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- W2892339085 abstract "e23140 Background: Clinical trial to evaluate the safety and efficacy of an oncology drug candidate in general is a long and expensive process required for regulatory approval in drug development. High failure rates and difficulties to predict the outcome of clinical trials have wasted the resources and hindered the progress to bring more cancer drugs to patients. PDX models have been widely used recently in preclinical efficacy studies of new cancer agents. Comparing with tumor cell line derived xenografts, PDX models showed more similarities to cancer patients in tumor pathological features, molecular changes and drug responses. More importantly, the large number of available PDX models make it feasible to do preclinical tests in large scales which can represent cancer complexity similar to clinical trials with cancer patients. Methods: At GenenDesign, we have established over 1000 PDX tumor models in various cancer types and derived about 200 acquired drug resistance models. In our in house studies, we have tested near 40 treatments with standard of cares (SoCs) and late stage clinical drug candidates either as mono-therapies or combination therapies, and have generated over 3300 drug response datasets. Many tests with targeted drugs are based on cancer gene aberrations as predictive biomarkers. The drug responses were analyzed by Modifying Response Evaluation Criteria in Solid Tumors (mRECIST) method. Results: By comparing the mRECIST scores in mouse trials with results from about two dozens of historical clinical trials at phase 3 or phase 2, we found that there are high correlations in the rates of objective response (OR), stable disease (SD) and progressive disease (PD) between the mouse trials and their counterpart clinical trials. Progression-free survival also showed similar patterns in these analyses. Conclusions: PDX based mouse trials have advantages in flexibility of study design, quickness in testing new drug candidates and direct comparison of multiple drug treatments in the same models. It can provide valuable information on clinical trial outcome prediction and support clinical study design and patient selection." @default.
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- W2892339085 date "2017-05-20" @default.
- W2892339085 modified "2023-09-25" @default.
- W2892339085 title "Evaluation of the correlations between patient-derived xenograft (PDX) model-based mouse trials and cancer patient-based clinical trials." @default.
- W2892339085 doi "https://doi.org/10.1200/jco.2017.35.15_suppl.e23140" @default.
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