The evolution of data ethics in clinical research and drug development

Abstract

Summary We are in an era of tremendous progress for leveraging large clinical datasets, real-world data, genomics, imaging, and advanced analytics to improve drug development, reduce development timelines, and address unmet medical needs. Data is being used in new ways to develop medicines and improve healthcare. A prevalent perspective is that all available medical data, assuming patient's rights to privacy and data protections are in place, should be used to advance science in the interest of patient care; in this perspective, data should be maximally used for the public good. At the same time, high profile cases have challenged public trust concerning industry's use of data. There is an inherent ethical tension between an obligation to use data for improving healthcare and public mistrust of the use of that data. Reasons for mistrust are broad and include concerns that invoke fairness, reciprocity, and benefit sharing, leading to questions such as: will industry use my data to develop medicines that I can’t access or afford? Will industry have my private information and could this affect my access to healthcare? Will new analysis methods exacerbate societal inequities and biases? In light of recent advances and such questions, there are increasing requests from academia, media, and the private sector for data ethics guidelines that can complement protecting patient data privacy and security. Demystifying the use of emerging technologies and data sources, exploring ethical tensions, and considering the perspectives of patients, academics, industry researchers, and governments are starting points for building trust and evolving data ethics.