Will they co-crystallize?

被引:79
作者
Wicker, Jerome G. P. [1 ]
Crowley, Lorraine M. [2 ]
Robshaw, Oliver [1 ]
Little, Edmund J. [1 ]
Stokes, Stephen P. [2 ]
Cooper, Richard I. [1 ]
Lawrence, Simon E. [2 ]
机构
[1] Chem Res Lab, Chem Crystallog, Mansfield Rd, Oxford, England
[2] Univ Coll Cork, Dept Chem, Synth & Solid Sate Pharmaceut Ctr, Analyt & Biol Chem Res Facil, Cork, Ireland
基金
爱尔兰科学基金会; 英国工程与自然科学研究理事会;
关键词
HYDROGEN-BOND; COCRYSTALS; SALT; PYRIDINE; ACIDS; AREA;
D O I
10.1039/c7ce00587c
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页码:5336 / 5340
页数:5
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