Pistoia Alliance, USA.
Bayer, Germany.
Drug Discov Today. 2019 Apr;24(4):933-938. doi: 10.1016/j.drudis.2019.01.008. Epub 2019 Jan 25.
Biopharmaceutical industry R&D, and indeed other life sciences R&D such as biomedical, environmental, agricultural and food production, is becoming increasingly data-driven and can significantly improve its efficiency and effectiveness by implementing the FAIR (findable, accessible, interoperable, reusable) guiding principles for scientific data management and stewardship. By so doing, the plethora of new and powerful analytical tools such as artificial intelligence and machine learning will be able, automatically and at scale, to access the data from which they learn, and on which they thrive. FAIR is a fundamental enabler for digital transformation.
生物医药研发行业，乃至生物医药、环境、农业和食品生产等其他生命科学研发行业，正日益变得依赖数据。通过实施科学数据管理和治理的 FAIR（可查找、可访问、可互操作、可重用）指导原则，它们能够显著提高效率和效果。这样一来，人工智能和机器学习等大量新型强大分析工具就能够自动、大规模地访问它们从中学习和赖以运行的数据。FAIR 是数字化转型的基本推动因素。
