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Artificial Intelligence has an exciting future in health care, from streamlining insurance claims, to aiding radiologists, dermatologists, cardiologists and other specialties by enhancing data-based pattern recognition, from providing rapid information and improving efficiency in hospitals to a direct role in the doctor’s office in informing both doctors and patients.
Don’t get me wrong, I have great respect for clinical judgment, creative solutions, and the need to preserve patient privacy. My personal empathy cannot be replaced by a computer voice, no matter how soothing it is. And so AI must work as a kind of co-pilot in the doctor’s office.
There is one area where AI will be an important game changer that hasn’t received nearly enough attention, namely helping to counter shortages of essential medications while at the same time aiding in the development of new drugs and repurposing old ones.
Imagine if AI could help determine availability both in terms of ingredients and final product, as well as which pharmacy has it. (iStock)
Drug shortages are growing, and crucial antibiotics such as amoxicillin (though frequently overprescribed by physicians), remain extremely important. Crucial mental health drugs such as Adderall and Vyvanse and Concerta for ADHD also remain in short supply, which is especially problematic for our teens, many of whom are returning to in person school from restrictive pandemic policies with increasing amounts of anxiety, socialization problems, and learning delays.
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This is not to say that ADHD drugs aren’t also overprescribed, but consider that, according to CDC, over 10% of children and teens ages 6 and up suffer from ADHD, and over 60% require medications. Shortages occur for many reasons, including narrow profit margins as disincentives, lack of sufficient active pharmaceutical ingredients coming from China and India, as well as increased demand.
But imagine if AI was employed by a tool to determine availability both in terms of ingredients, final product, as well as which pharmacy has it and which has the demand but no supply. An extensive use of AI if it decreases cost and improves efficiency on the drug delivery side could even add incentive to bringing drug manufacturing back to the U.S.
Even more exciting is the potential use of AI for drug development. Drug discovery, and the tried and true process of high throughput screening, where different chemicals are used to bombard different protein targets on diseased cells until one is found which works, could be and will be enhanced dramatically by machine learning, where AI can predict toxicity or even comes up with a slightly altered version of a molecule that works better than a previous one. The increased speed and cost savings will be enormous. It won’t replace the need for clinical trials, but it can augment them.
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One of the main reasons that we haven’t seen a new class of antibiotics developed since the late 1980s is that it is hard for a drug manufacturer to justify the billion dollar price tag of developing a new antibiotic when we humans only use it episodically, when we are sick. AI will change all that and make antibiotics easier and much cheaper to develop.
As antibiotics continue to be overused both in animal feed and by physicians mistreating upper respiratory viruses, more resistant bacteria will continue to emerge as they have a survival advantage. AI can help by tracking emerging patterns of resistance and incorporating them into a streamlined process of drug development.
AI as a solution for drug shortages, development and repurposing extends well beyond just antibiotics and ADHD drugs to cancer, obesity, and heart disease treatments and on to all drugs. Side effects, drug interactions, drug indications could all be monitored by AI, amassing a huge data base for doctors like me to use.
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I still remember the days of the Physicians’ Desk Reference that I had to pore through, and the changeover to online sourcing, which was eventually embedded in my Electronic Health Records program, was a big improvement in health care. AI will take this process several exponential steps beyond EHR.
It won’t be long before the next cancer cure or treatment for Alzheimer’s comes from an advanced machine trying out different chemical formulas until the right one is found. Don’t worry, physician/scientists will still take the helm after that. We need to embrace this new reality, not resist it. I know I am already embracing it.
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