Accelerating Cancer Trials with Digital Twins

Leveraging artificial intelligence to generate digital twins that accelerate cancer trials.

Project Overview

The Problem

Modern medical advancements and novel drugs have the potential to drastically improve outcomes for patients during treatments for various forms of cancer. Unfortunately, these treatment options are often delayed due to a long and cumbersome trial process.

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

Announced in August 2023,  global biopharmaceutical companies AstraZeneca and Bayer Pharmaceuticals are incorporating predictions from Altis Lab’s computational imaging platform, Nota, into their statistical analyses to quantify treatment effects earlier and more accurately. 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. Read more about AstraZeneca and Bayer’s early access to the AI models via Nota here.



Project Lead

  • AltisCropepd

Project Partners

  • SapienCropped
  • TrilliumCropped
  • UofCCropped
  • bayer small size
  • astrazeneca logo