Any medication taken orally must pass through the lining of the digestive tract. Carrier proteins found in the cells lining the gastrointestinal tract help with this process, but for many drugs, it is unknown which of these transporters they use to leave the digestive tract.
Identifying the transporters used by specific drugs could help improve patient treatment because if two drugs depend on the same transporter, they may interfere with each other and should not be prescribed together.
Researchers at MIT, Brigham and Women's Hospital, and Duke University have developed a multipronged strategy to identify transporters used by different drugs. Their approach, which uses both tissue models and machine learning algorithms, has already revealed that a commonly prescribed antibiotic and a blood thinner can interfere with each other.
“One of the challenges in modeling absorption is that drugs are bound to different transporters. “This study is about how we can model those interactions, which could help us make drugs safer and more effective, and predict potential toxicities that may have been difficult to predict until now,” says Giovanni Traverso, associate professor of mechanical engineering at MIT. , a gastroenterologist at Brigham and Women's Hospital and lead author of the study.
Learning more about which transporters help drugs pass through the digestive tract could also help drug developers improve the absorption capacity of new drugs by adding excipients that improve their interactions with the transporters.
Former MIT postdocs Yunhua Shi and Daniel Reker are the lead authors of the study, which appears today in Nature Biomedical Engineering.
Drug transportation
Previous studies have identified several transporters in the gastrointestinal tract that help drugs pass through the intestinal lining. Three of the most used, which were the focus of the new study, are BCRP, MRP2 and PgP.
For this study, Traverso and his colleagues adapted a tissue model they had developed in 2020 to measure the absorbability of a given drug. This experimental setup, based on lab-grown pig intestinal tissue, can be used to systematically expose the tissue to different drug formulations and measure how well they are absorbed.
To study the role of individual transporters within the tissue, the researchers used short strands of RNA called siRNAs to knock down the expression of each transporter. In each tissue section, they knocked down different combinations of transporters, allowing them to study how each transporter interacts with many different drugs.
“There are some paths that drugs can take through tissue, but it is not known which one. We can close the roads separately to find out, if we close this road, does the drug still pass? If the answer is yes, then you won't use that path,” says Traverso.
The researchers tested 23 commonly used drugs using this system, allowing them to identify the transporters used by each of those drugs. They then trained a machine learning model with that data, as well as data from several drug databases. The model learned to make predictions about which drugs would interact with which transporters, based on similarities between the chemical structures of the drugs.
Using this model, the researchers analyzed a new set of 28 currently used drugs, as well as 1,595 experimental drugs. This test yielded nearly 2 million predictions of potential drug interactions. Among them was the prediction that doxycycline, an antibiotic, could interact with warfarin, a commonly prescribed blood thinner. Doxycycline was also predicted to interact with digoxin, which is used to treat heart failure, levetiracetam, an anti-seizure medication, and tacrolimus, an immunosuppressant.
Identify interactions
To test those predictions, the researchers looked at data from about 50 patients who had been taking one of those three drugs when they were prescribed doxycycline. These data, which came from a database of patients at Massachusetts General Hospital and Brigham and Women's Hospital, showed that when doxycycline was given to patients already taking warfarin, the level of warfarin in the patients' bloodstream increased and then it went down again after he stopped taking doxycycline.
Those data also confirmed model predictions that doxycycline absorption is affected by digoxin, levetiracetam, and tacrolimus. Only one of those medications, tacrolimus, had previously been suspected of interacting with doxycycline.
“These are commonly used drugs, and we are the first to predict this interaction using this accelerated in silico and in vitro model,” says Traverso. “This type of approach gives you the ability to understand the potential safety implications of giving these medications together.”
In addition to identifying potential interactions between drugs already in use, this approach could also be applied to drugs currently in development. Using this technology, drug developers could adjust the formulation of new drug molecules to avoid interactions with other drugs or improve their absorbability. Vivtex, a biotech company co-founded in 2018 by former MIT postdoc Thomas von Erlach, MIT Institute Professor Robert Langer, and Traverso to develop new oral drug delivery systems, is now pursuing that kind of drug tuning.
The research was funded, in part, 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.
Other authors of the paper include Langer, 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.
