Exploring the Impact of Genetics on New Drugs and Potential Drug Targets: A Multi-Omics Approach to Improve Personalized Therapeutics.

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Background

In recent years, significant advancements have been made in the field of new drug development. With the advent of high-throughput sequencing technologies, the identification of new drug targets has become more efficient and precise. In addition, multi-omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, have emerged as a powerful tool for understanding the complexity of diseases and identifying new therapeutic targets.

The goal of this research topic is to explore the latest advances in new drug development and the use of multi-omics approaches for identifying new drug targets. The focus will be on understanding the molecular mechanisms underlying diseases and how they can be targeted for therapy. In addition, we will examine the role of personalized medicine and precision medicine in new drug development, and how these approaches can be leveraged to improve patient outcomes.

We welcome submissions of original research, review articles, meta-analysis, Mendelian Analysis, Case Reports, Methodological Advances, and perspectives that address the following themes:

Identification of FDA-approved drugs, new drugs, and Potential Drug Targets using single/multi-omics approaches

Discovering and predicting new drug targets through bioinformatics and ensuring these targets have been validated at least at the cellular level.

Examining the pharmacology, toxicity, and response of new drugs through a combination of clinical trials or case report.

Meta-analysis on the response and toxicity of drugs widely used in clinical settings, with a focus on utilizing large amounts of clinical data

New tools developed for new drug design and potential drug targets, including but not limited to machine learning, new algorithms, deep learning, knowledge graph, etc.

We are particularly interested in manuscripts that provide new insights into approaches in new drug development, and the impact on genetics and patient outcomes.

Please note: If patient data are analyzed, a comprehensive description of the patients including sex, age, diagnostic criteria, inclusion and exclusion criteria, disease stage, therapy received, comorbidities as well as additional clinical information and assessment of clinical response/effects should be included. If genetic, proteomics, metabolomics, or other omics data are analyzed, a comprehensive description of the methods and the rationale for the selection of the specific data studied should be provided. Studies related to natural compounds, herbal extracts, or traditional medicine products, are outside the scope of this Research Topic and should instead be submitted to the specialty section Ethnopharmacology.

Keywords: Genetics; Multi-Omics; Drug; Metabolomics; Transcriptomics; Machine Learning, Knowledge Graph; Natural Products; Traditional Chinese Medicines

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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