![\"Parmita\u2019s](\"https:\/\/static.toiimg.com\/thumb\/msid-132894001,imgsize-115362,width-400,height-225,resizemode-4\/parmita-mishra-founder-amp-ceo-precigenetics.jpg\")
<\/div>\n<\/div>\n<\/div>\n<\/section>\n<\/div><\/div>\n<\/div>\nArtificial intelligence has become remarkably good at writing code, generating images and even designing new proteins. Yet when it comes to under-standing what happens inside a living human cell, it is still largely guessing. The problem, according to Parmita Mishra, founder and chief executive of Silicon Valley-based Precigenetics, is not that AI lacks intelligence. It lacks the right data.\u201cYou can give AI as many research papers as you want,\u201d the 27-year-old says. \u201cIt still won\u2019t understand how a drug behaves inside a living cell. Just like a self-driving car can\u2019t learn to drive from traffic manuals alone, AI needs to actually observe biology.\u201d That belief has led Parmita to an unlikely place for a biotechnology company: the semiconductor industry. Her team has borrowed technologies developed over decades for making computer chips and adapted them to watch living human cells respond to medicines in real time. The company believes those observations could eventually become the missing dataset that allows AI to accelerate drug discovery.Parmita grew up in Delhi in a family of doctors before studying computational biology and computer science at the University of Pennsylvania. She says her exposure to hospitals from an early age, coupled with her engineering training, convinced her that biology needed to borrow more from disciplines such as computing and semiconductor engineering.Inspiration, she says, came from Nobel laureate CV Raman. His work on Raman spectroscopy transformed chemistry by showing that when light strikes a material, the way the photons scatter reveals its chemical composition. Today, Raman spectroscopy is routinely used to identify chemicals, drugs and materials.\u201cBut it was never used for living cells,\u201d Parmita says. \u201cPeople used it in chemistry, in pharma quality control, in semiconductors, but not to continuously study living biology. We realised that wasn\u2019t a scientific limitation. It was an engineering problem.\u201dThe team began with a Raman microscope similar to those already used in the semiconductor industry for inspecting materials at extremely high resolution. The first experiments failed almost immediately. \u201cWe literally took one of the semiconductor microscopes and asked ourselves, \u2018What is this missing?\u2019\u201d Parmita recalls. \u201cThe laser was killing the cells. So we asked why. The cells weren\u2019t getting nutrition, oxygen.\u201dEvery problem solved exposed another. The cells also needed carbon dioxide at the same concentration found inside the human body. They needed a constant temperature of 37\u00b0C. They needed nutrients flowing around them, much as blood vessels nourish cells inside the body.\u201cSo we kept solving one engineering problem after another,\u201d she says. Patented microfluidic chip<\/span>The result is a patented microfluidic chip that functions like a miniature life-support system. Parmita describes it as an artificial network of blood vessels and lungs that keeps living cells alive while they are continuously observed under the microscope. Instead of placing cells in a dish, adding a drug and examining them a day later after staining and destroying them, researchers can now watch the drug interacting with living tissue as it happens. The semiconductor influence extends beyond the microscope. The chips themselves are manufactured using techniques borrowed fromchip fabrication.\u201cWe\u2019re just borrowing from the semiconductor industry,\u201d Parmita says. \u201cWe\u2019re not claiming to be Einstein. We\u2019re applied scientists.\u201d She points to photolithography \u2013 the same manufacturing process used to print intricate patterns onto silicon wafers \u2013 as the inspiration for fabricating the tiny channels through which nutrients and medicines flow. Half of Precigenetics\u2019 engineering team comes from semiconductor backgrounds. The company has also borrowed the industry\u2019s philosophy of scaling.In computing, Moore\u2019s Law predicted that chip performance would improve rapidly while costs fell. Drug development, Parmita notes, suffersfrom the opposite phenomenon, known in the pharmaceutical industry as Eroom\u2019s Law, under which discovering new medicines becomesslower and more expensive over time.\u201cI just thought, why not literally copy Moore\u2019s Law? Why not build chips to solve the problem?\u201d she says.Deluge of data<\/span>Watching living cells also produces something the pharma industry has rarely possessed: enormous volumes of data. Every cell can generate between three and ten gigabytes of information every hour, revealing how its chemistry changes as medicines are introduced. Precigenetics aims to build one ofthe world\u2019s largest databases of how living human cells respond to drugs. Parmita likens it to the protein data-bases that enabled breakthroughs such as AlphaFold, except this database would capture cellular behaviour rather than static molecular structures.For now, Precigenetics is focused on laying the foundations. The company, backed by prominent investors, operates research laboratories inCalifornia\u2019s Bay Area, where it is developing the platform to study living cells, while its Arizona facility manufactures the microfluidic chips and optical systems. In India, it is establishing a pathology laboratory in Delhi to digitise tissue samples from patients and build datasets that better represent Indian populations.Its initial work is centred on liver toxicity screening and melanoma models, with the longer-term ambition of expanding its platform to other cancers and diseases \u2013 and giving AI the kind of living biological data it has never had before.<\/div>\n