A Review on Property Estimation Methods and Computational Schemes for Rational Solvent Design: A Focus on Pharmaceuticals

Abstract

This paper provides a review of the available literature on computational schemes for rational solvent design, with a focus on solvent extraction and crystallization (the two most common unit operations) in pharmaceutical industry. The computer-aided design of solvents is important as a cost-effective tool, especially with the regular development of new pharmaceutical molecules. Also, there is a need to minimize the amount and the number of solvents used with regard to environmental, health, and toxicological concerns. This review covers the properties of interest and the predictive methods for estimation of these properties in solvent design including the group contribution based methods, quantitative structure property prediction methods and molecular modeling methods. In addition, the various optimization approaches for rational solvent design such as outer approximation, branch and bound, simulated annealing, and genetic algorithm are also discussed.

Computer-aided molecular design: An introduction and review of tools, applications, and solution techniques

“…A number of approaches have also investigated pharmaceutical applications of CAMD. We note here that a good review exists on the topic of pharmaceutical solvents already [69]. Chemmangattuvalappil et al…”

Computer‐aided solvent selection and design for the efficient extraction of a pharmaceutical molecule

“…Structurally feasible molecules are formed by combinations of UNIFAC groups using the structural constraints given in Table . The rationale for use of these constraints is provided in the literature …”

“…The candidate solvents selected or designed are to be subjected to screening experiments. Due to the practical importance of rational solvent selection and design, many researchers world‐wide have employed computer‐aided solvent selection and design tools for this purpose …”

“…Our use of the computer‐aided approach is based on literature review that shows that computer‐aided tools are extensively employed for solvent selection and design in the pharmaceutical industry. A previous publication from our group provides a comprehensive literature review of the use of the CAMD framework for the design of solvents for processes involving pharmaceuticals . A brief survey of the relevant literature is presented here.…”

Predicting Thermodynamic Properties over Combinatorially Large Chemical Spaces

“…The ability to accurately estimate thermodynamic properties without the need for laboratory experiments has the potential to save both time and resources in fields such as polymer [147] and solvent [148] design as well as drug discovery. [12][13][14] This time and cost savings is important both in the design of new molecules, where properties are unknown, and 'reverse property prediction' where a model or molecule is designed to match specific experimental targets, such as designing metal-organic frameworks (MOFs) with specific gas loadings.…”