Target receptor identification and subsequent treatment of resected brain tumors with encapsulated and engineered allogeneic stem cells.

Cellular therapies offer a promising therapeutic strategy for the highly malignant brain tumor, glioblastoma (GBM). However, their clinical translation is limited by the lack of effective target identification and stringent testing in pre-clinical models that replicate standard treatment in GBM patients. In this study, we show the detection of cell surface death receptor (DR) target on CD146-enriched circulating tumor cells (CTC) captured from the blood of mice bearing GBM and patients diagnosed with GBM. Next, we developed allogeneic "off-the-shelf" clinical-grade bifunctional mesenchymal stem cells (MSCBif) expressing DR-targeted ligand and a safety kill switch. We show that biodegradable hydrogel encapsulated MSCBif (EnMSCBif) has a profound therapeutic efficacy in mice bearing patient-derived invasive, primary and recurrent GBM tumors following surgical resection. Activation of the kill switch enhances the efficacy of MSCBif and results in their elimination post-tumor treatment which can be tracked by positron emission tomography (PET) imaging. This study establishes a foundation towards a clinical trial of EnMSCBif in primary and recurrent GBM patients.

A framework to evaluate the economic impact of pharmacogenomics.

INTRODUCTION: Pharmacogenomics and personalized medicine promise to improve healthcare by increasing drug efficacy and minimizing side effects. There may also be substantial savings realized by eliminating costs associated with failed treatment. This paper describes a framework using health claims data for analyzing the potential value of pharmacogenomic testing in clinical practice. METHODS: We evaluated a model of alternate clinical strategies using asthma patients' data from a retrospective health claims database to determine a potential cost offset. We estimated the likely cost impact of using a hypothetical pharmacogenomic test to determine a preferred initial therapy. We compared the annualized per patient costs distributions under two clinical strategies: testing all patients for a nonresponse genotype prior to treating and testing none. RESULTS: In the Test All strategy, more patients fall into lower cost ranges of the distribution. In our base case (15% phenotype prevalence, 200 US dollars test, 74% overall first-line treatment efficacy and 60% second-line therapy efficacy) the cost savings per patient for a typical run of the testing strategy simulation ranged from 200 US dollars to 767 US dollars (5th and 95th percentile). Genetic variant prevalence, test cost and the cost of choosing the wrong treatment are key parameters in the economic viability of pharmacogenomics in clinical practice. CONCLUSIONS: A general tool for predicting the impact of pharmacogenomic-based diagnostic tests on healthcare costs in asthma patients suggests that upfront testing costs are likely offset by avoided nonresponse costs. We suggest that similar analyses for decision making could be undertaken using claims data in which a population can be stratified by response to a drug.