Projects per year
Abstract
The solubility of organic compounds plays an important role in pharmaceutical manufacturing, since key unit operations such as reactors, crystallisers, and solvent extraction units all rely on successful reagent dissolution. Consequently, it has recently been suggested that predictive solubility modelling should be used when developing new pharmaceutical processes so as to minimise the amount of experimentation required to understand the solubility of new molecular entities (NMEs). In response to this, the present paper has used the Nonrandom Two-liquid Segment Activity Coefficient (NRTL-SAC) model to describe the solubility of six organic compounds used in the production of an experimental anti-cancer drug, Adavosertib. Specifically: AZD1775 Adavosertib Maleate, AZD1775 Aniline Maleate, AZD1775 Nitropip, AZD1775 Hydroxymethylsulfanyl, AZD1775 Bromopyridine.HBr, and AZD1775 Pyrimidine. Meanwhile, it has used this model to estimate the melting temperature and enthalpy of fusion associated with each of these compounds; circumventing the various difficulties which can arise when measuring these values directly (i.e., the presence of exothermic and/or endothermic phenomena close to the melting point).
Original language | English |
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Number of pages | 22 |
Journal | ACS Omega |
Publication status | Accepted/In press - 8 May 2025 |
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RAPID: ReAl-time Process ModellIng and Diagnostics: Powering Digital Factories
Polydorides, N. (Principal Investigator) & Gerogiorgis, D. (Co-investigator)
Engineering and Physical Sciences Research Council
1/08/21 → 20/11/25
Project: Research
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A Digital Twin via First-Principles Modelling and Data Analytics for Process Optimisation in Pharmaceutical Manufacturing
Gerogiorgis, D. (Principal Investigator)
1/10/20 → 31/01/22
Project: Research