Computational crystal structure prediction (CSP) methods can now be applied to the smaller pharmaceutical molecules currently in drug development. We review the recent uses of computed crystal energy landscapes for pharmaceuticals, concentrating on examples where they have been used in collaboration with industrial-style experimental solid form screening. There is a strong complementarity in aiding experiment to find and characterise practically important solid forms and understanding the nature of the solid form landscape.
%0 Journal Article
%1 Price2016b
%A Price, Sarah L.
%A Braun, Doris E.
%A Reutzel-Edens, Susan M.
%D 2016
%I The Royal Society of Chemistry
%J Chem. Commun.
%K crystal-structure-prediction pharmaceutical-molecules
%N 44
%P 7065--7077
%R 10.1039/c6cc00721j
%T Can computed crystal energy landscapes help understand pharmaceutical solids?
%U http://dx.doi.org/10.1039/c6cc00721j
%V 52
%X Computational crystal structure prediction (CSP) methods can now be applied to the smaller pharmaceutical molecules currently in drug development. We review the recent uses of computed crystal energy landscapes for pharmaceuticals, concentrating on examples where they have been used in collaboration with industrial-style experimental solid form screening. There is a strong complementarity in aiding experiment to find and characterise practically important solid forms and understanding the nature of the solid form landscape.
@article{Price2016b,
abstract = {{Computational crystal structure prediction (CSP) methods can now be applied to the smaller pharmaceutical molecules currently in drug development. We review the recent uses of computed crystal energy landscapes for pharmaceuticals, concentrating on examples where they have been used in collaboration with industrial-style experimental solid form screening. There is a strong complementarity in aiding experiment to find and characterise practically important solid forms and understanding the nature of the solid form landscape.}},
added-at = {2019-03-11T21:00:05.000+0100},
author = {Price, Sarah L. and Braun, Doris E. and Reutzel-Edens, Susan M.},
biburl = {https://www.bibsonomy.org/bibtex/2d90c5a35c53e50f7510b82f5b626c853/fairybasslet},
citeulike-article-id = {14316715},
citeulike-linkout-0 = {http://dx.doi.org/10.1039/c6cc00721j},
citeulike-linkout-1 = {http://www.rsc.org/Publishing/Journals/article.asp?doi=C6CC00721J},
doi = {10.1039/c6cc00721j},
interhash = {c56378a825d5c866b68d33e91938cd9e},
intrahash = {d90c5a35c53e50f7510b82f5b626c853},
issn = {1359-7345},
journal = {Chem. Commun.},
keywords = {crystal-structure-prediction pharmaceutical-molecules},
number = 44,
pages = {7065--7077},
posted-at = {2017-03-23 09:19:20},
priority = {0},
publisher = {The Royal Society of Chemistry},
timestamp = {2019-03-11T21:06:37.000+0100},
title = {{Can computed crystal energy landscapes help understand pharmaceutical solids?}},
url = {http://dx.doi.org/10.1039/c6cc00721j},
volume = 52,
year = 2016
}