Artificial intelligence (AI) is a technology that builds an artificial
system with certain intelligence and uses computer software and hardware
to simulate intelligent human behavior. When combined with drug research
and development, AI can considerably shorten this cycle, improve research
efficiency, and minimize costs. The use of machine learning to discover
novel materials and predict material properties has become a new research
direction. On the basis of the current status of worldwide research
on the combination of AI and crystal form and cocrystal, this mini-review
analyzes and explores the application of AI in polymorphism prediction,
crystal structure analysis, crystal property prediction, cocrystal
former (CCF) screening, cocrystal composition prediction, and cocrystal
formation prediction. This study provides insights into the future
applications of AI in related fields.
Drospirenone (DE) is a fourth-generation
progesterone that has
been widely used in oral contraceptives for women because of its safety
and few side effects in terms of pharmacological activity. A new solvatomorph
(crystal form C) of DE with dimethyl sulfoxide was identified and
characterized for the first time through a thermogravimetry–mass
spectrometry (TG–MS) coupling system. The thermodynamic property
of the new solvatomorph of DE was different from those of most pharmaceutical
solvatomorphs, and it was revealed via the skimmer-type interfaced
TG–MS system and differential scanning calorimetry. This new
solvatomorph and a polymorph of DE obtained without solvent (crystal
form A) were well characterized by X-ray crystallography and vibrational
spectroscopic analysis. Computational studies based on their single-crystal
structures, such as Hirshfeld surface analyses, were used to determine
the intermolecular interactions in the crystal network. The single-crystal
structure of crystal form C of DE was determined and reported for
the first time.
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