Altis utilizes AI models trained on the world's largest cancer imaging database to predict drug efficacy from CT scans, enhancing the accuracy of patient outcome forecasts. This technology accelerates clinical trial processes for biopharma companies by providing actionable insights into imaging data.
Funding
$7.3M 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.
Founders
Product
Problem
Pharmaceutical companies face challenges in accurately predicting drug efficacy during clinical trials, leading to increased costs and prolonged development timelines. Traditional methods of assessing treatment response from CT scans can be subjective and lack the precision needed for optimal patient outcome forecasts.
Solution
Altis offers an AI-powered software solution that analyzes CT scans to predict drug efficacy and patient outcomes, thereby accelerating clinical research and development. The platform leverages AI models trained on a large cancer imaging database to identify subtle patterns and biomarkers indicative of treatment response. By providing quantitative, imaging-based prognostication (IPRO), Altis enables biopharma companies to gain actionable insights from imaging data, optimize trial design, and identify patients most likely to benefit from specific therapies. The technology aims to improve the accuracy of patient outcome forecasts, reduce the time and cost associated with clinical trials, and ultimately enhance the development of effective cancer treatments.
Target Audience
The primary target audience includes biopharmaceutical companies conducting oncology clinical trials and clinical sites involved in medical imaging research.
Features
- AI models trained on a large, curated database of cancer imaging data
- Quantitative analysis of CT scans to identify predictive biomarkers
- Imaging-based prognostication (IPRO) for predicting patient outcomes
- Web-based interface for visualizing and interpreting AI-driven insights
- Integration with existing clinical trial workflows and data management systems
- Secure and compliant data handling to protect patient privacy