With PAT, these CQAs can be measured in real time, therefore leading to real-time, continuous quality control of the process. PAT maps the route to a Quality by Design (QbD) approach to production. This is consistent with the FDA's current drug quality system: quality should not be tested into products; it should be built-in or should be by design.
The PAT framework uses in-line or on-line instrumentation to analyze raw, in-process materials and final products, in real time. Complex, multivariate and univariate instrument data is interpreted, from which the critical process parameters are predicted and where necessary adjusted to optimize the outcome of the process.
Analytical results make it possible to predict the quality of the end material, and to understand how altering critical process parameters (CPPs) will affect the process and end product.
The prediction of CQAs is made by analyzing the univariate and spectral instrumentation data with mathematical and statistical procedures known as multivariate analysis (MVA, also known as chemometrics).
In turn, by executing experiments where real-time quality predictions are made, the relationships between the CPPs and CQAs can be established, so that true process understanding is developed. Armed with this knowledge, it is possible to ‘close the loop’ and control the process using those quality predictions.
PAT can be employed at all stages of the development and manufacturing process, from small-scale implementations within laboratory, R&D or pilot plant operations, through to complex, interconnected GMP processes.
It has an established reputation in providing significant quality and commercial benefits.