Data Integrity: History, Issues, and Remediation of Issues

Abstract

Data integrity is critical to regulatory compliance, and the fundamental reason for 21 CFR Part 11 published by the U.S. Food and Drug Administration (FDA). FDA published the first guideline in 1963, and since then FDA and European Union (EU) have published numerous guidelines on various topics related to data integrity for the pharmaceutical industry. Regulators wanted to make certain that industry capture accurate data during the drug development lifecycle and through commercialization—consider the number of warning letters issued lately by inspectors across the globe on data integrity. This article discusses the history of regulations put forward by various regulatory bodies, the term ALCOA Plus adopted by regulators, the impact of not following regulations, and some prevention methods by using some simple checklists, self-audit, and self-inspection techniques. FDA uses the acronym ALCOA to define its expectations of electronic data. ALCOA stands for Attributable, Legible, Contemporaneous, Original, and Accurate. ALCOA was further expanded to ALCOA Plus, and the Plus means Enduring, Available and Accessible, Complete, Consistent, Credible, and Corroborated. If we do not follow the regulations as written, then there is a huge risk. This article covers some of the risk aspects. To prevent data integrity, various solutions can be implemented such as a simple checklist for various systems, self-audit, and self-inspections. To do that we have to develop strategy, people, implement better business processes, and gain a better understanding of data lifecycle as well as technology.

LAY ABSTRACT: If one does a Google search on “What is data integrity?” the first page will give the definition of data integrity, how to learn more about data integrity, the history of data integrity, risk management of data integrity, and at the top about various U.S. Food and Drug Administration (FDA) and European Union (EU) regulations. Data integrity is nothing but about accuracy of data. When someone searches Google for some words, we expect accurate results that we can rely on. The same principle applies during the drug development lifecycle. Pharmaceutical industry ensures that data entered for various steps of drug development is accurate so that we can have confidence that the drugs produced by the industry are within some parameters. The regulations put forward by FDA and EU are not new. The first regulation was published in 1963, and after that regulators published multiple guidelines. Inspectors from both regulatory bodies inspected the industry, and they found that the data was not accurate. If pharmaceutical industry produces drugs within the stated parameters, then it is approved and available in the market for patients. If inspectors find that the data is modified, then the drug is not approved. That means revenue loss for industry and drugs not available for patients. In this article, I explain some of the remediation plans for the industry that can be applied during the drug development lifecycle pathway.