Work

PharmaPy 2.0: Dynamic process modeling and analysis of end-to-end continuous pharmaceutical manufacturing

Year: 2026

Type: article

Abstract: As pharmaceutical manufacturing transitions from traditional batch processes to continuous manufacturing (CM), there is a need for CM design and development tools that integrate drug substance and drug product unit operations to enable a comprehensive assessment of product quality. PharmaPy, a Python-based framework, was recently proposed to advance CM. The original model library, however, only covered upstream drug substance processing. In this work, new capabilities, including drug product unit operations such as feeder, blender, roller compactor, and tablet press, have been added to the PharmaPy framework, enabling end-to-end dynamic study of direct compaction and dry granulation processes. The platform supports dynamic process modeling through computational efficiency and model accuracy by allowing different mechanistic, semi-mechanistic, and data-driven models. Sensitivity and feasibility analysis are performed on the integrated simulator to identify critical input variables and their corresponding design spaces for desired product quality. The dynamic response of process models is studied through changes in input variables. The enhanced PharmaPy package can now support decision-making from early research and development stages through manufacturing.

Source: Computers & Chemical Engineering

DOI: 10.1016/j.compchemeng.2026.109593

Authors: Mohammad Shahab, Kensaku Matsunami, Zoltan K. Nagy, Gintaras V. Reklaitis

Institutions: Purdue University West Lafayette, Indian Institute of Chemical Technology

Language: English

Topic: Granular flow and fluidized beds

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $4,050