The biggest obstacle to essential drugs is timing.
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You don’t need a medical degree to understand the importance of receiving drugs when you need them.
When patients face delays, the consequences can affect both short-term illnesses and chronic conditions. Essential medications can curb the spread of infections and disease, reduce pain, and help people return to their daily lives and work more quickly. And if you’ve ever watched an episode of “The Pitt,” you know that alleviating the burden on crowded hospitals allows staff to focus on patients with more serious ailments.
The good news is that artificial intelligence can significantly increase the speed at which pharmaceutical companies test, manufacture and distribute medications to the people who rely on them.
How AI is transforming drug discovery
AI is helping eliminate some of the industry’s biggest bottlenecks: finding the right drug and proving it works in trials, says Dan Sheeran, vice president and general manager of Healthcare and Life Sciences at Amazon Web Services (AWS).
“For patients, that’s years of waiting for a treatment that may already be in the development pipeline but hasn’t made it through discovery, clinical trials and approval,” says Sheeran.
To discover a new therapy, scientists must search through a near-infinite chemical space for molecules that are both effective and safe.
“That process has historically been manual, sequential and slow,” explains Sheeran. “AI agents can now propose candidate molecules, predict their properties, and learn from each round of experiments to sharpen the next round automatically.”
This isn’t simply a future possibility. AI is already helping with this critical early stage.
For example, Sheeran says biotech company Genentech built an AI agent that searches 38 million biomedical papers to identify drug targets and validate biomarkers, automating more than 43,000 hours of manual research each year.
In another instance, Sanofi, an AI-driven biopharma company, created a “lab-in-the-loop” system in which AI agents design molecules, plan synthesis, run experiments, and learn from the results in a continuous cycle. The result is discovery work that can be compressed into weeks rather than years.
With AI-driven simulations, virtual models can then test how the human body reacts to molecules even before physical lab work begins.
Getting new medicines through trials faster
AI continues to expedite the release of new drugs long after the discovery phase.
Shortening the time required to run clinical trials is another impactful way technology helps patients receive new medications sooner, says Ram Yalamanchili, Founder and CEO of Tilda Research, which works with pharmaceutical companies, biotech firms and the contract research organizations (CROs) that run trials on their behalf.
“Running a clinical trial in the U.S. typically costs tens of millions of dollars and takes several years to complete,” says Yalamanchili. “This involves an enormous amount of operational work, getting research sites activated, collecting and reviewing regulatory documents, resolving missing information, coordinating with research sites and vendors, and keeping thousands of records accurate and inspection-ready.”
Instead, AI changes the game. Yalamanchili points to Tilda Research’s “AI Teammates” platform and cites a recent example that reduced work expected to take six months to less than eight weeks. This improvement in speed doesn’t sacrifice quality, he adds, plus it doesn’t change how long the clinical science takes.
“AI isn’t shortening how long you need to monitor a patient’s response to a drug, and it shouldn’t, [but] what it does is remove the delays caused by human bottlenecks in the administrative machinery around a trial so trials can start faster, run with fewer errors, and move through regulatory documentation faster — which does, in aggregate, move a drug toward patients sooner.”
Improving drug manufacturing and delivery
Along with drug discovery and clinical trials, AI can also optimize manufacturing and improve supply chain forecasting.
Using “digital twins,” or virtual replicas of factories, manufacturers can monitor production lines to identify slowdowns and bottlenecks. Sensors can also flag the likelihood of equipment wear before breakdowns happen, which helps minimize costly factory downtime.
AI can sift through massive biomedical datasets in seconds to find promising drug candidates. It can also help companies better predict who needs medications, where they are needed, and when demand may surge. That can reduce shortages while also reducing overstocked medications that may expire and prove ineffective before they are used.
During delivery, AI-powered monitoring systems can track temperature-sensitive vaccines to prevent spoilage en route to a destination before they reach patients.
AI ushers in massive benefits across the entire pharmaceutical ecosystem. From drug makers and manufacturers to hospitals, clinics and pharmacies, technology is helping remove inefficiencies that slow progress. The ultimate benefit is simple: getting safe, effective medicines into the hands of those who need them faster.
Marc Saltzman is the host of the Tech It Out podcast and is the author of the book, Apple Watch For Dummies (Wiley).