G-KnowMe partners with University of Cambridge and NHS for automated cancer genome sequencing

New Delhi: Bangalore-based informatics startup G-KnowMe has joined hands with researchers at the University of Cambridge and the Cambridge University Hospitals NHS Foundation Trust (CUH) to develop an automated workflow for interpreting data from sequencing the entire genome of cancers.

Advancements in genome sequencing have greatly enhanced our understanding of cancer at an individual level. Tumor data holds crucial information guiding treatment decisions and offering novel insights into cancer biology. Despite a wealth of scientific information available on genetic profiles, it often lacks the structure needed for widespread clinical application. Compiling relevant data and staying updated with emerging research poses significant challenges to the clinical adoption of genome sequencing.

“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. But timely interpretation of the data to make informed clinical decisions is the challenge. Clinical interpretation of WGS data for breast cancer patient management will be developed under this collaboration’’, commented Professor Jean Abraham, Director of the Precision Breast Cancer Institute at the University of Cambridge. “To achieve this at scale,” she added, “we need to rely on cutting-edge automation and natural language processing tools powered by artificial intelligence.” 

Tumor profiles derived from genome sequencing offer insights into personalized treatment strategies, therapy response prediction, identification of potential clinical trials, and the detection of inherited cancer risks. Nimisha Gupta, Founder of G-KnowMe, stated, “G-KnowMe is leveraging its combined expertise in AI and cancer biology to develop solutions that enable the adoption of large panels in the clinical management of cancer. 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.”

As the cost of genome sequencing continues to decline, the integration of WGS into clinical practice becomes increasingly feasible. By automating the interpretation process, this partnership aims to harness the full potential of genomic data in improving cancer patient outcomes.