Abstract

Empiric selection of drugs has a low rate of success in cancer patients whose treatment options are limited due to previous treatments or have rare cancer types with no standard effective treatment options. Guidance based on the molecular characteristics of the tumour can provide valuable insights for the physician as to which treatments could be beneficial and, conversely, which would be best to avoid. With the advent of rapid, affordable tumour-profiling technologies, many serviEces have been launched which offer patients and physicians this information. However, the field remains relatively unregulated and few services to date have demonstrated that their approach has meaningful clinical utility or clinical benefit with an acceptable cost-effectiveness ratio. In this review, we describe the concept and clinical data supporting the use of one such service, Caris Molecular Intelligence (CMI). Caris have been pioneers in the field of precision medicine for over a decade. Over 120,000 clinical publications describing the predictive nature of biomarkers were reviewed and graded to provide the basis for proprietary software that matches the published evidence with the test results from a multiplatform approach that measures proteins, ribonucleic acid (RNA) and deoxyribonucleic acid (DNA).The CMI results help physicians to select drugs that are more likely to benefit anindividual patient, avoid those drugs that are not likely to work, and provide treatment options that otherwise would not be considered. Globally, over 85,000 patients with over 150 different types of cancer have been profiled with CMI. The Caris approach has shown to be effective in 10 physician-led evaluations, and the results of a prospective observational registry show a significant overall survival benefit in patients treated in line with the report. In over 350 patients treated as part of a CMI evaluation, 75% have been treated based on the report and over 40% of those evaluable had clinical benefit. These outcomes help to illustrate the clinical utility of this approach in helping patients where the next treatment decision is difficult.