Connected Discovery Ltd., London, UK.
Drug Discov Today. 2011 Nov;16(21-22):940-7. doi: 10.1016/j.drudis.2011.09.013. Epub 2011 Sep 23.
The life science industries (including pharmaceuticals, agrochemicals and consumer goods) are exploring new business models for research and development that focus on external partnerships. In parallel, there is a desire to make better use of data obtained from sources such as human clinical samples to inform and support early research programmes. Success in both areas depends upon the successful integration of heterogeneous data from multiple providers and scientific domains, something that is already a major challenge within the industry. This issue is exacerbated by the absence of agreed standards that unambiguously identify the entities, processes and observations within experimental results. In this article we highlight the risks to future productivity that are associated with incomplete biological and chemical vocabularies and suggest a new model to address this long-standing issue.
生命科学产业(包括制药、农化和消费品)正在探索新的研发商业模式,重点是外部合作。与此同时,人们希望更好地利用从人类临床样本等来源获得的数据来为早期研究计划提供信息和支持。这两个领域的成功都取决于成功整合来自多个提供者和科学领域的异构数据,这在行业内已经是一个重大挑战。由于缺乏明确标识实验结果中实体、流程和观察结果的公认标准,这一问题更加严重。本文重点介绍了不完整的生物和化学词汇可能给未来生产力带来的风险,并提出了一种新的模型来解决这一长期存在的问题。