Real Time Release

Real time release is the ability to evaluate and ensure the acceptable quality of in-process and/or final product based on process analytical data. Typically, the PAT component of real time release can include a validated combination of assessed material attributes (in-process and/or product at final process stage), process controls, process end-points, and other critical process parameters. Material attributes can be assessed using direct and/or indirect (e.g., correlated) process analytical methods. The combined process analytical measurements and other test data gathered during the manufacturing process can serve the basis for real time release of the final product and would demonstrate that each batch conforms to established regulatory quality attributes. We consider real time release testing to be an example of alternative analytical procedures for final product release.

Real time release as defined in this guidance builds on parametric release for heat terminally sterilized drug products, a practice in the United States since 1985. In real time release, material attributes are measured and controlled along with process parameters. Real time release as defined in this guidance may fulfill the requirements of parametric release for all dosage forms as defined by other regulatory authorities.

The Agency's approval should be obtained prior to implementing real time release for final products. Process understanding, control strategies, plus on-, in-, or at-line measurement of critical attributes that relate to product quality can provide a scientific risk-based approach to justify how real time quality assurance may be equivalent to, or better than, laboratory-based testing on collected samples. Real time release as defined in this guidance meets the requirements of testing and release for distribution (21 CFR 211.165).

With real time quality assurance, the desired quality attributes are ensured through continuous assessment during manufacture. Data from production batches can serve to validate the process and reflect the total system design concept, essentially supporting validation with each manufacturing batch.

Risk-Based Approach

Within an established quality system and for a particular manufacturing process, one would expect an inverse relationship between the level of process understanding and the risk of producing a poor quality product. For processes that are well understood, opportunities exist to develop less restrictive regulatory approaches to manage change. Thus, a focus on process understanding can facilitate risk-based regulatory decisions and innovation. Note that risk analysis and management is broader than what is discussed within the PAT framework and may form a system of its own. This is currently under discussion as part of the broad FDA Risk-Based initiative.

Process Understanding

A process is generally considered well understood when (1) all critical sources of variability are identified and explained; (2) variability is managed by the process; and, (3) product quality attributes can be accurately and reliably predicted over the ranges of acceptance criteria established for materials used, process parameters, and manufacturing environmental and other conditions. The ability to predict reflects a high degree of process understanding. Although retrospective process capability data are indicative of a state of control, these alone may be insufficient to gauge or communicate process understanding.

The emphasis on process understanding provides a range of options for qualifying and justifying new technologies such as modern on-line process analyzers intended to measure and control physical and/or chemical attributes of materials to achieve real time release. For example, if process knowledge is not shared or communicated when proposing a new process analyzer, the test-to-test comparison between an on-line process analyzer (e.g., NIR spectroscopy for content uniformity) and a conventional test method (e.g., a wet chemical test) on collected samples may be the only available option. In some cases, this approach may be too burdensome and may discourage the use of some new technologies (e.g., use of acoustic measurement patterns or signatures for process controls). An emphasis on process knowledge can provide less burdensome approaches for validating new technologies for their intended use.

Transfer of laboratory analytical methods to at-line methods using test-to-test comparisons may not necessitate a PAT approach. Existing regulatory and compendial approaches and guidances on analytical method validation should be considered.

Structured product and process development on a small scale, using experiment design and an on- or in-line process analyzer to collect data in real time for evaluation of kinetics on reactions and other processes such as crystallization and powder blending can provide valuable insight and understanding for process optimization, scale-up, and technology transfer. Process understanding then continues in the production phase when possibly other variables (e.g., environmental and supplier changes) may be encountered. Therefore, continuous learning through data collection and analysis over the life cycle of a product is important.