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24 April 2024 |
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Article overview
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Dose-response modeling in high-throughput cancer drug screenings: A case study with recommendations for practitioners | | Wesley Tansey
; Kathy Li
; Haoran Zhang
; Scott W. Linderman
; Raul Rabadan
; David M. Blei
; Chris H. Wiggins
; | | Date: |
13 Dec 2018 | | Abstract: | Personalized cancer treatments based on the molecular profile of a patient’s
tumor are becoming a standard of care in oncology. Experimentalists and
pharmacologists rely on high-throughput, extit{in vitro} screenings of many
compounds against many different cell lines to build models of drug response.
These models help them discover new potential therapeutics that may apply to
broad classes of tumors matching some molecular pattern. We propose a
hierarchical Bayesian model of how cancer cell lines respond to drugs in these
experiments and develop a method for fitting the model to real-world data.
Through a case study, the model is shown both quantitatively and qualitatively
to capture nontrivial associations between molecular features and drug
response. Finally, we draw five conclusions and recommendations that may
benefit experimentalists, analysts, and clinicians working in the field of
personalized medicine for cancer therapeutics. | | Source: | arXiv, 1812.5691 | | Services: | Forum | Review | PDF | Favorites | |
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