AI in healthcare is transforming personalized medicine, diagnostics, and drug discovery
Information is valuable in any profession, and in medicine it can be absolutely vital. Doctors and nurses spend a lot of time poring over charts, learning patient histories, striving to make the right diagnosis and pick the right course of treatment. Drug researchers can spend years or even decades developing medicines. With so many small differences from patient to patient and possible ailments and treatments, they can use a bit of help sifting through all the data. AI in healthcare can personalize care and speed up breakthroughs, which is why it’s set to be a $200 billion industry by the end of the decade.
Every patient is different, and caregivers strive to give each the best care they can. With precision medicine that takes into account an individual’s medical history, genetics, lifestyle, and environment, professionals can personalize patient care to a high degree. Cancer patients especially can benefit from precision medicine, receiving tailored treatments that maximize their odds of survival and minimize their risk of adverse effects.
“Ten years ago, if someone was diagnosed with a virulent form of leukemia, they had a very low chance of survival. There are many different variants of leukemia; without knowing the variant, choosing how to treat it is a gamble,” Renen Hallak, founder and CEO of data storage platform VAST Data, wrote for Forbes. “But now, doctors can sequence DNA, pinpoint which of the myriad variants afflict the individual and immediately get to the correct protocol, increasing their chance for survival dramatically.”
When it comes to prescribing medicine, there are a lot of factors that go into determining the most effective dose. Traditionally, doctors have used age, weight, and sex to determine dosage, but with AI enhancements in pharmacogenomics, they can analyze drug receptors in DNA to decipher an individual’s drug uptake and how well their body will break the drug down. That gets patients the correct dosage with minimal side effects.
Not only can AI in healthcare give professionals a clearer picture of what is happening with their patients, it can clue them in to what’s about to happen. Using much of the same genetic, environmental, and behavioral data, predictive medicine can assess the likelihood of a patient developing a particular disease. It’s especially useful in detecting rare diseases that doctors might not ever think to check for or would take far too much time without the aid of AI. As many diseases are far easier to treat when they are caught early, predictive medicine can lead to better patient outcomes with less expenditure for them and healthcare facilities. It’s an ounce of prevention with a 21st-century flair.
“With ever increasing pressures on healthcare systems, it’s time to ask the question: Where should priorities lie when directing predictive model efforts? There are various considerations to be made when posing this question, including, disease prevalence, life expectancy, cost to the system and patient triaging impacts, to name a few,” Rena Christina Tabata, CEO of ShareSmart, wrote.
One important disease predictive medicine can pay dividends in catching early is dementia. The brain changes that lead to dementia can start decades before a person shows symptoms. An AI tool developed at the Stevens Institute of Technology that analyzes speech patterns has proven to diagnose dementia with 95% accuracy, saving on expensive imaging and a battery of tests.
“This is a real breakthrough,” K.P. Subbalakshmi, founding director of Stevens Institute of Artificial Intelligence, said. “We’re opening an exciting new field of research and making it far easier to explain to patients why the AI came to the conclusion that it did, while diagnosing patients. This addresses the important question of trustability of AI systems in the medical field.”
AI Drug Discovery
Drug discovery and development has always been a game of trial and error. With the help of AI in healthcare, the game is going a lot faster these days.
“We might be able to have drugs in one-tenth of the time, from being discovered to being able to treat patients,” McKinsey’s Alex Devereson said. “Today, many diseases simply have no treatments whatsoever. I think, and I hope, we’re going to see a world where we can generate therapies that can treat those patients very effectively. Fundamentally, we will have life-changing, game-changing drugs — on a scale and at a pace that we’ve never seen before — getting to the right patient at the right time.”
Since 2020, when British startup Exscientia got an AI-designed drug into human clinical trials for the first time, hundreds of AI-led drugs have been in discovery and appeared in dozens of clinical trials. This year, the FDA granted Insilico Medicine the first Orphan Drug Designation for a drug discovered and designed with AI. As AI in healthcare improves, the breakthroughs will only come faster.
“There are billions of decisions needed to find the right molecules and it is a huge decision to precisely engineer a drug,” Exscientia CEO Andrew Hopkins told the BBC. “But the beauty of the algorithm is that they are agnostic, so can be applied to any disease.”