Struggling to Understand a Pill Bottle’s Tiny Type? Help Is on the Way.

It’s late. The pharmacy and doctor’s office are closed, and you’re standing in a store’s medicine aisle trying to figure out whether the over-the-counter pain reliever in your hand is safe for your mother. You flip over the box to read a drug facts label that’s both tiny and dense as a legal brief.

The labels are rarely read and of little help in deciding if a medication is safe to take along with other drugs or by people with specific conditions, says Eun Kyoung Choe, an associate professor at the University of Maryland College of Information, who’s working on a project to cut through the small print.

“People glance at it,” said Choe, who has conducted experiments to find out how well people understand such labels. “They read something, but it doesn’t register.”

Choe is the principal investigator behind Aidara, an AI-powered mobile app designed to do what the drug facts label doesn’t: translate complex medication safety information into clear, personalized guidance. It could help older adults, people with low health literacy, and the informal caregivers making medication decisions on behalf of someone else, often without much clinical support.

The project started in 2024, when Jeffrey Cox, a researcher in the FDA’s nonprescription drug division, reached out to Choe after learning about her work in health informatics. Cox’s team had been studying how consumers—particularly those with low literacy—interpret over-the-counter (OTC) drug labels. She was fascinated.

“Because as an OTC medication consumer myself, I admit I don’t pay a lot of attention to the drug facts label either,” Choe said. “I was surprised to learn how much decision-relevant information is actually in there.”

The two secured a small FDA grant to get started, and a year later, Choe expanded the work with funding from the Massachusetts AI and Technology Center for Connected Care in Aging and Alzheimer’s Disease, through the National Institute on Aging. That’s where the caregiver piece came in.

Besides people with literacy issues or older adults, those caregivers who administer OTC medications on behalf of someone else—especially those caring for a loved one with Alzheimer’s disease—are an underserved group—often older adults themselves who lack guidance and support, Choe said

To evaluate its app prototype, Choe’s team recruited adults 60 and older and informal caregivers 50 and older, and walked them through medication decision scenarios in the lab.

Aidara guides users through a structured process: First, enter the drug by typing, speaking or photographing the pill bottle; next, the app pulls from the drug facts label and generates screening questions—checking for allergies, drug interactions, age-related risks and disease contraindications. Finally, it delivers a recommendation: safe for use, consult a doctor, consult a doctor/pharmacist or do not use.

Each recommendation includes a personalized rationale tied to the user’s own health profile and the specific medication in hand. For those who get the all-clear, the team also plans to include directions for use in a more accessible format than normally found on an OTC medicine bottle. Notably, the lab study found that participants began paying closer attention to safety information and wanted to know more, including asking about drug interactions with their other medications.

Currently, the prototype works for a small set of medications out of the tens of thousands of OTC medications on the market. To scale up, the team is using large language models to automatically extract safety information from drug labels and convert it into decision trees to help guide patients.

The team has been working with researchers at Yonsei University in South Korea, annotating drug labels to build a benchmark dataset and evaluate the model’s outputs.

The ultimate goal is an app that works across a wide range of OTC medications and helps people make safer medication decisions, reducing the risk of adverse drug reactions.