The growing number of anti-cancer drugs available at different stages of clinical development combined with the broadening potential use of combination therapy further complexifies the identification of indications for drug combinations.
Well characterized patient derived xenograft mouse models (PDX) as produced by the IMODI consortium, combined with Artificial Intelligence tools that can integrate and analyze the broad range of generated data can help address this challenge. PDX experiments can provide an opportunity to simulate a clinical assessment using multiple mice models.
In this study, a PDX platform combined with Ariana Pharma’s KEM® Artificial Intelligence data analytics, was used to simulate a clinical trial and identify biomarkers of response.
mRECIST response and survival of respectively 21 and 26 PDXs against Oxalipaltin combined with 5-Fluorouracil and folinic acid (folfox) were assessed against a placebo, simulating a clinical trial–like setting with 2 arms. Biomarkers of response and survival were identified using KEM®.
24 candidate biomarker genes were identified. Alone or combined, these biomarkers are significantly linked to an increase or decrease of the survival PDX, with the potential to be used as inclusion or exclusion biomarkers.
This work demonstrates the ability of our combined PDX / Artificial Intelligence platform to simulate clinical trials and identify biomarkers of drug efficacy and synergy, thus fostering the design of precision medicine clinical trials.