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Proactive identification of candidates for newly approved targeted therapies using a clinical decision support program

Year: 2026
Type: article
Abstract: BACKGROUND: Comprehensive molecular profiling (CMP) enables identification of multiple biomarkers from a single sample to inform targeted therapy selection. However, the static nature of test reports limits their clinical relevance as new therapies emerge. Based on the presence of molecular alterations, the population of patients qualifying for FDA-approved therapies nearly doubled since 2017, while FDA-recognized biomarkers of drug response quadrupled. Lookback programs are clinical decision support services designed to notify clinicians when previously profiled patients become candidates for new targeted therapies based on original test results. This study describes biomarkers assessed in a lookback program and summarizes identification of patients who become candidates for novel treatment options following new FDA approvals. MATERIALS AND METHODS: Between 2018 and 2025, tumor samples were submitted to Caris Life Sciences for whole-exome sequencing, whole-transcriptome sequencing, and immunohistochemistry. With new biomarker-directed approvals, the support tool is prompted to evaluate indications as candidates for lookbacks. For approved candidates, molecular profiles from the database are retrospectively assessed for relevant biomarker status within disease-site context. After evaluation, a molecular scientist sends standardized communication informing oncologists of potential candidates for the new therapy. RESULTS: Since 2018, 87 biomarker-directed FDA approvals were evaluated for the lookback program. Among 483 000 molecular profiles, 13 293 patients were identified as candidates for newly approved agents in ten distinct tumor types and several tumor-agnostic indications. CONCLUSIONS: By coupling CMP with continuous evidence surveillance and proactive provider clinician engagement, lookback programs potentially close the gap between therapeutic innovation and clinical application by providing timely information about emerging targeted therapies.
Language: English
Subfield: Cancer Research
Open Access status: gold
Estimated APC paid: $3,852
OpenAlex ID: W7159117265
FWCI:
Cites: 18
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