For biology-driven, informed decision-making
Identifying patients who will benefit from immunotherapy is still a major challenge in clinical oncology. Most patients do not respond to these anti-cancer treatments, and some even display progression of disease while on treatment. The average response rate is in the range of 20%; That is, approximately 1 in 5 patients respond positively to the treatment.
To avoid unnecessary treatment, delays in administration, adverse reactions and/or unnecessary costs, it is important to identify, in advance, patients who will respond to their proposed treatment plan. For some treatments, biomarkers can help predict whether the patient will respond or not. But strong biomarkers are lacking for many cancer therapies, specifically for immunotherapy.
Studies conducted in the laboratory of Prof. Yuval Shaked at the Technion, Israel Institute of Technology, have shown that the body has a biological reaction to any administered anti-cancer treatment, including immunotherapy, chemotherapy, radiation, surgery, and targeted drugs. We call this the “host response,” where many different biological compounds that may interfere with the treatment’s proper function are secreted into the bloodstream.
PROphet® is a proprietary plasma-based proteomic pattern recognition tool that combines system biology, bioinformatics, and machine learning to support clinical decision-making. Requiring just one pre-treatment blood test for analysis, the platform identifies expression patterns in a panel of approximately 7,000 proteins and assigns a PROphet® score, a clinically validated metric reflecting the patient's likelihood of clinical benefit (CB).
By analyzing thousands of protein features, PROphet®’s proteomic pattern recognition enables physicians to make educated decisions and improve each patient's overall survival by providing personalized treatment plans. This approach allows for a deeper level of personalization, guiding the selection of the most effective therapy based on the patient's unique biology.
Our use of proteomic pattern recognition allows clinicians to identify whether a patient should be treated with immunotherapy alone or in combination with chemotherapy, leading to more precise decision-making and reducing the administration of unnecessary therapies.
The PROphet® algorithm is trained and validated on our large-scale clinical trial, PROPHETIC (NCT04056247). To date, the trial has over 1,700 patients recruited across 40 sites worldwide, making it one of the largest prospective cohorts in the precision oncology field. Indication-agnostic in nature, the PROphet® platform allows for multiple test indications, with its initial offering for late-stage non-small cell lung cancer (NSCLC) patients.
Pre-treatment blood test
High-throughput proteomic assay
Bioinformatics and machine learning
Evading growth suppressors
Tumor promoting inflammation
Genome instability and mutation
Invasion and metastasis
Avoiding immune destruction