Researchers at MIT, Brigham and Women’s Hospital, and Duke University have developed a method for identifying the protein transporters different drugs use to traverse the digestive tract. This could help to avoid dangerous drug interactions and enhance patient treatment as two medications that use the same transporter may interact negatively if prescribed together. The method relies heavily on tissue models and machine-learning algorithms. It has already revealed that a common antibiotic and a blood thinner can interfere with each other.
These findings can also assist drug developers in making their drugs more absorbable by adding excipients that enhance a drug’s interactions with the transporters. The researchers succeeded in identifying the transporters used by 23 commonly used drugs. They then used this data to train a machine-learning model, along with information from drug databases, to predict other drugs’ interactions with the transporters.
Put to real-world testing, the data from a patient database at Massachusetts General Hospital and Brigham and Women’s Hospital confirmed the model’s predictions. A biotech company called Vivtex, co-founded in 2018 by former MIT postdoc Thomas von Erlach, MIT Institute Professor Robert Langer, and Giovanni Traverso to develop new oral drug delivery systems, is already leveraging this technology to tune the formulation of new drug molecules to prevent interactions with other substances or improve their absorbability.
The research uncovers a fundamental aspect of drug absorption in the body, addressing an issue where a lack of understanding could lead to undesirable outcomes. Identifying the correct transporters used by specific drugs can help prescribe the right combinations that do not interfere with each other. This approach has a significant role in drug development, ensuring developers understand how their new drug formulation interacts within the body’s system.
