Simulation-based content uniformity engineering for drug development and manufacturing

• Published in: International journal of pharmaceutics Vol. 684; p. 126132
• Main Authors: Chu, Kevin T., Osan, Remus, Tin, Nicole, Bhattacharya, Somdatta, Lai, Chiajen
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 10.11.2025
• Subjects: Content Uniformity; Monte Carlo Simulation; Particle Size Distribution; Monte Carlo Simulation; Particle Size Distribution; Content Uniformity
• ISSN: 0378-5173; 1873-3476; 1873-3476
• DOI: 10.1016/j.ijpharm.2025.126132

[Display omitted] Stochastic models and Monte Carlo (MC) simulations of content uniformity (CU) are powerful tools for assessing CU risk without extensive experimental effort. However, simulations are valuable only if they are accurate, used appropriately, and embedded within natural operational workflows. Toward these ends, we first analyze a stochastic model of tablet formation to develop simple quantitative characterizations of dose regimes based on the active pharmaceutical ingredient (API) particle size distribution (PSD) that provide early guidance on CU risk. Second, we study a MC simulation of the stochastic tablet formation model to validate the importance of selecting upper particle size cutoff diameters used in simulation based on manufacturing processes including a margin of safety. Finally, we demonstrate simulation-based PSD engineering and CU risk assessment tools for process chemists and formulators designed to fit into common workflows, such as early-stage guidance for PSD targets, predicting USP < 905 > pass rates and statistics, and exploring the API PSD parameters and dose strengths where CU risk is low.