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March 18, 2026

Good laboratory practice or GLP is a set of principles intended to assure the quality and integrity of non-clinical laboratory studies that are intended to support research or marketing permits for products regulated by government agencies. The term GLP is most associated with the pharmaceutical industry and the required non-clinical in vitro and in vivo toxicology assessments that must be performed prior to approval of new drug products. However, GLP applies to many other non-pharmaceutical agents such as color additives, food additives, food contamination limits, food packaging, and medical devices.

The regulations in the United States can be found in 21 CFR Part 58  and for the European Union via the Organization for Economic Co-operation and Development (OECD).

What is GLP in pharma?

This blog post isn’t a comprehensive review of GLP regulations. However, there are some key areas of interest that touch pharmacokineticists.

The most important area is the scope of these regulations. Too often, researchers feel compelled to comply with GLP regulations in contexts where they do not apply. This then creates confusion, extra work, and additional costs. Let’s look at the scope of GLPs from the FDA documents and the OECD (italics added for emphasis):

This part prescribes good laboratory practices for conducting non-clinical laboratory studies … (FDA 21CFR58)

These Principles of Good Laboratory Practice should be applied to the non-clinical safety testing … (OECD, No.1)

When is GLP used in drug development and who oversees it?

GLP only applies to non-clinical studies and testing. It does not apply to clinical studies. Clinical studies are governed by Good Clinical Practices (GCP), the Declaration of Helsinki, and other regulations intended to protect human participant safety.

Furthermore, much of the GLP structure depends on the roles and responsibilities of the Study Director. This individual is responsible for the oversight and execution of all aspects of the non-clinical study. Study Directors don’t exist in the clinical study arena. Thus, GLP principles cannot be applied to the clinical setting.

GLP: A quality, not a scientific, system

Beyond the scope, there are two other items I would like to discuss. First, GLP is a quality management system, not a scientific management system. Or, in other words, GLP defines a set of quality standards for study conduct, data collection, and results reporting.

GLP does not define scientific standards. If a study follows GLP, then you can be reasonably confident that the reported results were collected as outlined in the study protocol. However, this provides no assurances that the study appropriately addresses the scientific hypothesis.

In the world of cooking, GLP would ensure that someone follows the recipe as written. Yet it does not assure you that the recipe was good, or that the resulting item will be tasty!

Second, a key component of the GLP system of quality standards is the Quality Assurance unit (QA). This QA unit is an independent group or individual that monitors the entire study conduct, analysis, and reporting. The purpose of QA is to verify that staff followed all written procedures throughout the study.

As an example, perhaps an SOP says that a senior pharmacokineticist must review the results prior to finalization. The QA auditor will verify that this review occurred. Verification could be done by reviewing a signed document, reviewing an electronic signature, or even speaking with the reviewer. The QA auditor will also ensure that the senior pharmacokineticist has adequate training (as defined by SOPs in the organization) to perform his or her duties.

This quality audit provides confidence that the study staff followed procedures. But again, this audit does not ensure that the procedures themselves are of high quality, or that researchers did not make any errors in the analysis.

Here are a few examples of how GLPs are often misinterpreted:

  1. Using GLP to perform bioanalysis for human clinical trials. As noted in the scope for both GLP and OECD GLP, the principles of GLP only apply to non-clinical studies. Therefore, following GLP, particularly with respect to QA reviews is an unnecessary cost. It is more important to follow analytical validation plans.
  2. Performing GLP as a single person. GLP work requires a minimum of 2 or 3 individuals. These are the person performing the work (analyst), a person reviewing the work (management), and a quality assurance reviewer (QA). If SOPs are written well, the analyst and the management can be the same individual. However, QA must always be an independent person.
  3. Results of GLP studies are “right.” A statement that a study was conducted in conformance with GLP simply means that quality systems were followed, and that the study’s results accurately report its conduct. It does not indicate that the conclusions drawn are accurate, scientifically robust, or even useful!

I hope you take some time to learn more about GLP and apply it correctly in your future work.

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This blog was originally published in December 2013 and has been updated for accuracy.

Author

Kevin Snyder, PhD

Director of Nonclinical Innovation and Emerging Technologies

Kevin Snyder recently served at FDA/CDER as the Associate Director of Nonclinical Informatics, where he managed data science and informatics initiatives to support the pharmacology/toxicology review program. These initiatives included research efforts to develop methods to optimize the regulatory use of standardized electronic CDISC-SEND-formatted toxicology study data as well as internal informatics projects to promote the development of scientifically sound, data-driven regulatory policies. Kevin has joined Certara in a new role as Director of Nonclinical Innovation and Emerging Technologies, guiding pharmaceutical sponsors in their efforts to strategically integrate nonclinical data across all phases of pharmaceutical development and enhance new drug safety. Prior to this transition, Dr. Snyder had served in various roles at the FDA: first in CDRH as a bioinformatician and in vitro diagnostic device reviewer and then as pharmacology/toxicology reviewer in CDER. He has played a leading role in several precompetitive consortia, including the Pistoia Alliance, CDISC, PHUSE, VICT3R, and BioCelerate, supporting efforts to enhance the implementation and utilization of standardized toxicology study data. Kevin is a dedicated advocate for the modernization of regulatory toxicology via strategic adoption of data standards and data science techniques to drive innovation in areas such as predictive modeling, virtual controls, and new approach methodologies (NAMs).

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