Multiscale Drug Effects Modeling using Applied Systems Pharmacology

Faculty #23
Discipline: Computer Sciences & Information Management
Subcategory: STEM Research

Lijun Qian - Prairie View A&M University

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Although there have been extensive studies on multiscale modeling of cancer from molecular level to tumor level in the past decade, drug effect modeling has mostly remained at the pharmacokinetics/pharmacodynamics (PK/PD) characterization in modern pharmacotherapy without any multiscale consideration and integration with existing multiscale tumor studies. Thus, there is a need to develop multiscale computational models which cover the divide between organism-level PK/PD model and cell-level biochemical models. In this study, a stochastic hybrid systems model that links the drug efficacy obtained at the cell population level to pathways of interest at the molecular level is proposed and investigated. A simulation study of the proposed model for colon cancer cell line HCT-116 with drug Lapatinib input is carried out and compared with the results from the wet-lab experiments at TGen. The observation is that Lapatinib repressed the cancer cells from proliferating and there exist a slow start for the first 10- 15 hours then a linear segment, and later after 30 hours a saturation in response as equally observed in the experiments at TGen. It is demonstrated the proposed model in silico has potential to aid progress towards integrative personalized medicine, in which we can administer optimal patient-specific nutritional or therapeutic regimen based on the patient’s profiles and drug effects.

Funder Acknowledgement(s): NSF HBCU-UP award 1238918

Faculty Advisor: None Listed,