Roles of mechanistic, data-driven, and hybrid modeling approaches for pharmaceutical process design and operation

Current Opinion in Chemical Engineering, Год журнала: 2024, Номер 44, С. 101019 - 101019

Опубликована: Апрель 5, 2024

Язык: Английский

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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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Dynamic flow experiments for data-rich optimization

Current Opinion in Green and Sustainable Chemistry, Год журнала: 2024, Номер 47, С. 100921 - 100921

Опубликована: Апрель 8, 2024

Flow chemistry is having an increasing influence on manufacturing in the chemical industry, but significant barriers remain development of these continuous processes. Dynamic flow experiments have potential to democratize and accelerate process a data-rich manner, reducing time material wastage. Models based data gathered can also be leveraged decrease waste environment. Here, we summarize literature reports dynamic (most which are from past 5 years), with focus on: experiment design, analytics, utilization resulting data. Finally, example pharmaceutical discussed detail. A higher uptake industrial environments coming years will undoubtedly facilitate greener

Язык: Английский

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Accelerating reaction modeling using dynamic flow experiments, part 2: development of a digital twin

Reaction Chemistry & Engineering, Год журнала: 2023, Номер 8(11), С. 2849 - 2855

Опубликована: Янв. 1, 2023

We describe the development of a digital twin for Michael addition continuous-flow process using data generated from dynamic flow experimentation.

Язык: Английский

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Dynamic experiments in flow accelerate reaction network definition in a complex hydrogenation using catalytic static mixers

Reaction Chemistry & Engineering, Год журнала: 2023, Номер 9(1), С. 132 - 138

Опубликована: Сен. 29, 2023

The combination of transient flow experiments with process analytical technology (PAT) enables the rapid characterization and kinetic modelling a complex ketone hydrogenation, catalyzed by catalytic static mixers (CSMs).

Язык: Английский

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Kinetic Study and Model-Based Design Space Determination for a Drug Substance Flow Synthesis Using an Amination Reaction via Nucleophilic Aromatic Substitution

Organic Process Research & Development, Год журнала: 2024, Номер 28(5), С. 1793 - 1805

Опубликована: Апрель 4, 2024

A kinetic study and model-based design space determination for drug substance flow synthesis using an amination reaction are presented. experiment was conducted to synthesize 3-fluoro-4-morpholinobenzonitrile from 3,4-difluorobenzonitrile, morpholine, diazabicycloundecene. Concentrations, residence time, temperature, reactor inner diameter were varied gather the data. set of equations defined describe mass energy balances, developed model could reproduce experimental profiles with high accuracy. By incorporating Reynolds number into pre-exponential factor, one-dimensional account performance variations in different conditions. The then used identify space, considering yield, productivity, environment. also evaluated process robustness given pulse disturbances, which help required sensor monitoring. Finally, a method facilitating regulatory processes proposed. presented approach can aid producing high-quality pharmaceuticals efficient, sustainable, cost-effective way by utilizing digital power.

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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A pharma perspective on sustainability advantages through adoption of continuous flow

Current Opinion in Green and Sustainable Chemistry, Год журнала: 2024, Номер 46, С. 100886 - 100886

Опубликована: Фев. 3, 2024

Язык: Английский

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An Automated Dual Modeling Approach to Accelerate Reaction Analysis and Optimization

Опубликована: Март 5, 2024

In modern pharmaceutical research, the demand for expeditious development of synthetic routes to active ingredients (APIs) has led a paradigm shift towards data-rich process development. Conventional methodologies en-compass prolonged timelines reaction and analytical model developments. Both method developments are separated into different departments often require an iterative optimize models. Addressing this issue, we intro-duce innovative dual modeling approach, seamlessly integrating Process Analytical Technology (PAT) strategy with optimization. This integrated approach is exemplified in diverse amidation reactions synthesis API benznidazole. The platform, characterized by high degree automation minimal operator in-volvement, achieves PAT calibration through “standard addition” approach. Dynamic experiments executed screen broad space gather data fitting kinetic parameters. Employing Julia-coded software program facilitates rapid parameter in-situ optimization within minutes. highly automated workflow not only expedites understanding chemical processes, but also holds significant promise time resource savings industry.

Язык: Английский

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Hybrid Model-based Design Space Determination for an Active Pharmaceutical Ingredient Flow Synthesis using Grignard Reaction

Computer-aided chemical engineering/Computer aided chemical engineering, Год журнала: 2024, Номер unknown, С. 463 - 468

Опубликована: Янв. 1, 2024

Язык: Английский

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