Skip to Content
No preview available

Actions

Download Analytics Citations

Export to: EndNote  |  Zotero  |  Mendeley

Collections

This file is not currently in any collections.

Prediction and Preparation of Co-amorphous Phases of a Bislactam [dataset] Open Access

The effectiveness of a partial least squares – discriminant analysis co-amorphous prediction model was tested using a co-amorphous screening data for the dimer of N vinyl(caprolactam) (bisVCap) as co-former with a range of active pharmaceutical ingredients. The prediction model predicted 71% of the systems correctly. An experimental co-amorphous screen was performed with this co-former with 13 different active pharmaceutical ingredients and the results were compared to the prediction model. A total of 85% of the systems correctly predicted. Stability assessments of three co-amorphous systems showed that the prediction model does not provide information on the stability of the co-amorphous material. The model was shown to perform well with small molecules which were different to the training set used to produce it.

Descriptions

Resource type
Dataset
Contributors
Contact person: Steed, Jonathan 1
Editor: Steed, Jonathan 1
Creator: Chambers, Luke 1
Data collector: Chambers, Luke 1
1 Durham University, UK
Funder
Engineering and Physical Sciences Research Council
Ashland
Research methods
Other description
Keyword
Coamorphous phases
Pharmaceuticals
Lactam
Subject
Chemistry, Physical and theoretical
Location
Language
English
Cited in
Identifier
ark:/32150/r2gq67jr208
doi:10.15128/r2gq67jr208
Rights
Creative Commons Attribution 4.0 International (CC BY)

Publisher
Durham University
Date Created
25/04/2022

File Details

Depositor
J.W. Steed
Date Uploaded
Date Modified
25 April 2022, 12:04:52
Audit Status
Audits have not yet been run on this file.
Characterization
File format: zip (ZIP Format)
Mime type: application/zip
File size: 8773059
Last modified: 2022:04:25 11:35:00+01:00
Filename: Coam Data.zip
Original checksum: de58359fa6b6037e542444344418aa3b
Activity of users you follow
User Activity Date