Discipline: Technology and Engineering
Subcategory: Biomedical Engineering
Marisa Ngbemeneh - Columbia University
Co-Author(s): Christy Pickering, Johns Hopkins University, MD; Feilim Mac Gabhann Ph.D., Johns Hopkins University, MD
Lung adenocarcinoma is a cancer originating in the mucus-producing glands of the lungs, and it causes nearly 1.7 million deaths globally each year. One of the most common first-line treatments for non-small cell lung adenocarcinoma (NSCLA) is bevacizumab (Avastin™), an antibody to Vascular Endothelial Growth Factor (VEGF). VEGF is upregulated in lung tumors and plays a role in their development by stimulating angiogenesis (the growth of new blood vessels). Bevacizumab binds to and inhibits this upregulated VEGF, hindering tumor growth. Despite this well-defined mechanism of action, there is significant variability in patients’ responses to the drug. The aim of this project is to quantify how interpatient variability affects bevacizumab’s pharmacokinetics (how the body affects the drug) and pharmacodynamics (how the drug acts on the body) differently for each patient. Patient variation in gene expression was incorporated into computational simulations of bevacizumab and its targets; these simulations were used to predict patient variation in drug concentration and therapeutic effect. The distribution of gene expression across the patient population was based on real NSCLA patients, using data from The Cancer Genome Atlas (TCGA). We found that variability in gene expression (a key pharmacodynamic factor) has a much larger impact on the predicted therapeutic effect of bevacizumab than variability in the pharmacokinetic factors. Biologically-based computational models like ours may provide insight into how specific patient populations will respond to existing and potential chemotherapy treatments for NSCLA. References: Lu, Jian-Feng et al. “Clinical Pharmacokinetics of Bevacizumab in Patients with Solid Tumors.” Cancer Chemotherapy and Pharmacology, 62 (2008): 779-786. PMC. Kut, C, F Mac Gabhann, and A S Popel. “Where is VEGF in the Body? A Meta-Analysis of VEGF Distribution in Cancer.” British Journal of Cancer 97.7 (2007): 987-985. PMC.Not Submitted
Funder Acknowledgement(s): Funding was provided by an NSF grant to Johns Hopkins University's INBT REU Site.
Faculty Advisor: Feilim Mac Gabhann Ph.D., email@example.com
Role: Under my mentor's guidance, I constructed a pharmacokinetic model for Bevacizumab based on a modified version of the one published by the drug manufacturer, Genentech. Creating this model involved writing MATLAB scripts to produce a robust and biologically-sound model of drug movement. I also extracted information about patient characteristics from The Cancer Genome Atlas and used these patient data distributions to reproduce a sample of virtual patients. Once this sample was fed into the model, I analyzed the changes in drug and target behavior to compare the overall effects of pharmacodynamic and pharmacokinetic variability in patients. Lastly, I also scripted code for the graphs and statistical plots that were used for analysis and on the poster.