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Continuous flow synthesis of active pharmaceutical ingredients (APIs) can offer access to process conditions that are otherwise hazardous when operated in batch mode, resulting in improved mixing and heat transfer, which enables higher yields and greater reaction selectivity. Reaction kinetic parameter estimation from flow synthesis data is an essential activity for the development of process models for drug substance manufacturing unit operations and systems, facilitating a reduction of experimental effort and accelerating development. The flow synthesis of lomustine, an anti-cancer API, in two flow reactors (carbamylation + nitrosation stages) was recently demonstrated by Jaman et al. (Org. Process Res. Dev., 2019, 23, 334). In this study, we postulate kinetic rate laws based on hereby proposed reaction mechanisms presented for the first time in the literature for this API synthesis. We then perform kinetic parameter regression for the proposed rate laws, on the basis of published data, towards establishing reactor models. For the carbamylation (irreversible reaction), we compare two candidate reaction rate laws, an overall third-order rate law (first-order in each reagent) deriving best fit. For the nitrosation, we propose two substitution reactions on the basis of published mechanisms (a rate-limiting equilibrium step, followed by a fast irreversible reaction) with very good model fit.
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- 1 Finished
A Digital Twin via First-Principles Modelling and Data Analytics for Process Optimisation in Pharmaceutical Manufacturing
1/10/20 → 30/09/21