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Will they co-crystallize?†
CrystEngComm ( IF 2.6 ) Pub Date : 2017-07-05 00:00:00 , DOI: 10.1039/c7ce00587c
Jerome G. P. Wicker 1, 2, 3, 4 , Lorraine M. Crowley 5, 6, 7, 8, 9 , Oliver Robshaw 1, 2, 3, 4 , Edmund J. Little 1, 2, 3, 4 , Stephen P. Stokes 5, 6, 7, 8, 9 , Richard I. Cooper 1, 2, 3, 4 , Simon E. Lawrence 5, 6, 7, 8, 9
Affiliation  

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.

中文翻译:

他们会共结晶吗?

预测共晶形成的数据驱动方法减少了成功生产新共晶所需的实验次数。使用内部对乙酰氨基酚测试实验集,在内部共结晶实验集上训练的机器学习算法可在成功排名的共形成者列表中将成功的共晶体形成富集2.6倍。
更新日期:2017-07-05
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