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PreprintLicence not statedChemRxiv

Predicting CYP450 Induction and PXR Activation with Machine Learning Approaches: Challenges and Opportunities

  • Markus Orsi1,2
  • Anton Thieme1,2
  • Matteo Gätzner1,2
  • Nicolò Milani1,2
  • Joe Napoli3
  • Michael Reutlinger1,2
  • Kenichi Umehara1,2
  • Johannes Kirchmair4,5
  • Andrea Andrews-Morger1,2
  • Jamie Clifton1,2
5 affiliations
  1. 1Roche Innovation Center
  2. 2F. Hoffmann-La Roche
  3. 3Drug Metabolism & Pharmacokinetics (DMPK, Genentech, Inc., 1 DNA Way, South San Francisco, California, 94080
  4. 4Faculty of Life Sciences
  5. 5University of Vienna
Open at sourceDOICite

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Cite

BibTeXRIS
BibTeX
@misc{orsi2026predicting,
  title = {{Predicting CYP450 Induction and PXR Activation with Machine Learning Approaches: Challenges and Opportunities}},
  author = {Markus Orsi and Anton Thieme and Matteo Gätzner and Nicolò Milani and Joe Napoli and Michael Reutlinger and Kenichi Umehara and Johannes Kirchmair and Andrea Andrews-Morger and Jamie Clifton},
  howpublished = {ChemRxiv},
  year = {2026},
  month = aug,
  doi = {10.26434/chemrxiv.15006350/v2},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15006350/v2},
}
RIS
TY  - UNPB
TI  - Predicting CYP450 Induction and PXR Activation with Machine Learning Approaches: Challenges and Opportunities
AU  - Markus Orsi
AU  - Anton Thieme
AU  - Matteo Gätzner
AU  - Nicolò Milani
AU  - Joe Napoli
AU  - Michael Reutlinger
AU  - Kenichi Umehara
AU  - Johannes Kirchmair
AU  - Andrea Andrews-Morger
AU  - Jamie Clifton
PY  - 2026
DA  - 2026/08/31
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15006350/v2
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15006350/v2
ER  -