Accelerating Cancer Trials with Digital Twins

How We Are Solving It

The Accelerating Cancer Trials with Digital Twins project aims to reduce the prohibitive time, cost and failure rate associated with bringing novel, effective anti-cancer drugs to market. Led by Altis Labs, Inc., the consortium is creating and incorporating digital twin models in cancer trials to facilitate earlier and more accurate measurements of drug efficacy that can be used within a created software platform to provide more accurate and cost effective clinical trials and better treatment decisions for individual cancer patients.

Canadian cancer centers will benefit from their fragmented clinical data being curated into the world’s largest and richest cancer imaging dataset, which will attract leading researchers and result in significant new IP, as well as high-impact publications. They will further benefit from Altis’ commercialization of digital twin software through negotiated licensing terms. Additionally, oncologists will gain access to novel technologies to inform treatment decisions and Canadian cancer patients will benefit from personalized care and novel, efficacious treatments.

The Result

Altis Lab’s computational imaging platform, Nota, is helping to accelerate cancer trials with digital twins; reducing the prohibitive time, cost and failure rate associated with bringing novel, effective anti-cancer drugs to market. Notably, this project successfully collated the world’s largest cancer imaging database, enabling measuring drug efficacy in clinical trials to be done earlier, more accurately and with greater cost-effectiveness that ultimately enable better treatment decisions for individual cancer patients. Altis developed and validated prognostic models for non-small cell lung cancer (NSCLC) and colorectal (CRC) patients, which outperformed existing tumor-size measurements that have been historically used as the basis for treatment response and regulatory approval.

In 2023, global biopharmaceutical companies AstraZeneca and Bayer Pharmaceuticals joined the collaboration to incorporate predictions from the initial early solution into their statistical analyses to quantify treatment effects. Through being able to manage and automatically analyze imaging data from past and current clinical trials using prognostic AI models, clinical development teams are able to use these AI models to predict disease progression for each patient enrolled in their clinical trial, generating a computational control arm of digital twins. This ultimately enables prioritization of their most promising drug candidates to increase probability of late-stage success and reduce time to market.

Altis was additionally able to leverage the support from this project to raise its seed financing round of $8.2M CAD and to lead a new pan-Canadian coalition to develop and commercialize imaging biomarkers using deep learning.