The Precision Cancer Consortium has hired AI-tech firm Massive Bio to help optimize its clinical trial recruitment operations.
The agreement- financial terms of which were not disclosed – will use trial protocols and patient inclusion and exclusion criteria from consortium members in conjunction with Massive Bio’s Deep Learning Clinical Trial Matching System (DLCTMS).
Initially, Massive Bio will design and pilot a trial matching tool for prospectively matching patients through genomic testing and clinical data to a set of selected ongoing biomarker-driven clinical trials within previously defined locations.
PCC and Massive Bio will also explore considerations for larger scale or real-world application for further development.
CEO Selin Kurnaz welcomed the partnership as beneficial for patients, developers and healthcare providers, commenting "We are thrilled to be working with the Precision Cancer Consortium to advance precision oncology through our innovative artificial intelligence (AI) analytics tools.
“With this partnership, we can streamline the process of clinical trial matching and reduce the burden on patients and healthcare systems."
This was echoed by -founder and CMO Arturo Loaiza-Bonilla, who emphasised the ability to use information for multiple sources as core to Massive Bio’s approach.
“Our technology utilizes genomics and clinical data from various platforms to present available intervention options for each patient in order to optimize clinical trial matching by reducing inefficiencies and multiple screenings.”
The PCC is a collaborative initiative to make data-driven precision oncology the new normal for all cancer patients globally, focusing on increasing patient access to targeted NGS testing and tailored interventions.
Current members include is AstraZeneca, Bayer, Eli Lilly & Company, GlaxoSmithKline (GSK), Janssen, Novartis, and Roche.
PCC project lead Yinghui Zhou, predicted the collaboration would be benefit consortium members’ cancer research efforts.
"This collaboration has the potential to address a major challenge in precision oncology and improve patient outcomes. By working together and utilizing a collection of genomics data from multiple sources centralized with the assistance of AI, we can create a valuable scientific resource and optimize the efficiency of clinical trial matching globally and scale."