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AI Case Study

BERG is developing targeted cancer drugs using machine learning with promising Phase I study results

BERG has developed a platform to swiftly analyze patient biology and identify biomarkers using machine learning. Their platform was used in Phase I study to identify patients more likely to benefit from the medicine, applying a precision medicine approach. They have used the platform to develop a new cancer drug and reduce chemotherapy-induced alopecia.

Industry

Healthcare

Pharmaceuticals And Biotech

Project Overview

"BERG will be presenting interim data from its ongoing Phase I study of BPM 31510 (IV) in advanced solid tumors, which demonstrates the promise of metabolically-driven therapy by reversing the Warburg phenotype in cancer. BPM 31510 (IV) is one of the first cancer drugs guided in development by artificial intelligence. BPM 31510 (IV) appears to reverse the compromised metabolism of cancer cells which normalizes the cancer microenvironment to induce cell death. BERG’s Interrogative Biology®platform was used in its BPM 31510 (IV) Phase I study to discover molecular markers identifying patients more likely to have clinical benefit to the treatment applying a precision medicine approach to the trial."
"BERG will also release data from its Phase I trial for its topical calcitriol, BPM 31543 for the prevention of chemotherapy-induced alopecia. Many cancer patients that are treated by chemotherapy encounter hair loss or alopecia as a major side effect, which can lead to significant psychosocial and quality of life issues. BERG’s topical compound BPM 31543 was developed to reduce chemotherapy-induced alopecia, and the data presented from the Phase I safety study shows that the topical compound is safe and well tolerated by patients with initial signs of efficacy."

Reported Results

Promising Phase 1 drug trial results indicating that targeted approach cuts time to drug discovery drastically

Technology

Function

R And D

Product Development

Background

Using AI to discover molecular markers identifying patients more likely to have clinical benefit to the treatment can reduce time taken to conduct research and trial

Benefits

Cost - Targeted Trials/ Precision testing

Data

Genome, proteome, lipidome and metabolome data
Trillions of data points from each sample

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