Abstract：
Pre-competitive data sharing can offer the pharmaceutical industry significant benefits in terms of reducing the time and costs involved in getting a new drug to market through more informed testing strategies and knowledge gained by pooling data. If sufficient data is shared and can be co-analyzed, then it can also offer the potential for reduced animal usage and improvements in the in silico prediction of toxicological effects. Data sharing benefits can be further enhanced by applying the FAIR Guiding Principles, reducing time spent curating, transforming and aggregating datasets and allowing more time for data mining and analysis. We hope to facilitate data sharing by other organizations and initiatives by describing lessons learned as part of the Enhancing TRANslational SAFEty Assessment through Integrative Knowledge Management (eTRANSAFE) project, an Innovative Medicines Initiative (IMI) partnership which aims to integrate publicly available data sources with proprietary preclinical and clinical data donated by pharmaceutical organizations. Methods to foster trust and overcome non-technical barriers to data sharing such as legal and IPR (intellectual property rights) are described, including the security requirements that pharmaceutical organizations generally expect to be met. We share the consensus achieved among pharmaceutical partners on decision criteria to be included in internal clearance procedures used to decide if data can be shared. We also report on the consensus achieved on specific data fields to be excluded from sharing for sensitive preclinical safety and pharmacology data that could otherwise not be shared.
摘要：
竞争前数据共享可以为制药行业提供显著的好处，通过更明智的测试策略和通过汇集数据获得的知识，减少新药上市所需的时间和成本。如果共享了足够的数据并可以进行共同分析，那么它还可以提供减少动物使用和改善毒理学影响的计算机预测的潜力。通过应用公平指导原则，可以进一步增强数据共享的好处。减少策展花费的时间，转换和聚合数据集，并允许更多时间进行数据挖掘和分析。我们希望通过描述作为通过综合知识管理（eTRANSAFE）项目增强横向安全性评估的一部分的经验教训，来促进其他组织和计划的数据共享。创新药物倡议（IMI）合作伙伴关系，旨在将公开可用的数据源与制药组织捐赠的专有临床前和临床数据进行整合。描述了促进信任和克服数据共享的非技术障碍的方法，例如法律和IPR（知识产权），包括制药组织通常期望得到满足的安全要求。我们同意制药合作伙伴之间就决定标准达成的共识，这些标准将被纳入内部审批程序，以决定是否可以共享数据。我们还报告了在特定数据字段上达成的共识，这些数据将被排除在敏感的临床前安全性和药理学数据的共享之外，否则将无法共享。
