Whitepaper: Optimal Validation Design
In this approach we not only incorporate sound statistical theory, but also all the peculiarities of the estimations, such as parameter and beta-expectation tolerance interval calculations.
In this approach we not only incorporate sound statistical theory, but also all the peculiarities of the estimations, such as parameter and beta-expectation tolerance interval calculations.
Before undertaking a validation attempt of an analytical method, it is important to think about the experimental design. In this white paper we go into some theoretical aspects and requirements needed to estimate the optimal experimental design from a cost vs. risk perspective. As a starting point and principle we use the Total Analytical Error (TAE) which we believe is the future of analytical method validation, and which is also slowly getting its way into the governing guidelines of analytical method validation such as ICH Q2(R2), ICH Q14 and USP <1220>.