Despite the clinical success of lipid nanoparticles (LNPs), formulation optimisation remains dominated by inherited lipid ratios and screening approaches that fail to capture the combined influence of composition and manufacturing process. In this study, one-factor-at-a-time (OFAT) and Design of Experiments (DoE) strategies were applied to investigate how lipid molar ratio influences critical quality attributes (CQAs) and mRNA expression. In addition, manually executed and automated microfluidic manufacturing methods were compared to assess their impact on formulation-performance relationships. Across all strategies, multiple formulations beyond the standard molar ratio achieved comparable physicochemical properties, including particle size < 120 nm, low polydispersity index (PDI < 0.2), and high encapsulation efficiency (> 75%). Differences in CQAs and expression profiles were observed between manually and automated microfluidic manufactured DoE formulations, indicating that both composition and process conditions influence formulation performance. DoE analysis revealed non-linear and process-dependent relationships between lipid composition and CQAs, with limited predictive capability within the explored design space, particularly for biological outputs. Comparison of OFAT and DoE datasets demonstrated that while OFAT identifies directional trends within a constrained design space, DoE provides broader insight into interaction effects and formulation trade-offs. Overall, these findings demonstrate that the conventional lipid ratio represents a robust but not necessarily optimal formulation and support a shift towards context-dependent, design-space-driven optimisation of LNP systems.
mRNA Technology