When any drug is taken orally, it needs to pass through the lining of the digestive tract. Transporter proteins on the cells lining the GI tract assist in this process, but for many drugs, it is unclear which specific transporters they utilize to exit the digestive tract.
Identifying the transporters used by individual drugs could enhance patient treatment as drugs that rely on the same transporter can interfere with each other and should not be prescribed together.
Researchers from MIT, Brigham and Women’s Hospital, and Duke University have developed a comprehensive strategy to identify the transporters used by different drugs. Their approach involves using tissue models and machine-learning algorithms, revealing interactions between a commonly prescribed antibiotic and a blood thinner.
Giovanni Traverso, an associate professor of mechanical engineering at MIT and a gastroenterologist at Brigham and Women’s Hospital, explains, “This study focuses on modeling absorption of drugs through different transporters, which could lead to safer and more effective drug use and predict potential toxicities that were previously hard to anticipate.”
Understanding which transporters assist drugs in passing through the digestive tract could also help drug developers improve the absorbability of new drugs by enhancing their interactions with transporters.
The study’s lead authors, former MIT postdocs Yunhua Shi and Daniel Reker, have published their findings in Nature Biomedical Engineering.
Previous research has identified several transporters in the GI tract that aid drugs in passing through the intestinal lining. The new study focuses on three commonly used transporters—BCRP, MRP2, and PgP.
Using a tissue model developed in 2020, the researchers measured the absorbability of different drugs. By knocking down the expression of individual transporters within the tissue, they were able to study how each transporter interacts with a variety of drugs.
After testing 23 commonly used drugs, the researchers trained a machine-learning model to predict interactions between drugs and transporters. This model was then used to analyze a new set of 28 drugs and 1,595 experimental drugs, revealing potential drug interactions.
One of the predictions made by the model was that the antibiotic doxycycline could interact with the blood thinner warfarin, as well as with digoxin, levetiracetam, and tacrolimus.
Further analysis of patient data confirmed the model’s predictions, highlighting potential interactions between doxycycline and the other drugs.
This approach not only identifies interactions between existing drugs but can also be applied to drugs in development to prevent interactions or improve absorbability.
Funded by the U.S. National Institutes of Health, the Department of Mechanical Engineering at MIT, and the Division of Gastroenterology at Brigham and Women’s Hospital, this research has the potential to revolutionize drug development and patient treatment.
Other authors of the paper include Robert Langer, Thomas von Erlach, James Byrne, Ameya Kirtane, Kaitlyn Hess Jimenez, Zhuyi Wang, Natsuda Navamajiti, Cameron Young, Zachary Fralish, Zilu Zhang, Aaron Lopes, Vance Soares, Jacob Wainer, and Lei Miao.
