Any medication taken orally must go through the liner of the digestive tract. Transporter proteins found on cells lining the gastrointestinal tract assist in this process, but for a lot of drugs it is just not known which of those transporters they use to depart the digestive tract.

Identifying the transporters utilized by specific drugs could help improve patient treatment because if two drugs depend on the identical transporter, they will influence one another and shouldn’t be prescribed together.

Researchers at MIT, Brigham and Women’s Hospital and Duke University have now developed a multi-step technique to discover the transporters utilized by different drugs. Their approach, which uses each tissue models and machine learning algorithms, has already shown that a commonly prescribed antibiotic and a blood thinner can interfere with one another.

“One of the challenges in modeling absorption is that drugs are subject to different transporters. “This study is about how we are able to model these interactions, which could help us make drugs safer and more practical and predict potential toxicities which will have been difficult to predict before,” says Giovanni Traverso, MIT associate professor of mechanical engineering, gastroenterologist at Brigham and Women’s Hospital and senior creator of the study.

As we learn more about which transporters help drugs go through the digestive tract, drug developers could also help improve the absorption of recent drugs by adding excipients that improve their interactions with transporters.

Former MIT postdocs Yunhua Shi and Daniel Reker are the lead authors of the study appears today In .

Drug transport

Previous studies have identified several transporters within the gastrointestinal tract that help drugs go through the intestinal lining. Three of essentially the most commonly used ones that were the main focus of the brand new study are BCRP, MRP2 and PgP.

For this study, Traverso and his colleagues adapted a tissue model they developed in 2020 to measure the absorbability of a particular drug. This experimental setup relies on laboratory-grown porcine intestinal tissue and may be used to systematically expose tissues to different drug formulations and measure how well they’re absorbed.

To study the role of individual transporters in tissue, the researchers used short strands of RNA called siRNA to repress the expression of every transporter. They destroyed different transporter combos in each tissue section and were in a position to examine how each transporter interacts with many alternative drugs.

“There are some ways in which drugs can get through the tissue, however it is just not known which way. We can close the roads individually to search out out if the drug gets through even when we close that road. If the reply is yes, that road is not going to be used,” Traverso said.

The researchers tested 23 commonly used drugs using this technique and were in a position to discover the transporters utilized by each of those drugs. They then trained a machine learning model using this data in addition to data from several drug databases. The model learned to make predictions about which drugs would interact with which transporters based on similarities between the drugs’ chemical structures.

Using this model, researchers analyzed a brand new set of 28 currently used drugs in addition to 1,595 experimental drugs. This screen yielded nearly 2 million predictions of possible drug interactions. Among them was the prediction that doxycycline, an antibiotic, could interact with warfarin, a commonly prescribed blood thinner. Doxycycline was also expected to interact with digoxin, used to treat heart failure, levetiracetam, an antiepileptic drug, and tacrolimus, an immunosuppressant.

Identify interactions

To test these predictions, researchers examined data from about 50 patients who had taken considered one of these three drugs after they were prescribed doxycycline. These data, which got here from a patient database at Massachusetts General Hospital and Brigham and Women’s Hospital, showed that when doxycycline was given to patients who were already taking warfarin, the extent of warfarin within the patients’ bloodstream rose after which fell again after they stopped taking it Doxycycline discontinued.

These data also confirmed the model’s predictions that doxycycline absorption is influenced by digoxin, levetiracetam, and tacrolimus. Only considered one of these drugs, tacrolimus, was previously suspected of interacting with doxycycline.

“These are drugs which might be commonly used, and we’re the primary to give you the chance to predict this interaction using this accelerated in silico and in vitro model,” says Traverso. “This form of approach gives you the chance to know the potential safety implications of giving these drugs together.”

In addition to identifying potential interactions between drugs already in use, this approach is also applied to drugs currently in development. Using this technology, drug developers could optimize the formulation of recent drug molecules to forestall interactions with other drugs or improve their absorption capability. Vivtex, a biotech company founded in 2018 by former MIT postdoc Thomas von Erlach, MIT Institute Professor Robert Langer, and Traverso to develop recent oral drug delivery systems, is now pursuing one of these drug optimization.

The research was funded partly by the US National Institutes of Health, the Department of Mechanical Engineering at MIT and the Department of Gastroenterology at Brigham and Women’s Hospital.

Additional authors of the article 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.

This article was originally published at news.mit.edu