Thought Leadership

White Paper
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>.
Journal Article
The ICH-Q2 has stated that the objective of validation of an analytical procedure is to demonstrate that it is suitable for its intended purpose, yet it – as well as the ICH-Q14 – fails to clearly define the actual aim of analytical procedure, leading to misunderstanding and confusion. Bruno Boulanger, Ph.D., Global Head Statistics and Data Science at PharmaLex, discusses how Bayesian statistics and interpretation bridge the gaps in the guidelines.
Journal Article
Don’t settle for approximations, make smart, risk-based economic decisions. Bruno Boulanger explains how the application of Bayesian statistics can assist with decision making when data samples are small but pre-existing information is available.
Video

Using Bayesian Statistics for Clinical Research

#ChatsWithChaudhrey Brad Carlin, PharmaLex using Bayesian Statistics for Clinical Research
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