Application of Scale-Up Methodologies to Industrial Pharmaceutical Processes

Abstract

Contract Development and Manufacturing Organizations (CDMOs), such as Esteve, are pivotal in sustaining the supply chain by producing commercial Active Pharmaceutical Ingredients (APIs) to meet global demand. Additionally, they manufacture APIs in clinical phases to expedite their application for the global population. The CDMO sector faces significant constraints due to customer timelines, clinical development needs, and project costs. Time is a critical factor, impacting both the client's supply chain and the effective scheduling of production in multipurpose plants. Achieving a right-first-time scale-up is essential, ensuring timely delivery to clients and preventing disruptions in plant scheduling, which can create a cascading effect, delaying multiple projects and compromising their delivery timelines. Efficient time management ultimately enhances business performance by increasing project throughput and maintaining competitiveness in the CDMO sector. Since the 1950s, empirical and semi-empirical correlations have been developed for batch stirred vessels. In recent decades, the emergence of commercial software and numerical simulation tools, such as Computational Fluid Dynamics (CFD), has significantly advanced the application of mixing and heat transfer models. These tools enable detailed simulations of multiphase flows and mixing processes, providing a deeper understanding of the dynamics within stirred vessels and allowing the systematic application of the scale-down strategy during laboratory trials. As a result, clients increasingly demand these modeling capabilities, recognizing their value in ensuring process reliability and efficiency. This work presents a novel scale-up methodology for Esteve, centered on batch process modeling and incorporating scale-down strategies to ensure accurate first-time scale-up, with a focus on mixing phenomena. Extensive literature, including articles, books, and handbooks, was reviewed to understand the impact of mixing on common fine chemical unit operations and the evolution of modeling approaches since the 1950s. This foundational knowledge facilitated the understanding of various modeling software fundamentals. Following initial analyses, new R&D laboratory equipment, including impellers and baffles, was designed to enhance geometric similarity between plant and laboratory vessels. VisiMix software was identified as the most suitable mixing modeling tool due to its robust fundamentals, rapid simulation capabilities, and precise ability to simulate the geometries of nearly all Esteve reactors. Over several years, the application of scale-down strategy in numerous Esteve projects, across more than 300 unit operations, has generated essential knowledge for developing unique scale-up strategies for various unit operations. These include fed-batch reactions, liquid-liquid reactions and extractions, solid-liquid reactions, crystallizations, as well as gas-solid-liquid reactions. The proposed scale-up methodology comprises several methods: i) a scale-up factor detection workflow for each unit operation, enabling chemists to identify scale-up factors without requiring mixing calculations; ii) once a scale-up factor is identified, key mixing parameters for scale-down are defined depending on each unit operation; and iii) a scale-up risk assessment evaluation is conducted prior to process validation, complementing the information from process development to establish the operational range for each process parameter (PARs studies). The most common unit operations have been exemplified through case studies of projects developed at Esteve.

Date of Award	16 Jul 2025
Original language	English
Supervisor	Ramon Alibes Arques (Director) & Ramon Berenguer Maimó (Director)