Breast cancer is a heterogeneous disorder with different molecular subtypes and biological characteristics for which there are diverse therapeutic approaches and clinical outcomes specific to any molecular subtype. It is a global health concern due to a lack of efficient therapy regimens that might be used for all disease subtypes. Therefore, treatment customiza¬tion for each patient depending on molecular characteristics should be considered.

In recent years, artificial intelligence (AI) shows promising results in the diagnosis, prediction, and management of diseases. The move from handwritten medical notes to electronic health records and a huge number of digital data commenced in the era of big data in medicine. AI can improve physician performance and help better clinical decision making which is called augmented intelligence.

The efficacy and safety of drug treatments vary widely due to genetic variations. Pharmacogenomics investigates the impact of genetic variations on patient drug response. This research investigates the frequency of UGT1A1 genetic varia¬tions in the Iranian population, comparing them with global data to provide insights into the pharmacogenomic approach in the Iranian population.

Cancer treatment has improved over the past decades, but many cancer patients still experience adverse drug reactions (ADRs). Pharmacogenomics (PGx), known as personalized treatment, is a pillar of precision medicine that aims to optimize the efficacy and safety of medications by studying the germline variations. Germline variations in the DPYD lead to significant ADRs. The present cross-sectional study aims to evaluate the allele frequency of the DPYD gene variations in the Iranian population to provide insights into personalized treatment decisions in the Iranian population.