In May, Bangalore-based informatics startup G-KnowMe tied up 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.
Genome sequencing has significantly advanced our understanding of cancer at an individual level. Patient’s tumors carry information that are key to guiding treatment and also provide novel insights. A large amount of scientific information connected to the genetic profile for understanding tumor biology, is published and publicly available to be interpreted by scientists.
However, such information is not always available in a format that is structured for scaling up this process. Streamlining a method to process the available information, compiling and selecting relevant pieces and staying abreast of emerging updates, are major challenges to the adoption of genome sequencing in the clinic.
As genome sequencing costs drastically fall, the line between its usage in clinical research and clinical management of the disease is blurred. The lure to extract maximum patient relevant information is increasing, for better management of the disease.
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
Professor Jean Abraham, Director of the Precision Breast Cancer Institute at the University of Cambridge
“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 the 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 carry information that can personalize treatment plans, predict response or resistance to approved therapies, suggest off-label therapies or relevant clinical trials for a patient, and at the same time identify any inherited basis for the cancer.
“G-KnowMe is leveraging its combined expertise in AI and cancer biology to develop solutions that enable adoption of large panels in clinical management of cancer. While our platform G-KnowMiner is already in use by large diagnostics labs 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”, commented Nimisha Gupta’’, Founder, G-KnowMe.
