Pharmaceutical Computational Solid-State Chemistry

Typical CPSSC approaches may be broadly classified into two major categories— those that are used to guide properties and process optimization (engineering) and those that are used for analysis and interpretation of the experimental results. The former category includes all kind of virtual screening approaches—solvent selection for crystallization and desolvation [34, 35], solvent selection for polymorph screening 

FIGURE 1.4 An outline of stages of solid form development in pharmaceutical industry. RSM is a regulatory starting material. 

Solid form—crystalline, amorphous, liquid crystal 

FIGURE 1.5 Multiscale modeling in computational pharmaceutical solid-state chemistry. Here DEM and FEM are discrete and finite element methods MC, Monte Carlo simulation MD, molecular dynamics MM, molecular mechanics QM, quantum mechanics, respectively statistical approaches include knowledge-based models based on database analysis (e.g., Cambridge Structure Database [32]) and quantitative structure property relationships (e.g., group contributions models [33a]). 

As could be expected, challenges facing the pharmaceutical industry contribute to the advancement of the computational soUd-state chemistry. For example, some of the virtual screening and other CPSSC methods were developed specifically to help address issues of the pharmaceutical industry. Significant progress has been made recently in many traditional applications (e.g., solubility prediction [55], CSP [56], and morphology prediction [25, 57, 58]) in order to accommodate predictions for complex pharmaceutical systems (solid and liquid multicomponent phases of relatively large and flexible molecules). 

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Unfortunately, our understanding of the physics and chemistry of salt formation is not yet at a stage where we can predict a priori the physicochemical properties of a proposed salt. A particular problem in this regard is the formation of a range of salt polymorphs and/or solvates. While qualitative/semiempi-rical guidelines have been developed, the selection process is still largely experiment based. It is to be hoped that developments in computational methods will soon lead to the more accurate prediction of bio-pharmaceutically relevant solid-state properties that will ultimately simplify the task of appropriate salt selection. 

Computational Pharmaceutical Solid State Chemistry, First Edition. Edited by Yuriy A. Abramov. 2016 John Wiley Sons, Inc. Published 2016 by John Wiley Sons, Inc. 

A complex nature of the pharmaceutical solid-state landscape imposes a series of challenges on the pharmaceutical industry. Computational modeling enables better nnderstanding of the fundamentals of solid-state chemistry and allows an enriched selection of solid form with desired physicochemical and processing properties. 

Title Computational pharmaceutical solid state chemistry / edited by Yuriy A. Abramov. 

There are a number of chemistry books available related to computational materials science and to modeling of molecular solid state, but none of the books cover current pharmaceutical industry applications. The intention of this book is to highlight the importance of the computational pharmaceutical solid-state chemistry and to fiU the gap in the current hterature. The book examines the state-of-the-art computational approaches to guide and analysis of solid form experiments and to optimize the physical and chemical properties of active pharmaceutical ingredient (API) related to its stability, bioavailability, and formulatability. While aU methods and approaches described in the book appear to be state of the art, the book is... 

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