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Systematic risk identification and assessment using a new risk map in pharmaceutical R&D
Institution:1. Reutlingen University, Alteburgstrasse 150, D-72762 Reutlingen, Germany;2. Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Jahnstrasse 29, D-69120 Heidelberg, Germany;3. University of St. Gallen, Institute of Technology Management, Dufourstrasse 40a, CH-9000 St. Gallen, Switzerland;4. Novartis Institute for BioMedical Research, Postfach, Forum 1, CH-4002 Basel, Switzerland;5. Pediatric Immunology, Department of Pediatrics I, Hoppe-Seyler-Strasse 1, D-72076 Tübingen, Germany
Abstract: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.
Keywords:Pharmaceutical  Research and development (R&D)  Artificial intelligence  Drug discovery  Drug development  Risk
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