Good news! Unusual or rare drug interactions can be dangerous!
On the other hand, the reverse applies too! AI may finally allow to mix more drugs in better ways without causing harmful effects. Heretofore, the precautionary principle prevented many potentially useful drug combinations.
"... Learning 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. ...
For this study, ... 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. ...
Using this model, the researchers analyzed a new set of 28 currently used drugs, as well as 1,595 experimental drugs. This screen 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 antiseizure medication, and tacrolimus, an immunosuppressant. ..."
From the abstract:
"In vitro systems that accurately model in vivo conditions in the gastrointestinal tract may aid the development of oral drugs with greater bioavailability. 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. For 24 drugs with well-characterized drug–transporter interactions, 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. 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."
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