Analyzing pathway design from drug perturbation experiments

Noah Berlow, Ranadip Pal, Lara Davis, Charles Keller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Drugs that target specific kinases are becoming common in cancer research. In this article, we analyze the design of a modeling approach for drug sensitivity prediction and combination targeted therapy design based on drug perturbation experiments. We consider a target inhibition map model that predicts the tumor sensitivities for all possible combination of target inhibitions. The estimation of the model is based on experimental sensitivity data for multiple target inhibitory drugs. The target inhibition map model provides a steady-state snapshot of the underlying dynamical model. To analyze the robustness of the combination therapy design approach, we consider the inverse problem of possible dynamic models that can generate the target inhibition map model and their transient and steady state response to drugs. We showed that the knowledge of the steady state target inhibition map can be used to estimate the directional pathway using a small number of steady state target expression measurements.

Original languageEnglish
Title of host publication2012 IEEE Statistical Signal Processing Workshop, SSP 2012
Pages552-555
Number of pages4
DOIs
StatePublished - 2012
Event2012 IEEE Statistical Signal Processing Workshop, SSP 2012 - Ann Arbor, MI, United States
Duration: Aug 5 2012Aug 8 2012

Publication series

Name2012 IEEE Statistical Signal Processing Workshop, SSP 2012

Conference

Conference2012 IEEE Statistical Signal Processing Workshop, SSP 2012
CountryUnited States
CityAnn Arbor, MI
Period08/5/1208/8/12

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