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Creators/Authors contains: "Mitra, Joydeep"

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  1. ; ; (, IEEE)
    Free, publicly-accessible full text available February 10, 2026
  2. ; ; (, IEEE)
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  3. ; ; (, IEEE)
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  4. ; ; ; ; (, IEEE Electrification Magazine)
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  5. ; ; ; ; ; ; ; ; ; ; et al (, International Conference on Computer-Aided Design (ICCAD))
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  6. ; ; ; ; (, CrystEngComm)
    null (Ed.)
    An automated application, CoForm, was used for predicting the outcomes of attempted co-crystallizations between two active pharmaceutical ingredients, loratadine and desloratadine, and 41 potential co-formers from the general interest (OGI) list. The predictive abilities of the app were compared to structure-informatics tools based on hydrogen-bond propensity (HBP) and molecular complementarity (MC). The results indicate that CoForm delivered a success rate of 78% for both loratadine and desloratadine compared to 76% and 54%, respectively (HBP), and 39% and 22%, respectively (MC). 
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