we have applied the R&D risk map and identified 84 scientific publications describing 64 cases in which AI is addressing key R&D risks, thus, describing the case of AI in pharmaceutical R&D. Delivering transformative therapies to patients while maintaining growth in the pharmaceutical industry requires an efficient use of research and development (R&D) resources and technologies to develop high-impact new molecular entities (NMEs). However, increasing global R&D competition in the pharmaceutical industry, growing impact of generics and biosimilars, more stringent regulatory requirements, as well as cost-constrained reimbursement frameworks challenge current business models of leading pharmaceutical companies. Big data-based analytics and artificial intelligence (AI) approaches have disrupted various industries and are having an increasing impact in the biopharmaceutical industry, with the promise to improve and accelerate biopharmaceutical R&D processes. Here, we systematically analyze, identify, assess, and categorize key risks across the drug discovery and development value chain using a new risk map approach, providing a comprehensive risk–reward analysis for pharmaceutical R&D.