Colorimetric Microplate Assay Coupled with Nonlinear Mixed-Effects Modeling for High-Throughput Evaluation of...

Conventional preservative efficacy tests for ophthalmic formulations rely on discrete colony counts and therefore provide limited insight into the dynamic processes of microbial inactivation and recovery. Such endpoint-based evaluations can obscure formulation-dependent differences in antimicrobial performance and hinder rational optimization of preservative systems. In this study, we developed a quantitative framework that integrates a high-throughput WST-8-based colorimetric microplate assay with nonlinear mixed-effects (NLME) modeling to characterize bacterial killing and regrowth dynamics in borate-buffered systems. Escherichia coli responses were analyzed across 43 formulations using L27 orthogonal and Box-Behnken experimental designs. Bacterial inactivation was described by first-order kinetics, while post-exposure regrowth was modeled using a damage-dependent suppression term. The resulting hierarchical NLME model adequately described bacterial growth trajectories across all formulations, as confirmed by goodness-of-fit diagnostics, visual predictive checks, and bootstrap analyses. Multivariate covariate analysis suggested that borax and pH-related physicochemical conditions contributed to variability in bacterial inactivation rate constants, indicating that antimicrobial activity in borate systems is influenced by buffer composition and the associated physicochemical environment rather than by total borate concentration alone. By coupling structured experimental design with hierarchical population modeling, the proposed framework enables dynamic and mechanism-informed evaluation of preservative efficacy. This approach extends conventional endpoint-based testing and provides a quantitative platform for data-driven optimization and risk assessment of ophthalmic formulations.