Dataset Information
Williams2022 - Permeable compound selection using in vitro ADME data (PAMPA pH 5).
Ontology highlight
ABSTRACT: Parallel Artificial Membrane Permeability is an in vitro surrogate to determine the permeability of drugs across cellular membranes. PAMPA at pH 5 was experimentally determined in a dataset of 5,473 unique compounds by the NIH-NCATS. 50% of the dataset was used to train a classifier (SVM) to predict the permeability of new compounds, and validated on the remaining 50% of the data, rendering an AUC = 0.88. The Peff was converted to logarithmic, log Peff value lower than 2.0 were considered to have low to moderate permeability, and those with a value higher than 2.5 were considered as high-permeability compounds. Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos81ew
ORGANISM(S): Homo sapiens
SUBMITTER: Zainab Ashimiyu-Abdusalam
PROVIDER: MODEL2404220004 | biostudies-other |
SECONDARY ACCESSION(S): 35030421
REPOSITORIES: biostudies-other
Publications
Using in vitro ADME data for lead compound selection: An emphasis on PAMPA pH 5 permeability and oral bioavailability.
Bioorganic & medicinal chemistry 20220105
Membrane permeability plays an important role in oral drug absorption. Caco-2 and Madin-Darby Canine Kidney (MDCK) cell culture systems have been widely used for assessing intestinal permeability. Since most drugs are absorbed passively, Parallel Artificial Membrane Permeability Assay (PAMPA) has gained popularity as a low-cost and high-throughput method in early drug discovery when compared to high-cost, labor intensive cell-based assays. At the National Center for Advancing Translational Scien ...[more]
