Onc.ai develops AI models leveraging oncology real-world data, including imaging, EMR, and genomics, to enhance precision oncology. The company's deep learning imaging AI aims to bring clarity to cancer treatment decision-making for medical oncologists. Initial products focus on predicting clinical outcomes in metastatic lung cancer to support pharmaceutical clinical development.
Funding
$31M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
NCFounders
Product
Problem
Oncologists face challenges in optimizing treatment strategies for metastatic lung cancer patients undergoing PD-1 immunotherapy due to the complexity of the disease and variability in patient response. Traditional methods for assessing treatment response may be subjective or lag behind actual disease progression, hindering timely adjustments to treatment plans. The lack of comprehensive real-world data and AI-driven insights further complicates decision-making.
Solution
Onc.AI offers an AI-powered clinical management platform designed to enhance treatment decision-making for metastatic lung cancer patients receiving PD-1 immunotherapy. The platform leverages a large oncology real-world dataset, incorporating diagnostic imaging, EMR data, lab results, and genomics, to generate actionable insights. By applying deep learning to serial CT scans, the platform predicts clinical outcomes and assesses treatment response earlier and more accurately than traditional methods. This enables oncologists to personalize treatment strategies, improve patient outcomes, and fulfill the potential of precision oncology.
Target Audience
The primary users are medical oncologists treating metastatic lung cancer patients with PD-1 immunotherapy, as well as pharmaceutical companies involved in clinical development.
Features
- AI-driven analysis of diagnostic imaging, including deep learning on serial CT scans
- Integration of real-world data from EMR, labs, and genomics for a comprehensive patient profile
- Prediction of clinical outcomes in metastatic lung cancer patients undergoing PD-1 immunotherapy
- Early assessment of treatment response to enable timely adjustments to treatment plans
- Identification of patients who may benefit from alternative treatment strategies
- FDA Breakthrough Device Designation for Serial CT Response Score deep learning model