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CrystEngComm
Article . 2022 . Peer-reviewed
License: CC BY NC
Data sources: Crossref
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Predicting pharmaceutical crystal morphology using artificial intelligence

Authors: Matthew R. Wilkinson; Uriel Martinez-Hernandez; Laura K. Huggon; Chick C. Wilson; Bernardo Castro Dominguez;

Predicting pharmaceutical crystal morphology using artificial intelligence

Abstract

We present the use of artificial intelligence to predict the morphology of crystallizing active pharmaceutical ingredients, first using publicly available data, and then using our own screening efforts to address the limitations we identified.

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    9
    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
hybrid