Abstract
Patients experiencing adverse drug events (ADE) from polypharmaceutical regimens present a huge challenge to modern healthcare. While computational efforts may reduce the incidence of these ADEs, current strategies are typically non-generalizable for standard healthcare systems. To address this, we carried out a retrospective study aimed at developing a statistical approach to detect and quantify potential ADEs. The data foundation comprised of almost 2 million patients from two health regions in Denmark and their drug and laboratory data during the years 2011 to 2016. We developed a series of multistate Cox models to compute hazard ratios for changes in laboratory test results before and after drug exposure. By linking the results to data from a drug-drug interaction database, we found that the models showed potential for applications for medical safety agencies and improved efficiency for drug approval pipelines.
Original language | English |
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Journal | Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing |
Volume | 30 |
Pages (from-to) | 360-376 |
Number of pages | 17 |
ISSN | 2335-6936 |
DOIs | |
Publication status | Published - 2025 |