The study aims to evaluate the clinical utility of the xDRIVE functional precision medicine + artificial intelligence (AI) platform in predicting treatment response for metastatic colorectal cancer (mCRC). The primary objective is to assess xDRIVE's accuracy in forecasting clinical benefit from standard-of-care (SOC) therapies, with a target of ≥80% accuracy in 25 participants. Achieving this threshold would provide sufficient statistical power to reject the null hypothesis of ≤50% accuracy. The secondary goal is to determine the feasibility of utilizing xDRIVE for timely treatment recommendations. Success will be defined by the ability to provide recommendations within four weeks for at least 64% of patients, ensuring clinical applicability. Additionally, the study includes an exploratory objective to examine oncologists' perspectives on integrating xDRIVE into clinical decision-making. This will be achieved through a post-hoc survey assessing physician experiences with the precision oncology platform.
Metastatic colorectal cancer (mCRC) remains a critical unmet clinical need, necessitating innovative approaches to improve patient outcomes. Functional precision medicine (FPM)-guided interventions offer the potential to enhance treatment decision-making by tailoring therapies based on individual patient responses. This study aims to evaluate the clinical utility of xDRIVE, a precision oncology platform, in predicting treatment response to standard-of-care (SOC) therapies in patients with advanced colorectal cancer. By integrating cutting-edge biobanking and personalized medicine approaches, the study seeks to determine whether xDRIVE can provide accurate and timely treatment recommendations, ultimately optimizing clinical management for patients with mCRC. The primary objective is to assess the accuracy of xDRIVE in predicting clinical benefit, defined as a complete response, partial response, or stable disease. Success will be determined by achieving at least 80% accuracy in 20 of 25 participants, allowing for rejection of the null hypothesis (≤50% accuracy) with 90% statistical power. A total of 30 participants will be enrolled to ensure robust evaluation. The secondary objective is to evaluate the feasibility of utilizing xDRIVE in a clinically actionable timeframe, with success defined as delivering treatment recommendations within four weeks for at least 64% of cases. This feasibility threshold will allow for rejection of the null hypothesis (≤35% feasibility) with 90% power. Additionally, the study will explore oncologists' perspectives on integrating xDRIVE into clinical decision-making. A post-hoc survey will be conducted to assess physician experiences, providing insights into the potential impact and adoption of precision oncology platforms in routine practice.
Study Type
OBSERVATIONAL
The results of the drug sensitivity assay and genetic screening will be used to inform treating physician about patient-specific drug sensitivity or resistance guiding best therapy choices. Treatment will not be given as part of the study.
Accurate prediction of clinical benefit (complete response, partial response or stable disease) to physician-selected treatment among among enrolled patients with mCRC
The primary objective is to determine the accuracy of clinical benefit prediction by xDRIVE testing in participants with advanced CRC who receive SOC therapies. Response to SOC therapy will be determined by RECIST guidelines, with disease response measured through radiographic imaging. Accurate prediction of RECIST-determined clinical response (complete response, partial response, stable disease, or progressive disease) by xDRIVE tumor in 20 of 25 participants (80%) is sufficient to reject the null hypothesis (≤50% accuracy) with 90% power (α = 0.05). Enrollment will be a total of 30 subjects.
Time frame: Tumor measurements will be taken at baseline before treatment and at the first post-treatment scan. RECIST will be used to assess response. Outcomes will be tracked for the duration of the study, up to one year.
Feasibility of returning xDRIVE functional precision medicine data in a clinically-actionable timeframe
The secondary objective is to determine the feasibility of using xDRIVE to provide treatment recommendation in a clinically-actionable timeframe. Feasibility will be demonstrated if treatment recommendations are returned within 4 weeks for at least 16 of 25 patients (64%), which is sufficient to reject the null hypothesis (≤35% treatment recommendations) with 90% power (α = 0.05).
Time frame: Timeframe for successful return of data is within 4 weeks. Previous studies have demonstrated a median 10-day turnaround time.
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