Surge of Data Integrity Violations Irritating the FDA


Some of the observations noted in actual warning letters include:

  • Sampling or retesting to achieve a specific result or to overcome an unacceptable result.
  • Failing to retain original raw data.
  • Not recording data at the time a procedure is completed.
  • Backdating record entries.
  • Disabling audit trails.

Common Misconceptions

Regulatory organizations provide various resources with guidelines and instructions for complying with data integrity requirements. However, there still seems to be some misconceptions about the concept, including:

  • Auditors won’t check recycle bins.
  • Out-of-specification (OOS) reporting is merely paperwork and does not impact patient safety if not completed.
  • Violations are limited to only fraud and misrepresentation.
  • Sharing login credentials is necessary for ensuring someone is always able to move processes forward.
  • The whole industry works this way.

The FDA’s Views on the Subject

Consumers don’t have the option of reviewing active pharmaceutical ingredient (API) data, Certificates of Analysis (CoA), clinical study information or any other information involved in a product’s development. They count on the FDA to cover those bases and ensure drug products meet the requirements for quality, safety and efficacy.

  • We closely analyze reams of data to ensure the quality and safety of manufacturing throughout a product’s life cycle. When investigating possible drug safety concerns, a multidisciplinary team reviews the data.
  • The FDA takes strong compliance and enforcement actions when issues are observed.
  • Warning letters to human drug manufacturers regulated by the FDA’s Center for Drug Evaluation and Research (CDER) have steadily increased over the past four years. In fact, in fiscal year (FY) 2018, CDER issued nearly five times as many warning letters to human drug manufacturers as it did in FY 2015.

Where Data Integrity Breaks Down

Pharmaceutical manufacturing environments have a lot of moving parts, numerous personnel and a considerable amount of data throughout an extensive supply chain. In business environments, employees are expected to multitask and produce high levels of output in a short amount of time with a very narrow margin of error.

Preserving the Integrity of Data

While there are many factors involved in an organization’s data integrity issues, a major contributor is human error. For example, many laboratory processes for determining product quality rely on a significant amount of human input and subjective assays to produce quality control data. It’s not that analysts lack knowledge or skill; it’s mostly because many processes simply allow for errors to occur.

  • Set up role-based authentications to prevent unauthorized access and potential data manipulation. Also, track user access and changes for audit trail purposes. (21 CFR 211.68(b))
  • Store data in a central repository that is secure, forward compatible, immediately accessible and prevents deterioration. (21 CFR 212.110(b))
  • Integrate critical business software systems such as enterprise resource management (ERP) manufacturing execution systems (MES) and laboratory information management systems (LIMS) to establish a single source of truth for all data. This helps ensure the integrity of data as it moves between systems. (21 CFR 211.68(c))
  • Organize and analyze large amounts of data to effectively identify trends, make operational decisions, eliminate duplicated efforts and waste, plan equipment usage and maintenance, etc.(4)
  1. “Under the Spotlight: Data Integrity in Life Sciences,” Deloitte. Retrieved from
  2. “Statement from FDA Commissioner Scott Gottlieb, M.D., and Director of FDA’s Center for Drug Evaluation and Research Janet Woodcock, M.D., on the FDA’s continuing efforts to maintain its strong oversight of generic drug quality issues domestically and abroad” Retrieved from
  3. “Guidance for Industry: Computerized Systems Used in Clinical Investigations,” U.S. Department of Health and Human Services (HHS). Retrieved from



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