Browsing by Subject "Prodrugs"

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    Correlating Irinotecan and Capecitabine Treatment for Colorectal Cancer to Gene Expression, Polymorphisms, and Clinical Outcomes
    (2011-03-16) Hinkle, David T., IV.; Harrington, Maureen A.; Chiorean, Elena G.; Sanghani, Sonal P.
    Colorectal cancer is the third most common type of cancer and the third most common cause of cancer-related mortality. There are three types of treatment available to patients, either individually or in combination. Treatments are radiation, chemotherapy, and surgery. In a Phase II clinical trial at IUSM, a multimodality approach was chosen. The patients with locally advanced rectal cancer received preoperative treatment with capecitabine and irinotecan (CPT-11) combination followed by chemoradiation with capecitabine and finally surgery to improve response and decrease local recurrence. Irinotecan and Capecitabine are both prodrugs activated in vivo to SN-38 and 5-FU, respectively. Identification of the molecular markers for 5-FU and Irinotecan efficacy and toxicity is important for the development of more efficient and less toxic treatment strategies for patients with colorectal cancer. The goal of this study was to determine the expression levels of the genes involved in activation and metabolism of capecitabine and irinotecan in pre and post treatment specimens from these patients. The genes quantitated by real-time PCR were carboxylesterase 1 and 2 (CES1 and CES2), thymidylate synthase (TS), β-glucoronidase (β-GUS), thymidine phosphorylase (TP), dihydropyrimidine dehydrogenase (DPD) and topoisomerase I (Topo I). The UGT1A1*28 polymorphism in UDP glucuronosyltransferase 1 is associated with SN-38 toxicity. Therefore, the UGT1A1*28 polymorphism status in patients was determined by PCR-sequencing. Correlative analysis of gene expression and UGT1A1*28 mutation with clinical outcome in this Phase II study was completed.
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    Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization
    (Public Library of Science, 2015) Jayachandran, Devaraj; Laínez-Aguirre, José; Rundell, Ann; Vik, Terry; Hannemann, Robert; Reklaitis, Gintaras; Ramkrishna, Doraiswami; Department of Pediatrics, IU School of Medicine
    6-Mercaptopurine (6-MP) is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN) through enzymatic reaction involving thiopurine methyltransferase (TPMT). Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP's widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype) plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient's ability to metabolize the drug instead of the traditional standard-dose-for-all approach.