Solubility Prediction in Pharmaceutical Process Development
Predictive Modelling for Solubility Optimization
The solubility of crystalline solids in organic solvents plays a key role in the design of small molecule pharmaceutical synthesis. To save both time and experimental resources, predictive models for solubility are generally employed. While perhaps the most common application is to select solvent(s) for the final (re)crystallization of the active pharmaceutical ingredient (API), the tools and methodologies for solubility prediction are readily extended to several other applications. This includes prediction of the solubility of impurities (e.g., to assist in designing a process to preferentially reject impurities), the solubility of intermediates (e.g., to assist with intermediate isolation), or even the estimation of how a solute will partition between two liquid phases (e.g., to predict the outcome of an extractive workup).
This presentation will focus on the current state-of-the-art models, methodologies, and applications of solubility prediction commonly used in pharmaceutical process development. It will also highlight a recent collaboration, as part of the Enabling Technologies Consortium (ETC), in which five peer pharmaceutical companies engaged in a collaboration to benchmark the performance of several commonly-used solubility models by predicting the solubility of 24 solutes in 80 solvent systems.
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About the Presenter
Dr. Francesco Ricci
Boehringer Ingelheim
Francesco (Frank) Ricci obtained a B.S. in Chemical Engineering from Manhattan College in 2010, and a Ph.D. in Chemical Engineering from Princeton University in 2016. After his graduate studies, Frank joined Boehringer Ingelheim Pharmaceuticals in Ridgefield, CT. Since joining BI, he has worked in the Solid State & API Engineering group, which focuses primarily on small-molecule crystallization process development and scale-up. Over the past 6 years at BI, Frank has focused on expanding digitalization and modelling efforts, with a focus on physicochemical and unit operation modelling, as well as in situ PAT applications. Since 2017, Frank has also served as an adjunct professor of Chemical Engineering at Manhattan College, where he teaches graduate-level thermodynamics. Both industrially and academically, Frank maintains a strong interest in thermodynamics, with a particular emphasis on the modelling of phase equilibria – the most pertinent of which to crystallization is of course solid-liquid equilibrium (e.g., the solubility of crystalline solids in organic solvents). To this end, he is also a participating member of the Enabling Technologies Consortium’s Solubility Modelling Group.
