BLR-based G-KnowMe Teams Up with Cambridge for Cancer Genome Interpretation

This collaboration aims to develop an efficient workflow to support personalized cancer care.

Bengaluru-based informatics startup G-KnowMe has partnered with researchers at the University of Cambridge and Cambridge University Hospitals NHS Foundation Trust (CUH) in the UK to automate the clinical interpretation of whole genome sequencing (WGS) data for cancer treatment. 

Founded in 2020 by Nimisha Gupta, G-KnowMe is a DeepTech startup focusing on digital healthcare, diagnostics, and life sciences. 

The startup, formerly known as OmDisha Healthcare Technologies, utilizes advanced informatics and molecular assays to create solutions for diagnostic labs, bio-repositories, and patient management systems. 

This collaboration aims to develop an efficient workflow to support personalized cancer care.

G-KnowMiner, G-KnowMe's flagship platform, supports the development of web and mobile solutions using optical character recognition (OCR), natural language processing (NLP), ML, and AI for data analysis and management.

Interpreting Whole Genome Sequencing Data

Whole genome sequencing is becoming increasingly important in cancer management as next-generation sequencing (NGS) technology evolves and the cost of sequencing decreases. 

However, the timely interpretation of this data remains a significant challenge.

Prof Jean Abraham, director of the Precision Breast Cancer Institute at the University of Cambridge, said, "Whole genome sequencing (WGS) of cancers is emerging as the new paradigm in cancer management as Next-Generation Sequencing (NGS) technology scales and the cost of sequencing drops. However, timely interpretation of the data to make informed clinical decisions is the challenge."

He further highlighted the need for advanced tools by saying that to achieve this at scale; there is a reliance on advanced automation and natural language processing tools powered by artificial intelligence.

AI & Genomics for Personalized Cancer Treatment

The partnership aims to leverage AI and genomics to personalize cancer treatment plans, predict responses to approved therapies, and identify suitable clinical trials. 

Tumor profiles contain valuable information that can help tailor treatments to individual patients and uncover inherited cancer risks.

Sharing insights, Nimisha Gupta, founder, G-KnowMe, said, "While our platform, G-KnowMiner, is already in use by large diagnostics labs in the Indian market to interpret data from NGS panels used for cancer diagnostics, expanding its scope to interpreting WGS data within a clinically relevant time frame is what we aim to achieve through this partnership."

Advancements in Cancer Drug Response Prediction

In a related development, researchers at the National Institutes of Health (NIH) introduced an AI tool capable of predicting cancer drug responses using data from individual cells within tumors. 

This study, published in Nature Cancer on April 18, 2024, by the National Cancer Institute (NCI), suggests that this approach could enhance cancer treatment by more precisely matching patients with effective drugs.

Current methods for matching patients to drugs rely on bulk sequencing of tumor DNA and RNA, which averages genetic data from all cells within a tumor sample. 

This approach can miss essential variations among different cell types, including subpopulations that may respond differently to treatments. 

Single-cell RNA sequencing offers high-resolution data at the individual cell level, providing insights into the genetic profiles of various cell clones within tumors. This technology can potentially improve drug targeting but faces challenges due to its high cost and limited availability in clinical settings.