From fear to hope: AI finds a new role in fight against cancer

For years the debate around AI has swung between excitement and anxiety but researchers are now putting this technology to work on humanitys toughest challenge the mysteries of cancerAt the centre of one such effort is Debarka Sengupta associate dean of Innovation Research and Development Indraprastha Institute of Information Technology Delhi IIITDelhi who is using AI and genomics to detect cancer earlier understand how tumours behave and help doctors choose treatments tailored to individual patientsRather than viewing cancer as a single disease or a mutation in one gene Senguptas laboratory studies it as a complex biological system by combining molecular biology genomics singlecell analysis microfluidics and AIThe aim is to detect weak cancer signals that are often hidden in blood tissue or massive biological datasets and turn them into information that doctors can actually use Sengupta told PTITraditionally cancer research has focused on studying one gene or one biomarker at a time AI he explained allows researchers to analyse thousands of genes different cell types and clinical records simultaneously uncovering patterns that would be almost impossible to identify manuallyThe real value of AI is not just speed It helps researchers discover patterns that would be extremely difficult to see manually especially when the signal is distributed across thousands of genes many cell types and multiple experimental systems he saidAmong the teams major achievements is the development of an 11gene blood test based on platelet RNA that could eventually become an affordable screening tool for multiple cancersUnlike expensive genome sequencing technologies the test is designed to work on RTPCR machines the same technology widely deployed across India during the COVID19 pandemicSuch a test could potentially be run in the same kind of qPCRequipped molecular labs that scaled during COVID testing making broad deployment much more practical in India and similar settings Sengupta saidHe added that they have also been working on circulating tumour cell detection in triplenegative breast cancer where the challenge is to find extremely rare cancer cells in the bloodThat work was exciting because it combined molecular biology microfluidics and AI he addedBut detection is only one part of the puzzleThe researcher also focuses on AI models that can predict how individual cancers are likely to respond to different medicines potentially helping doctors move away from the current trialanderror approach to treatmentThrough a startup called GeneSilico the team is building what it calls an Agentic Digital Twin an AIpowered virtual model that combines a patients molecular profile clinical history tumour biology treatment guidelines and scientific literature to help oncologists evaluate possible treatment optionsThe goal is not to replace doctors Sengupta saidIt is to provide them with a deeper evidence layer so they can better understand which therapies appear biologically plausible and which treatment strategies have stronger scientific supportDespite rapid advances Sengupta cautioned that AI is still far from becoming an independent decisionmaker in hospitalsWe are closer than many people think but these technologies need rigorous clinical validation regulatory oversight and careful integration into medical practice he saidSengupta believes India has a unique opportunity because of the molecular testing infrastructure built during the COVID19 pandemic which could eventually support affordable cancer diagnostics if such technologies are successfully translated into clinical useAsked whether AI is sometimes overhyped Sengupta said the technology delivers its greatest value when it helps researchers manage biological complexity rather than attempting to replace cliniciansIn oncology AI should function as a scientific reasoning tool that supports doctors not as a black box making decisions on its own he saidLooking ahead his laboratory plans to further validate bloodbased cancer detection methods and improve AI systems that can predict drug responses using genomic and clinical dataIf these efforts succeed cancer patients a decade from now may no longer rely only on a onetime biopsy reportInstead doctors could continuously update a patients disease profile using blood tests imaging and genetic information allowing treatments to evolve alongside the cancer itselfThe vision is to make cancer care more personalised more evidencebased and ultimately more accessible Sengupta saidThis story has been sourced from a third party syndicated feed agencies Midday accepts no responsibility or liability for its dependability trustworthiness reliability and data of the text Midday managementmiddaycom reserves the sole right to alter delete or remove without notice