The focus is on understanding how insights from studies on DDIs can enhance our knowledge of DGIs and vice versa. This could lead to better management strategies for predicting and preventing negative drug reactions. By analyzing genetic data, the project seeks to identify specific genetic variants (known as star alleles) that could influence the risk of SADRs in response to certain medications.
The scientific rationale behind this project stems from the observation that DDIs are not always indicative of DGIs, suggesting a gap in our understanding that could be pivotal for drug safety and efficacy. The goal is to bridge this gap by using whole genome sequencing data to conduct a comprehensive analysis of how genetic factors affect drug interactions and their outcomes. This includes using sophisticated statistical models to account for a wide range of variables, such as age, gender, race, co-medications, and comorbid conditions.
The project is set to run for at least one year and has the potential to significantly impact public health. By providing a more nuanced understanding of how drugs interact with genetic factors, it aims to advance patient care through more personalized and precise treatment strategies. This could lead to a reduction in adverse drug reactions, improving patient safety and treatment outcomes.