Computational Modeling of Drug Response Identifies Mutant-Specific Constraints for Dosing panRAF and MEK Inhibitors in Melanoma
Leveraging pre-clinical data and computational modeling, our approach proposes dosage strategies that can optimize synergy in drug combinations, while also bringing forth the real-world challenges of staying within a precise dose range. Overall, this work presents a framework to aid dose selection in drug combinations.
Authors
- Logan Brooks (ORCID: https://orcid.org/0000-0003-0877-4978)
- Luca Gerosa (ORCID: https://orcid.org/0000-0001-6805-9410)
- Scott A. Foster (ORCID: https://orcid.org/0000-0002-2773-7999)
- Eva Lin
- Purushottam D. Dixit (ORCID: https://orcid.org/0000-0003-3282-0866)
- Andrew Goetz
- Bartosz Czech (ORCID: https://orcid.org/0000-0002-9908-3007)
- Rana Mroue
- Darlene Dela Cruz
- Scott E. Martin (ORCID: https://orcid.org/0000-0001-5685-9787)
- Fergus Shanahan (ORCID: https://orcid.org/0000-0003-0467-0936)
- Thomas Hunsaker (ORCID: https://orcid.org/0000-0001-7665-747X)
- Udi Segal
Institutions
- Yale University (US)
- Simulation Technologies (United States) (US)
Publication Details
- Journal
- Cancers
- Published
- 2024-08-22
- DOI
- https://doi.org/10.3390/cancers16162914
- Citations
- 1
- Primary Topic
- Melanoma and MAPK Pathways
- Type
- article
- Field-Weighted Citation Impact
- 0.23
Funders
- National Institutes of Health
- Genentech