Abstract
The molecular characterization of patient tumors provides a rational and highly promising approach for guiding oncologists in treatment decision-making. Notwithstanding, genomic medicine still remains in its infancy, with innovators and early adopters continuing to carry a significant portion of the clinical and financial risk. Numerous innovative precision oncology trials have emerged globally to address the associated need for evidence of clinical utility. These studies seek to capitalize on the power of predictive biomarkers and/or treatment decision support analytics, to expeditiously and cost-effectively demonstrate the positive impact of these technologies on drug resistance/response, patient survival, and/or quality of life. Here, we discuss the molecular foundations of these approaches and highlight the diversity of innovative trial strategies that are capitalizing on this emergent knowledge. We conclude that, as increasing volumes of clinico-molecular outcomes data become available, in future, we will begin to transition away from expert systems for treatment decision support (TDS), towards the power of AI-assisted TDS—an evolution that may truly revolutionize the nature and success of cancer patient care.
Highlights
The advent of genomic technologies, such as generation sequencing (NGS), has allowed for industry and academia to increasingly offer products and services that enable physicians to understand the therapeutic implications of patient data, based on the computational analysis of real-time clinical and molecular knowledge
The “Targeted Agent and Profiling Utilization Registry” (TAPUR) Study is a non-randomized open label clinical trial that aims to describe the safety and efficacy of commercially available, targeted anticancer drugs that are prescribed for treatment of patients with advanced cancer, whose tumor harbors a genomic variant that is known to belong to a drug target or to predict sensitivity to a drug
Notwithstanding, the study has shown the feasibility of performing a multi-center phase II trial employing genomic profiling technologies, a fact that, in itself, has been helpful in evolving clinical trial strategy in the field. Each of these preliminary results suggest that, in early clinical trials, matching patients with targeted drugs based on their molecular profile results in (a) longer response times when compared to their prior therapy and (b) higher rates of response, survival, and time to treatment failure as compared to those that were seen in patients treated without molecular matching
Summary
The advent of genomic technologies, such as generation sequencing (NGS), has allowed for industry and academia to increasingly offer products and services that enable physicians to understand the therapeutic implications of patient data, based on the computational analysis of real-time clinical and molecular knowledge While this information-driven approach is widely believed to define the future of cancer patient care, conclusive evidence demonstrating the broad clinical utility of this strategy is still lacking. The result is an environment where innovators continue to accrue significant financial burden and risk, whilst the payers and regulators await the delivery of applicable evidence It is incumbent on pharmaceutical companies, diagnostics companies and providers of decision support analytics, to expeditiously produce the evidence that is required to demonstrate the positive impact of these technologies on patient survival and/or quality of life. We explain the range of actionable biomarker types that can be gleaned from NGS data and highlight some of the key technologies and clinical studies that are helping to clarify the clinical utility of these innovations in evidence-based medicine
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