the coronavirus pandemic has caused the shortage of the antidepressant drug zoloft
Steve Buissinne – Pixabay
It’s almost impossible to read or listen to the news without hearing about the most recent shortage of Adderall — the most commonly prescribed drug for the treatment of Attention Deficit Hyperactivity Disorder (ADHD) in the United States — which started more than seven months ago and has been negatively impacting patients ever since.
This isn’t the first time that Adderall has seen a shortage — in no small part due to ongoing regulatory and supply chain issues. More disturbingly, it’s far from being the only drug shortage in America right now, despite the fact it’s taken center stage with the media since October of last year.
There are currently around 1,450 pharmaceutical products experiencing shortages in the United States today, according to the Food and Drug Administration (FDA). Among these shortages are some critical types of chemotherapy drugs. And while this problem can’t be boiled down to just one area of failure, it certainly begs the question: Are there enough alternatives available, and could artificial intelligence help to fill the gap in medication availability?
Finding a permanent solution for the drug shortages we’re facing in America first means getting to the heart of the matter. In the case of Adderall, the shortage is caused by a combination of regulatory restrictions, supply chain issues, formulation considerations and capacity-building failures.
Chemotherapy drugs, such as cisplatin — used in the treatment of ovarian, testicular, bladder, lung, cervical and head and neck cancer — and carboplatin, are experiencing shortages mostly due to issues with capacity building within the biopharmaceutical industry. What this means is that there simply aren’t enough manufacturers to fill gaps when one fails.
To make matters worse, when drugs are in short supply, doctors and pharmacies are forced to prioritize who receives treatment, meaning that potentially hundreds of thousands of patients will be de-prioritized and labeled as no longer eligible to receive life-saving cancer treatments. Including cisplatin and carboplatin, there are 11 oncology medications in short supply.
In a perfect world, the answer would simply be to produce more. So far, that hasn’t stopped the shortage of chemotherapy drugs, Adderall or any other drug that is, or has been, in short supply. And it won’t keep it from happening again, either. That’s because while the immediate problem is immediate access, the looming problem is the fact that there aren’t enough medication options for patients and providers to choose from.
The primary reason there are so few medications available to patients in the United States is that most potential treatments fail in preclinical or clinical trials. In fact, just one out of 10 potential medical treatments successfully achieve regulatory approval.
Last year, just 37 novel drugs received FDA approval, the fewest drugs approved for use in treating human conditions in six years. That isn’t because regulatory approval is too stringent; the FDA exists to ensure that drugs are safe for people and that they do what they’re intended to do. It’s because developing drugs that are both safe and work as intended is difficult. And that’s a problem artificial intelligence (AI) was made to solve.
AI is already accelerating the drug development process. AI methodologies, including those in practice now at my own company, VeriSIM Life, are being used to effectively test therapeutic combinations and compounds to find those that will be the most effective with the least number of side effects. And this information is tested against millions of data points to ensure that these new combinations do what they are intended to do: help patients live healthfully.
Importantly, this all happens before human patients are ever involved in a clinical trial, de-risking the experimentation process and potentially accelerating the timeline to market. That’s important because most drugs take between 10 and 12 years to make it from development to the pharmacy.
But AI’s contributions to medicine aren’t limited to the development of new formulations, though that could certainly offer new effective treatments across a wide variety of human diseases and provide more options to patients and providers.
AI apps can also predict efficacious reformulation, for example from a capsule to a caplet, or from digestible medications to transdermal applications by running simulations to perfect dosing and outcomes match between the applications. This opens a new door for pharmaceutical researchers to develop new applications for medical treatments that have traditionally only come in one form, such as capsules or tablets, which could further ease the strain of increasing demand.
AI additionally has the power to help researchers better understand how treatments will impact not only the broader population but also individuals due to variability in their genetics, health history and other factors. In other words, AI could help pre-determine which ADHD medication formulation will work best for an individual patient. That can be particularly important in the case of chemotherapy drugs. Even when they’re not in short supply, chemotherapy drugs don’t work for every patient, and not every patient qualifies to use them.
AI has the power to help researchers and physicians personalize treatment for cancer patients and determine through computer simulations which chemotherapy drugs and combinations will best help individual patients before ever prescribing a treatment plan. We may very well find that the same is true for every other available or currently unavailable medication on the market.
And while today, the focus is on alleviating the current shortage and getting medication into the hands of patients who need it now, it bears repeating that our focus cannot be merely on the manufacturing process but must go all the way back to development.
By leveraging AI to improve, de-risk and accelerate the drug development process, the pharmaceutical industry ultimately will be able to make more treatments available that work for more people and do so with a greater level of efficacy. That could be just the thing needed to permanently eliminate chemotherapy drug shortages and damaging prioritization that comes with them, and other drugs in trouble, and truly help people to live their best and most healthful lives.
Jo Varshney is the founder and CEO of VeriSIM Life.
(Opinions expressed in this article are the author’s own.)
Artificial intelligence
AI
2023-07-15 03:24:03
Original from www.ibtimes.com
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