Any drug that’s taken orally must go through the liner of the digestive tract. Transporter proteins found on cells that line the GI tract help with this process, but for a lot of drugs, it’s unknown which of those transporters they use to exit the digestive tract.
Identifying the transporters utilized by specific drugs could help to enhance patient treatment because if two drugs depend on the identical transporter, they will interfere with one another and shouldn’t be prescribed together.
Researchers at MIT, Brigham and Women’s Hospital, and Duke University have now developed a multipronged technique to discover the transporters utilized by different drugs. Their approach, which makes use of each tissue models and machine-learning algorithms, has already revealed that a commonly prescribed antibiotic and a blood thinner can interfere with one another.
“Considered one of the challenges in modeling absorption is that drugs are subject to different transporters. This study is all about how we are able to model those interactions, which could help us make drugs safer and more efficacious, and predict potential toxicities which will have been difficult to predict until now,” says Giovanni Traverso, an associate professor of mechanical engineering at MIT, a gastroenterologist at Brigham and Women’s Hospital, and the senior creator of the study.
Learning more about which transporters help drugs go through the digestive tract could also help drug developers improve the absorbability of recent drugs by adding excipients that enhance their interactions with transporters.
Former MIT postdocs Yunhua Shi and Daniel Reker are the lead authors of the study, which appears today in .
Drug transport
Previous studies have identified several transporters within the GI tract that help drugs go through the intestinal lining. Three of essentially the most commonly used, which 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 that they had developed in 2020 to measure a given drug’s absorbability. This experimental setup, based on pig intestinal tissue grown within the laboratory, could be used to systematically expose tissue to different drug formulations and measure how well they’re absorbed.
To check the role of individual transporters inside the tissue, the researchers used short strands of RNA called siRNA to knock down the expression of every transporter. In each section of tissue, they knocked down different combos of transporters, which enabled them to review how each transporter interacts with many alternative drugs.
“There are just a few roads that drugs can take through tissue, but you do not know which road. We will close the roads individually to determine, if we close this road, does the drug still undergo? If the reply is yes, then it’s not using that road,” Traverso says.
The researchers tested 23 commonly used drugs using this technique, allowing them to discover transporters utilized by each of those drugs. Then, they trained a machine-learning model on that data, in addition to data from several drug databases. The model learned to make predictions of which drugs would interact with which transporters, based on similarities between the chemical structures of the drugs.
Using this model, the 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 potential drug interactions. Amongst 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 antiseizure medication, and tacrolimus, an immunosuppressant.
Identifying interactions
To check those predictions, the researchers checked out data from about 50 patients who had been taking one in every of those three drugs once they were prescribed doxycycline. This 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 already taking warfarin, the extent of warfarin within the patients’ bloodstream went up, then went back down again after they stopped taking doxycycline.
That data also confirmed the model’s predictions that the absorption of doxycycline is affected by digoxin, levetiracetam, and tacrolimus. Only one in every of those drugs, tacrolimus, had been previously suspected to interact with doxycycline.
“These are drugs which are commonly used, and we’re the primary to predict this interaction using this accelerated in silico and in vitro model,” Traverso says. “This type of approach gives you the power to grasp the potential safety implications of giving these drugs together.”
Along with identifying potential interactions between drugs which are already in use, this approach may be applied to drugs now in development. Using this technology, drug developers could tune the formulation of recent drug molecules to forestall 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 recent oral drug delivery systems, is now pursuing that sort of drug-tuning.
The research was funded, partly, 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.