Q&A: How can drug repurposing lower drug costs and improve care?

HERSHEY, Pa. — Americans pay a lot of money for prescription medications. In 2023, spending on prescription drugs in the United Stated topped $722 billion, a trend that’s expected to continue. Yet, nearly 30% struggle to pay for their prescriptions and more than half of adults are worried about the affordability of their family’s medications, according to polling from KFF.

One way to potentially lower the cost of prescription drugs? Find new uses for existing medication, which is the idea behind drug repurposing.

“New drugs are expensive to develop. If we can identify new uses for off-patent drugs, we can accelerate the drug discovery process, saving both time and money,” said Dajiang Liu, distinguished professor, vice chair for research and director of artificial intelligence and biomedical informatics at the Penn State College of Medicine.

Recently, Liu and his colleagues developed a drug repurposing pipeline, supported by funding from the National Institutes of Health, to identify new potential therapeutics for autoimmune diseases, such as lupus and rheumatoid arthritis. They published their findings in the journal Cell Genomics. In the following Q&A, Liu discussed drug repurposing, how it works and its benefits.

Q: What is drug repurposing?

Liu: Drug repurposing is when we find a new use for a medication that’s already on the market. Existing drugs are approved for a particular disease. Sometimes, those drugs may also be effective in treating other conditions. Diseases can share the same mechanism, or the pathway for how a disease develops, even though they may lead to distinct conditions.

Q: What are the benefits of drug repurposing?

Liu: One major advantage of drug repurposing is that the drugs are already on the market and are safe. Normally, it takes a lot of time and effort to establish a drug’s safety but here, we can move directly to determining a drug’s effectiveness.

Cost is another issue, especially if the repurposed drug is off patent since generic drugs are much cheaper. If we can find alternative uses for these drugs, it could help lower the cost of prescription drugs.

Q: What’s an example of a drug that has been repurposed?

Liu: One well-known example is hydroxychloroquine. It was originally developed as an anti-malarial drug, but people found evidence, from experiments and observation, that it’s quite effective at slowing down the progression of lupus, an autoimmune disease, and also controlling flare-ups of the disease.

In my previous research, we found that dextromethorphan, a cough medicine, was effective for smoking cessation treatment.

Q: What’s the process for screening potential candidates for drug repurposing?

Liu: Previously, drug repurposing was an ad hoc process where someone, by luck, might observe that a drug could be effective for another disease. There are tens or even hundreds of thousands of approved drugs in the U.S. Food and Drug Administration database, and someone would have to dedicate their career to screen them manually to figure out one repurposed drug for one disease.

Now, we don’t have to rely on the genius of a particular scientist or on luck. With a data science approach, we can stream and automate the process to look for patterns in very complex data using machine learning, accelerating scientific discovery.

Q: You and your collaborators developed a novel approach to finding new uses for existing drugs. Can you tell me more about it?

Liu: First, we identify therapeutics based on how they influence the mechanisms involved in a disease. In our work, we look at gene expression or how cells translate the information contained within a gene. In some diseases, gene expression is elevated while in other diseases, it’s decreased. If the gene expression is what’s causing the disease, by reversing it — decreasing gene expression in cases where it’s elevated or elevating it in cases where it’s suppressed — we can potentially reverse the disease as well. We look for drugs with these kinds of patterns of reversing gene expression. These are experiments with cells that happen in the lab.

Then, we validate the mechanism of the candidate drug. In our new model, we do this by examining data from electronic health records. For example, we look at the health records of people who have taken the drug we’re interested in and look at biomarkers or disease incidence of the new disease that we want to treat with the existing drug.

Q: What’s novel about your approach?

Liu: This drug repurposing pipeline — going from mechanistic studies to real-world data from electronic health records — is completely novel for autoimmune diseases. Electronic health records have been used to look at potential for new lipid-lowering medications because you can measure cholesterol and see if it has decreased over time. For autoimmune disease, there isn’t one set of relevant biomarkers to look at.

We still need to do randomized controlled trials and other studies, but designing a model for validating autoimmune disease-related drugs this way is completely new. We also don’t have to focus on only one autoimmune disease. We can look at all autoimmune diseases together because many autoimmune diseases share similar disease mechanisms, which accelerates the process and potentially makes it more efficient.

Lastly, going from mechanistic studies of cells directly to human data lets us jump over some labor intensive and time-consuming steps. This approach could potentially allow us to validate drugs more quickly because we can directly evaluate the efficacy of the drug in humans.

Q: Why is drug repurposing potentially meaningful for people with autoimmune disease?

Liu: There aren’t a lot of good treatment options and existing treatments often have bad side effects, which can limit their use. The hope is that if you can find new drugs, they might have fewer side effects and might be more effective.

Q: You’ve identified some potential candidates for repurposing for autoimmune diseases. What happens next?

Liu: Yes, we identified six potential drugs. For example, hyoscyamine is a medication often prescribed for irritable bowel syndrome. It reverses disease gene expression the same way as steroid drugs, like cortisone, and we saw that it reverses gene expression in genes associated with rheumatoid arthritis. It could be effective for treating rheumatoid arthritis and have fewer side effects than the currently used anti-inflammatory drugs.

The next step would be to take the identified drugs to clinical trials and continue to refine the framework to study other diseases. With more evidence from human trials, we are poised to transform health care for many Americans, making it more affordable and effective.