OSCR

Predicting blood-brain barrier permeability of chemicals by machine learning modeling.

Overview

Authors: Yaroslav Chushak1,2, Teresa R. Sterner1,2, Rebecca A. Clewell1,3
ORCID iDs: Yaroslav Chushak, Teresa R. Sterner
  1. 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson AFB, USA
  2. Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Wright-Patterson AFB, USA
  3. Eagle Integrated Systems, LLC, Wright-Patterson AFB, USA
Institutions: Henry M. Jackson Foundation (United States); United States Air Force Research Laboratory (United States); 711th Human Performance Wing; Wright-Patterson Air Force Base (United States)
Journal: NAM journal, volume 2, article 100121
Dates: received 5 June 2026; accepted 25 July 2026; published online 25 July 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1016/j.namjnl.2026.100121 · PMID 42571363 · PMCID PMC13452279 · OpenAlex W7171111764
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: cellular / molecular (subfield)
Methods: Machine learning, Statistics
Keywords: Blood-brain barrier permeability, Machine learning modeling, Classification and regression models, Important molecular features, Structural alerts
Journal subjects: Full Length Article
Topic: Computational Drug Discovery Methods (Computational Theory and Mathematics, Computer Science), according to OpenAlex
Funding: Air Force Research Laboratory 711th Human Performance Wing (FA8650-21-2-6250); Air Force Research Laboratory
Citations: not cited yet (Europe PMC); 32 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Code

No file of the authors' code could be read here: it is described below, and read at its source.

sourceforge.net/openbabel

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: the link answers
Software Heritage: not checked
Found in: the text, “Dataset collection and preparation”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
At the source: sourceforge.net/projects/openbabel/

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 0 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • no repository, dataset or request procedure was recognized in it

Read it in the paper: doi.org/10.1016/j.namjnl.2026.100121.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 2, 28 September 2026

  • Authors: added Teresa R. Sterner (0000-0003-1163-6947); removed Teresa R. Sterner

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 3 authors, 5 keywords, 2 funders, 32 references.

Cite

This paper

Chushak, Y., Sterner, T. R., & Clewell, R. A. (2026). Predicting blood-brain barrier permeability of chemicals by machine learning modeling. NAM journal, 2, 100121. https://doi.org/10.1016/j.namjnl.2026.100121

BibTeX

@article{chushak2026predicting,
author = {Chushak, Yaroslav and Sterner, Teresa R. and Clewell, Rebecca A.},
title = {{Predicting blood-brain barrier permeability of chemicals by machine learning modeling}},
journal = {NAM journal},
year = {2026},
month = jul,
volume = {2},
pages = {100121},
publisher = {Elsevier},
issn = {3050-6204},
doi = {10.1016/j.namjnl.2026.100121},
url = {https://doi.org/10.1016/j.namjnl.2026.100121},
pmid = {42571363},
pmcid = {PMC13452279}
}

RIS

TY - JOUR
AU - Chushak, Yaroslav
AU - Sterner, Teresa R.
AU - Clewell, Rebecca A.
TI - Predicting blood-brain barrier permeability of chemicals by machine learning modeling
T2 - NAM journal
J2 - NAM J
PY - 2026
DA - 2026/07/25
VL - 2
SP - 100121
SN - 3050-6204
PB - Elsevier
DO - 10.1016/j.namjnl.2026.100121
UR - https://doi.org/10.1016/j.namjnl.2026.100121
LA - en
ER -

CSL-JSON

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"volume": "2",
"page": "100121",
"DOI": "10.1016/j.namjnl.2026.100121",
"PMID": "42571363",
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"ISSN": "3050-6204",
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The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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