Researchers Use AI To Learn Which Drugs Don’t Mix


A study, published in the journal Nature Biomedical Engineering, centers around a model used to determine which drugs may interfere with one another if taken together. 

“In vitro systems that accurately model in vivo conditions in the gastrointestinal tract may aid the development of oral drugs with greater bioavailability,” the researchers wrote. 

“Here we show that the interaction profiles between drugs and intestinal drug transporters can be obtained by modulating transporter expression in intact porcine tissue explants via the ultrasound-mediated delivery of small interfering RNAs and that the interaction profiles can be classified via a random forest model trained on the drug–transporter relationships.”

According to MIT News, which wrote about the study, the researchers made “use of both tissue models and machine-learning algorithms,” which “revealed that a commonly prescribed antibiotic and a blood thinner can interfere with each other.”

The outlet said that discovering “more about which transporters help drugs pass through the digestive tract could also help drug developers improve the absorbability of new drugs by adding excipients that enhance their interactions with transporters.” Likewise, it could “also be applied to drugs now in development.” 

“Using this technology, drug developers could tune the formulation of new drug molecules to prevent 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,” MIT News said.

In tests with 24 drugs “with well-characterized drug–transporter interactions,” the researchers said that the “model achieved 100% concordance.” 

“For 28 clinical drugs and 22 investigational drugs, the model identified 58 unknown drug–transporter interactions, 7 of which (out of 8 tested) corresponded to drug-pharmacokinetic measurements in mice,” they continued. 

“We also validated the model’s predictions for interactions between doxycycline and four drugs (warfarin, tacrolimus, digoxin and levetiracetam) through an ex vivo perfusion assay and the analysis of pharmacologic data from patients. Screening drugs for their interactions with the intestinal transportome via tissue explants and machine learning may help to expedite drug development and the evaluation of drug safety.”

Giovanni Traverso, an associate professor of mechanical engineering at MIT and the senior author of the study, told MIT News that one of the “challenges in modeling absorption is that drugs are subject to different transporters.” 

“This study is all about how we can model those interactions, which could help us make drugs safer and more efficacious, and predict potential toxicities that may have been difficult to predict until now,” said Traverso, who is also a gastroenterologist at Brigham and Women’s Hospital.

MIT News has more background on the study:

“Previous studies have identified several transporters in the GI tract that help drugs pass through the intestinal lining. Three of the most commonly 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 a given drug’s absorbability. This experimental setup, based on pig intestinal tissue grown in the laboratory, can be used to systematically expose 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 siRNA to knock down the expression of each transporter. In each section of tissue, they knocked down different combinations of transporters, which enabled them to study how each transporter interacts with many different drugs.”

The publication explained that, to test their predictions, researchers “looked at data from about 50 patients who had been taking one of those three drugs when they were prescribed doxycycline,” which showed “that when doxycycline was given to patients already taking warfarin, the level of warfarin in the patients’ bloodstream went up, then went back down again after they stopped taking doxycycline.” It also “confirmed the model’s predictions that the absorption of doxycycline is affected by digoxin, levetiracetam, and tacrolimus,” according to MIT News.

“There are a few roads that drugs can take through tissue, but you don’t know which road. We can close the roads separately to figure out, if we close this road, does the drug still go through? If the answer is yes, then it’s not using that road,” Traverso told the publication.

“These are drugs that are commonly used, and we are the first to predict this interaction using this accelerated in silico and in vitro model,” Traverso continued. “This kind of approach gives you the ability to understand the potential safety implications of giving these drugs together.”



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