生物制药
生物仿制药
制药工业
风险分析(工程)
鉴定(生物学)
报销
业务
转化式学习
分析
药物开发
数据科学
计算机科学
知识管理
医学
药品
生物技术
药理学
医疗保健
经济
内科学
心理学
生物
植物
经济增长
教育学
作者
Alexander Schuhmacher,Clara Brieke,Oliver Gassmann,Markus Hinder,Dominik Hartl
标识
DOI:10.1016/j.drudis.2021.06.015
摘要
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.
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