Data Integrity-A Study of Current Regulatory Thinking and Action.

In reaction to breaches of data integrity in the pharmaceutical industry, regulatory authorities have introduced inspection approaches or initiatives with the aim of reducing occurrences of data integrity problems. This review article-based on study of 65 cases of regulatory action from 2002 to 2014-provides an overview of current regulatory thinking and action on breaches of data integrity affecting GxP (health-related regulations) processes supporting non-clinical studies, clinical studies, laboratory controls, and production controls. These case studies largely represent position of the U.S. Food and Drug Administration and the regulatory agencies affiliated with the European Medicines Agency. Also discussed is the role of human factors as a potential source of data integrity problems. The article concludes by recommending some remedial controls that could be established to avoid or reduce occurrences of data integrity problems.Lay Abstract: In fulfilling their mission to protect public health, regulatory agencies (e.g., U.S. Food and Drug Administration, European Medicines Agency) must establish confidence that medical products they approve are fit for their intended use. In so doing they rely on scientific and operational data generated during research, development, manufacturing, sales, marketing, distribution, and post-marketing surveillance activities. The level of confidence they build is directly proportional to the scientific validity and integrity of data presented to them by the sponsors of medical products. In this article we present analysis of 65 case studies that document regulatory action taken by various regulatory agencies on breach of data integrity between 2002 and 2014. The ensuing discussion on current trends largely represents position of the U.S. Food and Drug Administration and European Medicines Agency. The article concludes by proposing some remedial controls that could be established by pharmaceutical companies to avoid or reduce occurrences of data integrity problems.