How liquid biopsies, AI, and multi-cancer screening are transforming early diagnosis and patient outcomes

In India, cutting-edge diagnostics are gaining ground in early cancer identification, leveraging advanced technologies like liquid biopsies, multi-gene sequencing, and innovative AI tools. With the rising cancer burden, these progressions are critical for timely and accurate diagnosis, enabling better patient outcomes and improving survival rates.

Liquid biopsies: A non-invasive approach

Biopsies, while viable, are invasive and may not always capture the full genetic landscape of a tumour. Liquid biopsies have arisen as a less invasive, more comprehensive solution by detecting circulating tumour DNA (ctDNA) in the blood. This approach is especially useful for patients where tissue biopsies are not plausible. Today, there are organisations in India that have been at the forefront of developing liquid biopsy tests that offer high responsiveness and accuracy.

Multi-cancer early detection (MCED): Screening across multiple cancer types

India’s healthcare framework is also pushing towards comprehensive cancer screening with multi-cancer early detection (MCED) tests. These tests can simultaneously screen for various tumours using a solitary blood test. MCED innovation, using a machine learning algorithm, detects specific DNA methylation patterns and mutations characteristic of various cancers.

One of the promising advancements is the utilisation of genomic and proteomic innovations to evaluate various diseases, including those that presently need standard screening techniques, like pancreatic and ovarian tumours. 

AI-powered diagnostics: Enhancing accuracy and speed

AI and machine learning are playing a critical role in enhancing diagnostic accuracy. AI algorithms can analyse complex datasets to identify subtle genetic changes, speeding up the diagnostic process and improving precision. Indian healthcare organisations are increasingly adopting AI-powered tools to improve test sensitivity, ensuring the detection of even low-frequency variations. 

The use of AI intelligence in diagnostics is also helping overcome the challenges of false positives and false negatives, which have been a concern with conventional screening methods. This technology integration allows for real-time data analysis, making diagnostics more unique and receptive to the patient’s condition. 

The road ahead: Challenges and opportunities 

Despite the commitment, a few difficulties remain. Implementing next-gen diagnostics on a national scale requires addressing issues connected with cost, framework, and openness. While tests like liquid biopsies and MCED are getting some decent momentum in metropolitan habitats, there is a need to make these headways accessible in country regions, where medical care access is restricted. Efforts to lessen the expense of these technologies through local manufacturing and streamlined testing procedures are already underway, with multiple companies setting up infrastructure to support widespread adoption.

Additionally, the integration of these advancements into the standard medical care framework will require regulatory approvals and standardised protocols to ensure consistent and accurate results. Cooperative efforts between the public authority, private sector, and healthcare providers will be essential to develop guidelines and frameworks that support the safe and effective use of these diagnostic tools across India.