Data-Driven Framework for Overage Determination in Biologically Active Formulations

Data-Driven Framework for Overage Determination in Biologically Active Formulations Using Degradation Kinetics and Probabilistic Modeling

This capstone project developed a data-driven framework for determining overage requirements in biologically active formulations using degradation kinetics and probabilistic modeling. Overage, defined as the intentional addition of excess active ingredient to compensate for degradation over time, is commonly used in supplement and pharmaceutical formulations, but is often determined using fixed or empirical assumptions rather than quantitative analysis. The objective of this project was to evaluate whether stability modeling and simulation could be used to establish more accurate, system-specific overage requirements for probiotic and enzyme formulations.

Published stability data for probiotic and enzyme systems were analyzed using first-order degradation kinetics, nonlinear regression, and Monte Carlo simulation to model degradation behavior and predict end-of-shelf-life compliance. The results demonstrated significant differences in degradation behavior between systems, with probiotics requiring measurable overage to maintain label claim compliance while the enzyme system remained comparatively stable. This project highlights the importance of formulation-specific modeling and demonstrates how data analysis can be used to improve formulation strategy, risk assessment, and quality decision-making in biologically active products.