Enhancing pharmacogenomic data accessibility and drug safety with large language models: a case study with Llama3.1.

Pharmacogenomics (PGx) holds the promise of personalizing medical treatments based on individual genetic profiles, thereby enhancing drug efficacy and safety. However, the current landscape of PGx research is hindered by fragmented data sources, time-consuming manual data extraction processes, and the need for comprehensive and up-to-date information. This study aims to address these challenges by evaluating the ability of Large Language Models (LLMs), specifically Llama3.

Modulation of Estrogen α and Progesterone Receptors in Triple Negative Breast Cancer Cell Lines: The Effects of Vorinostat and Indole-3-Carbinol In Vitro.

Background/aim: Triple negative cancer (TNBC) is a subtype of breast cancer that is highly aggressive, with poor prognosis and responds differently to treatments. This study investigated the role of vorinostat and indole-3-carbinol (I3C) on regulating critical receptors that are not normally expressed in TNBC.

Materials And Methods: Using real-time PCR, immunostaining, and western blots, the re-expression of estrogen receptor α (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER2) receptors was examined in four different TNBC cell types.