Publications

Cardiometabolic medications are prescribed to prevent and treat cardiometabolic diseases such as diabetes, high blood pressure, and high cholesterol. This study investigated whether genes could affect the way in which patients use cardiometabolic medications. The authors combined and analyzed cardiometabolic medication use history and genetic information of 567,671 patients from three large biobank studies: FinnGen, the Estonian Biobank and the UK Biobank. In total, 333 locations across several genes were found to be associated with total medication use, medication switching or treatment discontinuation. This study demonstrates how medication use history can help better understand the underlying biology of cardiometabolic diseases.

Dasatinib is a medication used to treat certain types of leukemia. Its effectiveness can be influenced by other drugs that patients might be taking. Some medications can affect the enzyme (CYP3A4) that breaks down dasatinib in the liver, while others, like antacids, can change stomach acidity and affect how dasatinib is absorbed.
Researchers created a so called physiologically based pharmacokinetic (PBPK) model to predict how dasatinib behaves in the body and interacts with other drugs. This model simulates the human body and helps understand how dasatinib is distributed, broken down, and eliminated over time.
The PBPK model was developed using dasatinib’s properties and clinical study data. It accurately described how dasatinib levels change in the blood. The model was then used to figure out how to adjust dasatinib doses when taken with other medications, for example:
• How the dasatinib dose should be reduced with enzyme blockers (CYP3A4 inhibitors), or
• How the dasatinib dose should be increased with enzyme boosters (CYP3A4 inducers).
This model helps physicians to personalize dasatinib treatment for patients, ensuring they receive the correct dose when taking other medications, thereby improving effectiveness and reducing side effects.

Imatinib is a medication used to treat chronic myeloid leukemia, a type of blood cancer. It is broken down in the body by enzymes called CYP2C8 and CYP3A4. Additionally, a protein called P-glycoprotein pumps imatinib out of cells, affecting its activity. Imatinib can interact with other medications, influencing the enzymes and the protein, which can impact the effectiveness and safety of both imatinib and the other drugs.
Researchers created a computer model, known as a physiologically-based pharmacokinetic (PBPK) model, to predict how imatinib and its byproduct behave in the body and interact with other drugs. This model simulates the human body and helps understand how imatinib is distributed, broken down, and eliminated over time.
The PBPK model was developed using imatinib’s properties, its breakdown by CYP3A4 and CYP2C8, and its interaction with P-glycoprotein. Clinical study data were used to validate the model, which accurately described imatinib levels in the blood over time. The model was then used to explore drug interactions:
• With drugs affecting enzyme activity, like rifampicin, ketoconazole, and gemfibrozil: These simulations showed how these drugs could change imatinib and its byproduct levels.
• With drugs affected by imatinib, like simvastatin and metoprolol: The simulations showed how imatinib could alter the levels of these drugs.
The model successfully predicted these interactions, matching observed data closely. It can help in developing new drugs and optimizing dosages for patients, ensuring safe and effective treatments when multiple medications are used together.