In Silico Predictions of the Gastrointestinal Uptake of Macrocycles in Man Using Conformal Prediction Methodology.
Absorption
Dissolution
Machine learning
PBPK
Permeability
Solubility
Journal
Journal of pharmaceutical sciences
ISSN: 1520-6017
Titre abrégé: J Pharm Sci
Pays: United States
ID NLM: 2985195R
Informations de publication
Date de publication:
09 2022
09 2022
Historique:
received:
26
03
2022
revised:
16
05
2022
accepted:
16
05
2022
pubmed:
24
5
2022
medline:
23
8
2022
entrez:
23
5
2022
Statut:
ppublish
Résumé
The gastrointestinal uptake of macrocyclic compounds is not fully understood. Here we applied our previously validated integrated system based on machine learning and conformal prediction to predict the passive fraction absorbed (f
Identifiants
pubmed: 35605685
pii: S0022-3549(22)00211-8
doi: 10.1016/j.xphs.2022.05.010
pii:
doi:
Substances chimiques
Pharmaceutical Preparations
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2614-2619Informations de copyright
Copyright © 2022 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Urban Fagerholm, Sven Hellberg and Ola Spjuth declare shares in Prosilico AB, a Swedish company that develops solutions for human clinical ADME/PK predictions. Ola Spjuth declares shares in Aros Bio AB, a company developing the CPSign software.