New funding will help build out a platform designed to detect treatment effects sooner.
Altis Labs has new funding to help give drug makers a better look into how treatments can affect more types of cancer.
The news: The Toronto-based healthtech startup has closed a $25-million USD ($35-million CAD) Series A round to expand its AI-powered prognosis platform for clinical trials. The round was co-led by New York City-based biotech investor OrbiMed and Qiming Venture Partners USA, the US-based branch of Chinese investor Qiming Venture Partners.
Clinical oncology trials rely on endpoints, or outcomes that have to be achieved to prove whether a treatment is effective. Altis claims its flagship AI model, IPRO, can automatically generate survival predictions from radiology scans, allowing drug developers to detect treatment effects earlier and more reliably.
Altis will use the new funding to apply its AI models to more cancer types, deploy with more global biopharmaceutical partners, and help establish AI endpoints as a new standard for oncology trials.
From the source: In one of Altis’s recent lung cancer trials, the IPRO AI model analyzed approximately 10,000 radiology scans and generated prognostic outcome measures for each patient.
According to a post-hoc Johnson & Johnson analysis of the trial, IPRO detected treatment effects missed by traditional endpoint methods 11 months before the primary progression-free survival results (how long a patient lived without the tumour getting worse), and 26 months before the final overall survival results.
The context: Altis co-founder and CEO Felix Baldauf-Lenschen moved from San Francisco to Toronto in 2019 to launch the company because the city has “world-class” AI talent and hospitals, he told BetaKit in 2023 following Altis’ seed round. More than three years later, Altis has built IPRO on what it calls the industry’s largest real-world imaging database, including the associated clinical information and outcomes spanning over 500,000 patient years.
Final thought: Drug developers rely on early endpoints for trial design and portfolio decisions, so they might prematurely discontinue promising treatments or move forward with flawed therapies based on traditional endpoint analysis, according to Altis. If IPRO can provide a more accurate and reproducible prediction like Altis claims, drug makers could find out what treatments are working sooner.
Feature image courtesy Altis Labs.