Researchers from MIT, Brigham and Women’s Hospital, and Duke University have developed an innovative approach to identify the transporter proteins that help drugs exit the digestive tract. By understanding which transporters are involved, doctors can avoid prescribing drugs that interfere with each other. The team used tissue models and machine-learning algorithms to study drug transport and interactions. The study revealed that a commonly prescribed antibiotic could interfere with a blood thinner.
The absorption of drugs in the digestive tract is a complex process, as they must pass through the lining of the gastrointestinal tract. Transporter proteins on the cells lining the digestive tract aid in this process. However, it remains unknown which transporters specific drugs utilize to exit the digestive tract.
Identifying the transporters used by specific drugs is crucial in improving patient treatment. When two drugs rely on the same transporter, they can interfere with each other and should not be prescribed together.
The researchers developed a multipronged strategy, combining tissue models with machine-learning algorithms, to identify drug transporters. Their approach involved using siRNA to knock down the expression of individual transporters in pig intestinal tissue. By systematically closing off different roads in the tissue, the researchers could determine which transporters were involved in drug absorption.
The team tested 23 commonly used drugs to identify the transporters used by each drug. Then, they trained a machine-learning model using this data, as well as information from various drug databases. This model could predict potential drug interactions based on the structural similarities between drugs.
Using this model, they analyzed a new set of 28 currently used drugs and 1,595 experimental drugs. The screen yielded nearly 2 million predictions of potential drug interactions, including the prediction that the antibiotic doxycycline could interact with the blood thinner warfarin, a medication commonly prescribed to prevent blood clotting.
To test these predictions, the researchers examined data from patients who had been prescribed doxycycline while taking warfarin. The data confirmed that the level of warfarin in the patients’ bloodstream increased when they started doxycycline and returned to normal once they stopped taking it.
This study not only identified potential drug interactions in drugs already in use but also offers insights for drug developers. Understanding the transporters involved in drug absorption can help developers improve the formulation of new drugs to prevent interactions with other drugs or enhance their absorbability.
Overall, this novel strategy provides a fresh perspective on understanding drug interactions through transporter proteins, leading to safer and more effective patient treatment.
FAQ
Q: What did the researchers from MIT, Brigham and Women’s Hospital, and Duke University develop?
A: The researchers developed an innovative approach to identify the transporter proteins that help drugs exit the digestive tract.
Q: Why is it important to understand which transporters are involved in drug absorption?
A: By understanding which transporters are involved, doctors can avoid prescribing drugs that interfere with each other.
Q: How did the researchers identify drug transporters?
A: The researchers used tissue models and machine-learning algorithms to study drug transport and interactions. They used siRNA to knock down the expression of individual transporters in pig intestinal tissue to determine which transporters were involved.
Q: What did the researchers find in their study?
A: The study revealed that a commonly prescribed antibiotic, doxycycline, could interfere with a blood thinner, warfarin.
Q: How did the researchers confirm their findings?
A: The researchers examined data from patients who had been prescribed doxycycline while taking warfarin. The data confirmed that the level of warfarin in the patients’ bloodstream increased when they started doxycycline and returned to normal once they stopped taking it.
Definitions
Transporter proteins: Proteins found on the cells lining the digestive tract that aid in the absorption of drugs into the body.
Machine-learning algorithms: Algorithms that allow computers to learn and make predictions or decisions without being explicitly programmed.
siRNA: Small interfering RNA, a class of double-stranded RNA molecules used to study gene function by knocking down the expression of specific genes.
Blood thinner: Medication, such as warfarin, that reduces the blood’s ability to clot and is commonly prescribed to prevent blood clotting in certain medical conditions.
Related Links
– MIT
– Brigham and Women’s Hospital
– Duke University
The source of the article is from the blog guambia.com.uy