Will they co-crystallize?

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Will they co-crystallize?

Wicker, Jerome G. P.; Crowley, Lorraine M.; Robshaw, Oliver; Little, Edmund J.; Stokes, Stephen P.; Cooper, Richard I.; Lawrence, Simon E.
Date: 2017
Copyright: © 2017, The Royal Society of Chemistry. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Material from this article can be used in other publications provided that the correct acknowledgement is given with the reproduced material.
Copyright information: https://creativecommons.org/licenses/by/3.0/
Related: http://pubs.rsc.org/en/Content/ArticleLanding/2017/CE/C7CE00587C#!divAbstract
Citation: Wicker, J. G. P., Crowley, L. M., Robshaw, O., Little, E. J., Stokes, S. P., Cooper, R. I. and Lawrence, S. E. (2017) 'Will they co-crystallize?', CrystEngComm, 19(36), pp. 5336-5340. doi: 10.1039/c7ce00587c
Published Version: 10.1039/c7ce00587c

Abstract:

A data-driven approach to predicting co-crystal formation reduces the number of experiments required to successfully produce new co-crystals. A machine learning algorithm trained on an in-house set of co-crystallization experiments results in a 2.6-fold enrichment of successful co-crystal formation in a ranked list of co-formers, using an unseen set of paracetamol test experiments.

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© 2017, The Royal Society of Chemistry. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Material from this article can be used in other publications provided that the correct acknowledgement is given with the reproduced material. Except where otherwise noted, this item's license is described as © 2017, The Royal Society of Chemistry. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Material from this article can be used in other publications provided that the correct acknowledgement is given with the reproduced material.
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