What Is Drug Repurposing?
Drug repurposing uses an existing medication to treat other conditions. The practice originated long before AI became available. For instance, aspirin is a painkiller that can also reduce the risk of blood clots, heart attack and stroke.
Thalidomide is an early example of how drug repurposing changed the medical industry. Researchers created it to sedate patients before surgeries, but it never received approval. When they studied the side effects that prevented it from being a safe sedative, they found it could treat multiple myeloma and other tumors (1).
Teams invest significant time and money into creating new medications. Repurposing can transform setbacks into opportunities without requiring extra funding. People can get lifesaving drugs faster without waiting the average 12 years between when research starts and when they can access new medications (2).
How AI Assists With Existing Medication Uses
AI has become a crucial part of drug repurposing. Understanding how it benefits the process will help you learn why research teams embrace it.
1. Algorithms Can Scan Drug Profiles Quickly
Doctors already use AI to review patients’ health histories and provide diagnostic suggestions in minutes (3). Applying the same benefit to drug profiles helps teams find new uses for existing medications.
In 2020, researchers used AI to compare the COVID-19 virus with 3,410 available drug profiles (4). The results pointed doctors toward an HIV treatment called Antazanvir. Those hospitalized with SARS-CoV-2 quickly gained a treatment option in a crucial period when the medical community was scrambling to find therapeutic strategies.
2. AI May Find Rare Disease Solutions
Medical literature takes time and patience to read thoroughly. After industry experts sift through hundreds or thousands of drug profiles, they must still compare their findings with patient records to pinpoint solutions for rare diseases. The effort can be exhausting, which may lead to overlooked critical details. AI algorithms don’t experience fatigue or burnout. They can locate any text related to a patient’s condition and report back in moments.
3. Artificial Intelligence Could Accelerate Clinical Trials
New drugs go through four stages of clinical trials (5), including candidate screening. While researchers might take weeks or months to finalize their candidate selection, AI can review applicants immediately.
If the algorithm knows what to look for in each patient profile, it can highlight the people who may have the best experience with drug testing. New treatments with existing medications may become available sooner because AI shaves weeks or months off clinical trial testing.
Why It Helps Patients and Providers
Besides drug repurposing, AI has promising potential in medical research. Patients and doctors could benefit in numerous ways if AI becomes a more prominent tool in the medical field.
Faster Access to Treatments
Traditional avenues to make new medications are time-consuming. People can get hormone treatments for prostate and breast cancer now, but the option only exists because companies funded clinical trials (6). Patients can quickly get help if researchers use AI tools to connect drug side effects with treatments for other conditions. The difference could save lives for anyone with an aggressive disease.
Personalized Medicine May Improve Medication Safety
You may have better drug experiences if your doctor makes recommendations based on your comprehensive health history. Humans can overlook fine details, but AI doesn’t.
An algorithm can search patient data for their genetic profile or experience with previous prescriptions and recommend which drugs to repurpose. The personalized experience could make your future treatments more effective and prevent you from trying multiple drugs to get your desired results.
Extra Treatment Options Improve Cost Savings
Medical services are expensive. Industry leaders constantly look for ways to make health care access more affordable, like scheduling home visits and virtual check-ins to avoid clinic fees (7). They also rely on AI to multiply treatment options.
You’ll pay a hefty price at the pharmacy if you use a name-brand prescription to manage an illness. A medical team’s discovery that a generic medication for a different condition can successfully treat your diagnosis could save you thousands. Research teams achieve that goal with AI-powered drug repurposing.
Potential Concerns People Have With the Practice
AI could become a valuable tool for researching existing medications, but it also presents concerns. People may worry that AI programs will save and reuse their sensitive health information, especially in doctors’ offices (8). Cybercriminals could hack the program and steal the information, while some companies sell patient data to advance future AI algorithms (9).
Regulatory hurdles also exist for AI use in medical research. Teams must provide detailed evidence of a drug’s efficacy before it becomes available for additional treatments. Regulators must understand how each team got its data (10). Regulators may not approve promising drugs if researchers can’t explain how their AI platform made accurate predictions.
Transparency overcomes many AI-related challenges in drug use research. When companies developing AI algorithms share how their models function, they can explain data sourcing to regulators and repurposing teams. Patients gain insight into who uses their data and how, while providers who outline their cybersecurity measures reassure everyone involved in drug repurposing. Together, these efforts build confidence in the process.
AI Is Shaping New Drug Repurposing Strategies
It’s easy to envision a future where AI programs are integral to the medical community. Algorithms help researchers pinpoint new drug uses with existing medications, which saves lives, time and money. The topic may become less intimidating to the public if everyone understands how AI works within that system.
Comments
comments