AI helping in early cancer detection via genomics solutions, data analytics

AI plays key role in enhancing early detection, diagnosis, and treatment outcomes

This report has been updated  Indian hospitals are increasingly integrating artificial intelligence (AI) into cancer care which aids in early detection, diagnosis accuracy, personalised treatments, and patient outcomes, according to experts.

 

Strand has partnered with many life sciences companies, including Palisade Bio to apply machine learning algorithms to public datasets, identifying novel biomarkers for ulcerative colitis. The company said AI improves early melanoma detection by distinguishing benign from malignant skin lesions. In breast cancer, it streamlines mammogram screenings, reduces errors, and boosts efficiency. AI also predicts patient outcomes and optimises resource allocation for better prognosis.

 

“AI is being increasingly used to vastly reduce the costs and timelines in drug discovery and in treatment planning by aiding tumor characterisation, evaluating therapeutic effects, and enabling data-driven precision oncology. In skin cancer, machine learning (ML) based models could classify skin cancer with an accuracy of 94.2 per cent, with a sensitivity and specificity greater than 90 per cent,” said Swaraj Basu, Principal Bioinformatics Engineer, Strand Life Sciences.

 

 

Basu said AI can reduce radiologists' workload by 30 per cent by improving diagnostic accuracy and patient interactions.

 

Ritika Harjani Hinduja, Consultant - Radiation Oncology, at Mumbai-based P D Hinduja Hospital, said in radiation oncology, some of the tasks done by AI include contouring of normal structures and plan renditions and checks.

 

“Similarly, there are some molecular and precision oncology tests, like Oncotype Dx in breast cancer where data generated from testing of certain receptors and mutations is fed into deep learning systems and we get a recurrence risk score which can guide the need for further treatment in early breast cancer. These are just some instances where machine learning and AI have made their way into cancer,” Hinduja said.

 

Dinesh Madhavan, President of Group Oncology, Apollo Hospitals, highlighted that while AI aids in cancer detection, diagnosis, therapy, and ongoing care, its overall success rate remains uncertain and continues to be questioned.

 

“Success rate is based on the outcome of patients in oncology…. Survival in cancer depends on disease free survival after five years. Though AI helps in early detection, treating more number of customers, and alerts when consultation is needed, still patients should be mindful of their health. The success rate of AI usage in cancer care majorly depends on the conversion rate of the patients. In the last 8 months, we were able to cover about 600 plus patients through the integration of AI,” said Madhavan.   

Technological breakthroughs enable hospitals or clinicians to analyse vast datasets, including radiology scans, pathology images, and electronic health records to identify patterns and insights that might be missed by human assessment. 

 

 In November, Strand launched CancerSpot, a multi-cancer early detection test that complements scans and biopsies. The company is also advancing AI-driven genomics solutions, focusing on Biomedical Text Normalisation and AI platforms for drug target discovery and precision medicine.

 

It has also partnered with life sciences companies like Palisade Bio to apply ML to public datasets, identifying novel biomarkers for ulcerative colitis.

 

“The growing need for AI in cancer care is driven by technological advancements, increasing data availability, and the inherent challenges of cancer management. Sophisticated AI algorithms, combined with access to large datasets, enable deeper insights into complex biological mechanisms and patient behaviors,” Basu said.

 

Human resource constraints, such as the shortage of radiologists and variability in diagnostic accuracy, further emphasise the value of AI in reducing errors, improving scalability, and streamlining workflows,” said Basu.

 

Hinduja noted that major radiation machine vendors like Varian, Electa, and Accuray now feature AI-based auto contouring and plan adaptation in radiation oncology, with HCG using Varian's AI-enabled system. 

 

“The drive for incorporating AI is like any other field. Some works are time-consuming and can be assisted by AI, while physicians pay more attention to advancing research and treatment avenues. AI will never replace the physician but will be an excellent assistant,” Hinduja said. 

 

Apollo has integrated AI in cancer care in pilot mode across two centers in Bengaluru - HSR and Electronic City.

 

“In the next quarter, we are planning to take this beyond these two centers. Currently, we have invested about Rs 4 crore each in AI incorporation. Based on the outcome and improvements, we plan to further invest more in the upcoming fiscal,” said Madhavan. 

 

Apollo has tied up with Accuray India and Varian. Going forward, the hospital chain looks to introduce AI-driven robotic surgeries and monogram services.

 

Last week, HealthCare Global (HCG) partnered with Accenture to apply advanced AI, including Generative AI and deep learning, on multi-omic patient data. This collaboration combines the tech giant’s AI expertise with HCG's oncology insights to enable early cancer detection and treatment.

 

“Today, optimising cancer care necessarily calls for tech-driven advancements in research and academics, especially for ensuring seamless, error-free data collection and streaming,” said BS Ajaikumar, Executive Chairman, Healthcare Global Enterprises.

 

“Given the heterogeneity of tumor genomics and other forms of omics, AI has become integral to precise, personalised medical advancements. AI-powered innovation has activated established drugs in certain tumors, which was not the case previously,” Ajaikumar said.

 

Apollo Hospitals' ‘Health of the Nation 2024’ report, released in April, highlights a concerning rise in cancer cases in India, with projections showing a 13 per cent increase from 1.39 million in 2020 to 1.57 million by 2025.