FDA Releases Guidance on Data Integrity for In Vivo Bioavailability and Bioequivalence Studies

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On April 1, 2024, FDA issued a draft guidance document, Data Integrity for In Vivo Bioavailability and Bioequivalence Studies, which provides recommendation for data integrity for clinical and bioanalytical portions of bioavailability (BA) and bioequivalence (BE) studies submitted with investigational new drug applications (INDs), new drug applications (NDAs), and abbreviated new drug applications (ANDAs). The guidance also applies to the bioanalytical portion of clinical pharmacologic studies supporting biologic license applications (BLAs) regulated by the Center for Drug Evaluation and Research (CDER) and the bioanalytical portion of nonclinical studies. Applicants and testing sites are also encouraged by the agency to use these recommendations when conducting other studies, including in-vitro and pharmacology and toxicology studies.

All data submitted to FDA must be accurate, complete, and reliable, FDA states in the document. Applicants and testing sites must achieve and maintain data integrity throughout a product’s data lifecycle. To assist applicants in doing this, the guidance document outlines ways to achieve and maintain data integrity for applicants, testing site management, and quality management systems. However, the document does not list all best practices that should be used for data integrity.

Data integrity has been on the agency’s radar for a while. “In recent years, FDA has observed data integrity concerns during the inspection of testing sites, clinical testing sites, and analytical testing sites, and during the assessment of the BA and BE study data submitted in support of applications. Data integrity concerns can impact application acceptance for filing, assessment, regulatory actions, and approval as well as post-approval actions, such as therapeutic equivalence ratings,” the document states (1).

“It is each applicant’s responsibility to achieve and maintain data integrity for their studies, which includes identifying and implementing the most effective and efficient risk-based controls. FDA encourages applicants and testing site management to review FDA regulations and all applicable guidance for industry to understand FDA’s current thinking on a topic,” the agency states in the guidance.

FDA defines data integrity in the document as “the accuracy, completeness, and reliability of data. Accurate, complete, and reliable data should be attributable to the person generating the data, legible, contemporaneously recorded, original or a true copy, and accurate (ALCOA). These characteristics of the data should be maintained throughout the data lifecycle.” The document emphasizes that data integrity and data quality are different, with data quality providing the assurance that data are generated “in compliance with applicable standards and can be used for its intended purpose.”

Guidance provided in the guidance document include recommendations for testing site selection, monitoring and oversight, testing site management, quality management systems, data storage and backup, and quality assurance. Training of personnel who interact with BA and BE study data is also addressed.

Advances in data integrity

With data integrity being such a priority for both regulators and industry, advances in artificial intelligence (AI) and machine learning (ML) have helped drug companies manage and utilize the wealth of data that is available from clinical studies, manufacturing, post-marketing studies, and real-world experiences. But the pharma industry may need to take steps to fully accept and implement these tools.

“Unlike oil or precious gems, data are abundant. However, as with precious gems, quality is paramount. High-quality data can improve efficiency and unlock insights that lead to new discoveries and support better manufacturing processes, especially with the help of [ML and AI]. Relying on bad data, however, can lead to wrong conclusions and have significant cost implications,” according to Natalie Batoux and Dan Rayner. “The biopharmaceutical industry is lagging behind other industries in terms of digital transformation. To catch up, companies will need to treat their data as one of their most valuable assets, prioritize the capture of high-quality data at every level of the business going forward, and check the integrity of their historical data” (2).

References

1. FDA. Data Integrity for In Vivo Bioavailability and Bioequivalence Studies (CDER, April 2024). https://www.fda.gov/media/177404/download
2. Batoux, N. and Rayner, D. In a Digital Goald Rush, Data Integrity is Priceless. Pharmaceutical Technology In the Lab eNewsletter, Oct. 4, 2023. https://www.pharmtech.com/view/in-a-digital-gold-rush-data-integrity-is-priceless

Source: FDA