Congratulations to Professor Hardik Jeetendra Pandya for receiving a prestigious grant (Point of Care Detection and Diagnosis of Oral Cancer using a Low Cost Imaging Module Enabled by AI) from National Institutes of Health, National Cancer Institute, under the Cancer Detection and Diagnosis Research program.

Dr. Fiona Ginty from GEHTIC is the PI from the USA and Dr. Narayana Subramaniam from SPARSH Hospital is the clinical consultant for this grant.

Total Funding: US$ 2,487,643 (~US$ 2.487 Million)

IISc funds for 5 years: US$ 1,033,756 (~US$ 1.033 Million)

The overall vision of the proposed project is to develop and deploy an affordable automated point-of-care (POC) telecytology platform for oral cancer screening that will reliably establish a diagnosis of oral cancer in the community setting and establish an immediate referral care pathway. Oral cancer is a significant public health problem in India; 77,000 new cases and 52,000 deaths are reported annually, which is approximately one-fourth of global incidences.

Approximately 70% of cases present at an advanced stage, when the probability of cure is very low, and a five-year survival rate is around 20%.

It has been estimated that early diagnosis, with timely and proper treatment, could improve the survival rate by up to 90%. The current ‘gold standard’ of oral cancer screening is a visual inspection of the mouth by trained individuals, followed by a biopsy of suspicious lesions.

However, in India, there is a nine-month delay from the onset of symptoms to diagnosis. Of this, seven months are attributed to delays in the medical pathway. The majority of the population lives in a rural environment, where access to pathology services and expertise is very limited. Without definitive proof of cancer, patients, most of the time, are not eligible for state-run insurance programs for treatment.

The proposed approach comprises a portable system integrated for scanning brush biopsy cytology slides with cloud connectivity to transmit images to pathologists and/or automated diagnosis via a validated algorithm for identifying atypical cells.

The team envisage a prototype with in-built artificial intelligence (AI) algorithms for automated reporting in the field. Dr. Pandya believe this innovative and affordable workflow would expedite diagnosis and provide significantly earlier treatment for oral cancer patients.