Regulatory Policies - Australian Therapeutic Goods Administration (TGA)
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The Australian Therapeutic Goods Administration (TGA) has worked with the industry in supporting the validation and implementation of RMMs. During the 2010 PDA 5th Annual Global Conference on Pharmaceutical Microbiology, Dr. Vivienne Christ (Chief Microbiologist, TGA Office of Laboratories and Scientific Services) discussed her agency's policies and validation guidance that they follow with regard to RMMs.
The TGA utilizes relevant sections in the Ph. Eur. and British Pharmacopoeia (BP) in that these compendia also allow for the validation of alternate methods. They also rely on the validation guidance from USP Chapter <1223>, Ph. Eur. Chapter 5.1.6, PDA Technical Report #33, and ISO 17025 (validation of non-standard methods), to name a few. From the legislative perspective, the TGA also turns to the TGA GMPs, which allows for other acceptable methods as long as they are shown to be equivalent to those in the GMP guide, as well as Annex 11 (computer validation) and Annex 15 (IQ, OQ, PQ). However, unlike other regulatory agencies, such as the FDA, the TGA only “quietly” embraces new technologies, and to date, they have not communicated a formal statement or policy.
The TGA views RMMs to be used in a wide range of applications, including finished product testing and in-process testing. Validation expectations include a DQ, IQ and OQ performed by the vendor, and the PQ (jointly performed by the vendor and user) and verification of the method using actual product. Testing on potential interfering substances should be performed, and for users intending to develop a matrix testing strategy (i.e., grouping products together), a justification for doing so should be provided. Furthermore, there is the expectation that equivalence or superiority to classical method is demonstrated, as well as the computer validation of software. For a qualitative method, the validation should address specificity, sensitivity, ruggedness, robustness, and equivalence. For quantitative tests, the user should demonstrate accuracy, precision, ruggedness, robustness, equivalence sensitivity, linearity, and specificity.