AIMS: The present review explores the existing evidence on pharmacogenomic tests for prediction of lithium response in the treatment of bipolar disorder. We focused our research article on reports describing findings from genome-wide association stud...
Recent advances in pharmacology are revolutionizing drug discovery and treatment strategies through personalized medicine, pharmacogenomics, and artificial intelligence (AI). The objective of the present study is to review the role of personalized me...
Personalized medicine is a novel frontier in health care that is based on each person's unique genetic makeup. It represents an exciting opportunity to improve the future of individualized health care for all individuals. Pharmacogenomics, as the mai...
Genome-wide association studies (GWAS) have identified genetic variations associated with adverse drug effects in pharmacogenomics (PGx) research. However, interpreting the biological implications of these associations remains a challenge. This revie...
This paper presents a methodology for automatically extracting insights from PubMed articles using a Natural Language Processing (NLP) framework. Our approach, leveraging advanced NLP techniques and Named Entity Recognition (NER), is crucial for adva...
Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing various scientific and clinical disciplines including pharmacogenomics (PGx) by enabling the analysis of complex datasets and the development of predictive models. The integra...
Expert opinion on drug metabolism & toxicology
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INTRODUCTION: Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning and in-silico predictions, scarcity of data hamp...
Individual may response to drug treatment differently due to their genetic variants located in enhancers. These variants can alter transcription factor's (TF) binding strength, affect enhancer's chromatin activity or interaction, and eventually chang...
Drug response prediction (DRP) is a central task in the era of precision medicine. Over the past decade, the emergence of deep learning (DL) has greatly contributed to addressing DRP challenges. Notably, the prediction of DRP for cancer cell lines be...