Functional Precision Medicine: Combinatorial Immunotherapy via Optim.AI™ 2.0
Current cancer care faces significant challenges due to response variability and a lack of predictive biomarkers for immunotherapy. To address this, the Optim.AI™ 2.0 platform integrates high-content imaging with ex vivo tumor-immune co-cultures to predict patient-specific responses to drug combinations.
Methodology: High-Content Screening
The platform utilizes primary patient samples to create a biological disease model. These samples are co-cultured with peripheral blood mononuclear cells (PBMCs) to simulate the immune environment before drug treatment. Following a 48-to-72-hour incubation with various therapies—including bispecific antibodies and ADCs—high-content screening measures cell viability. This functional readout allows for the ranking of effective combinations.
Clinical Performance in NHL and CRC
The platform has demonstrated high clinical utility in Non-Hodgkin Lymphoma (NHL):
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Sensitivity: 81.8%
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Specificity: 68.0%
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Positive Predictive Value: 89.2%
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Accuracy: 74.5%
In Colorectal Cancer (CRC), Optim.AI™ 2.0 identifies synergistic drug-drug interactions using parabolic response surface maps. These visualizations help prioritize salvage regimens over standard-of-care options by quantifying Normalized Cell Viability (NCV).
Conclusion
Optim.AI™ 2.0 provides a real-world clinical tool for evaluating immunotherapies, particularly for patients lacking actionable molecular biomarkers. By combining functional assays with molecular profiling, clinicians can better identify effective, personalized drug combinations.