How it works

The xCures platform transforms complex unstructured medical data directly from the patient’s medical records into structured data suitable for analysis and machine learning. Our A.I. engine then actively cross-references this data against the vast digital library of oncology data to match patients with potential treatments and predict outcomes. This empowers patients and their oncologists to make more informed and effective treatment decisions.

Creating Useful Data

The xCures platform automatically captures Real-time, Regulatory-grade, Clinical data (RRC) from cancer patients.

Assisted by A.I. the platform aggregates, organizes, and structures medical records into longitudinal datasets that can give patients and oncologists access to the most promising treatment options, while giving researchers access to data that is fully FDA 21 CFR Part 11 compliant, and source data verified.

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The Team: Technology Meets Oncology

To fully integrate cancer research and care, xCures has assembled a multi-disciplinary, boundary-pushing team spanning A.I., data science, and clinical research. The team has solved three of the biggest challenges in applying A.I. to oncology:

1. Medical data processing: We automated mechanisms to get a deep clinical understanding of cancer patients and structure longitudinal data without adding any additional administrative burden to the system.
2. Treatment indexing: We created a living master catalog of all the potential cancer treatments, including individual interventions and combination regimens, expert-sourced medical rationales, and access pathways.
3. Patient-Treatment matching: We developed a suite of tools to match patients to a shortlist of appropriate options using NLP, and rank them using Bayesian predictive models operating on real outcomes data, and expert insights mined from Virtual Tumor Boards.