Machine learning driven bioequivalence risk assessment at an early stage of generic drug development

The model was used to develop a bioequivalence risk assessment approach to categorize drugs in early development into high, medium or low risk classes.

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Publication Details

Journal
European Journal of Pharmaceutics and Biopharmaceutics
Published
2024-10-28
DOI
https://doi.org/10.1016/j.ejpb.2024.114553
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.36

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article

Machine learning driven bioequivalence risk assessment at an early stage of generic drug development

Iztok Grabnar, Dejan Krajcar, Dejan Velušček
1 citations
European Journal of Pharmaceutics and Biopharmaceutics
Computational Drug Discovery Methods
0.36
article

Machine learning driven bioequivalence risk assessment at an early stage of generic drug development

Iztok Grabnar, Dejan Krajcar, Dejan Velušček
article en
1 citations

Abstract

The model was used to develop a bioequivalence risk assessment approach to categorize drugs in early development into high, medium or low risk classes.

European Journal of Pharmaceutics and BiopharmaceuticsVol. 205
Sanden (Japan) (JP), University of Ljubljana (SI)
Javna Agencija za Raziskovalno Dejavnost RS
Openalex Percentile: Top 35%
Computational Drug Discovery Methods
0.36
DOIOpen Access PDFOpenAlex
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