Impact of modeling and simulation on pharmaceutical process development

Current Opinion in Chemical Engineering, Год журнала: 2025, Номер 47, С. 101093 - 101093

Опубликована: Янв. 27, 2025

Язык: Английский

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Testing on continuous production of mefenamic acids - design of experiment through simulation and process optimisation

European Journal of Pharmaceutical Sciences, Год журнала: 2025, Номер unknown, С. 107102 - 107102

Опубликована: Апрель 1, 2025

In the pharmaceutical manufacturing industry, continuous production methods have been recognised as providing several benefits compared to traditional batch production. These include increased flexibility, higher product output, enhanced quality assurance through better monitoring techniques, and more consistent distribution of Active Pharmaceutical Ingredients (APIs). Despite these clear advantages, there is a lack research focused on simultaneous optimisation multiple sub-processes in manufacturing. This study explores processes production, explicitly targeting mefenamic acid using wet milling (WM) mixed-suspension mixed-product removal (MSMPR). We employ data-driven evolutionary algorithms address many-objective problems (MaOPs). High-fidelity model-generated data generated via General Process Modelling System (gPROMS) subsequently utilised develop simpler surrogate models based Radial Basis Function Neural Network (RBFNN). enables very fast simulations, suitable for use with computationally intensive machine learning algorithms. Utilising algorithms, are used model-based process optimisation. The efficacy MaOP approach evaluated range numeric visual performance indicators. Our findings underscore viability integrating high-fidelity discern functional relationships between dependent variables (objective functions) independent (decision variables), robust framework within domain. approximated solutions are, average, 58% than obtained from Latin hypercube sampling. chosen optimal can form basis parameter setting upcoming experimental campaigns. significance this work demonstration, first time, pharmaceuticals simple derived high fidelity simulations Machine Learning.

Язык: Английский

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Probabilistic Design Space Exploration and Optimization via Bayesian Approach for a Fluid Bed Drying Process

European Journal of Pharmaceutical Sciences, Год журнала: 2025, Номер unknown, С. 107116 - 107116

Опубликована: Май 1, 2025

Язык: Английский

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Spectroscopic Methods for Studying Reaction Mechanisms

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 153 - 208

Опубликована: Июнь 4, 2025

Spectroscopic methods represent key tools for identifying organic reaction mechanisms and obtaining information about molecular structures transient intermediates. However, the broad repertoire of reactions, frequent difficulties in tracking compound intermediates, challenges interpretation spectral data can hamper progress lead to misconceptions. This chapter aims explain these alongside kinetic studies isotope effects comprehensively understand dynamics. explains how nuclear magnetic resonance, infrared spectroscopy, ultraviolet‒visible computer-based mass spectrometry reveal interactions highlights importance such approaches through comparison simulations. The finalized section demonstrates need a variety perspectives overall explanations promoting synthesis complex compounds. field looks forward significant with further real-time education on reliable machine learning using spectroscopy.

Язык: Английский

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Controlled Nucleophilic Aromatic Substitution of Hexafluorobenzene Using a Flow Microreactor

Journal of Fluorine Chemistry, Год журнала: 2024, Номер 280, С. 110366 - 110366

Опубликована: Окт. 24, 2024

Язык: Английский

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