| Literature DB >> 26423340 |
Hideaki Bando1, Naoko Takebe2.
Abstract
Exciting recent advancements in deep-sequencing technology have enabled a rapid and cost-effective molecular characterization of patient-derived tumor samples. Incorporating these innovative diagnostic technologies into early clinical trials could significantly propel implementation of precision medicine by identifying genetic markers predictive of sensitivity to agents. It may also markedly accelerate drug development and subsequent regulatory approval of novel agents. Particularly noteworthy, a high-response rate in a Phase II trial involving a biomarker-enriched patient cohort could result in a regulatory treatment approval in rare histologies, which otherwise would not be a candidate for a large randomized clinical trial. Furthermore, even if a trial does not meet its statistical endpoint, tumors from a few responders should be molecularly characterized as part of the new biomarker-mining processes. In order to accommodate patient screening and accelerate the accrual process, institutions conducting early clinical trials need to be a part of a multi-institution clinical trials network. Future clinical trial design will incorporate new biomarkers discovered by a 'phenotype-to-genotype' effort with an appropriate statistical design. To help advance such changes, the National Cancer Institute has recently reformed the existing early phase clinical trials network. A new clinical trial network, the Experimental Therapeutics Clinical Trials Network (ET-CTN), was begun and, in addition to its pre-existing infrastructure, an up-to-date clinical trial registration system, clinical trial monitoring system including electronic database and a central Institutional Review Board were formed. Ultimately, these reforms support identifying the most appropriate therapy for each tumor type by incorporating state-of-the-art molecular diagnostic tools into early clinical trials.Entities:
Keywords: Phase I and II clinical trial; clinical trial network; experimental therapeutics; molecular characterization; next-generation sequencing; translational research
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Year: 2015 PMID: 26423340 PMCID: PMC4635628 DOI: 10.1093/jjco/hyv144
Source DB: PubMed Journal: Jpn J Clin Oncol ISSN: 0368-2811 Impact factor: 3.019