Abstract

Using Multivariate Data Analysis to Quantify Physicochemical Properties of Excipients

Nirav Shah, Senior Data Scientist, MKS Data Analytics Solutions (formerly MKS Umetrics)

FDAs PAT Guidance points out the importance of "risk based approaches", "mechanistic understanding of formulation and process factors" and "the latest scientific advances". This presentation is based on validated software and as so not the latest scientific advances but it will demonstrate how risk can be minimized and how better understanding of formulation and mechanistic factors can be achieved. The presentation will be using excipients as an example as excipients are source of variation in production, so that understanding variability in excipient physico-chemical properties is important. The demonstrated analysis method offers drug product developers several advantages over present experimental methods, including the ability to examine excipient products for manufacturing site and/or year-to-year variations, to quantify a domain of prior experience for each excipient by determining the percentage of excipient lots contained within a multi-dimensional ellipsoid described by the excipient lots used during drug product development, and to rationally select excipient lots from the vendors inventory to maximize the domain of prior experience throughout the drug development process.