About this Research Topic
The discovery of new biomarkers, drug targets, and therapeutic mechanisms is pivotal for the development of effective treatments across a spectrum of diseases. Traditional methods, such as omics technologies and molecular biology techniques, have been the cornerstone of biomedical research due to their proven reliability and depth of insight. In parallel, artificial intelligence (AI) has emerged as a transformative tool, offering innovative approaches to data analysis and interpretation. Despite its rapid advancement, concerns about the reliability and reproducibility of AI methods compared to traditional approaches persist. By embracing both traditional and AI methodologies, researchers can leverage the strengths of each to enhance discovery processes, validate findings, and accelerate progress in pharmacology.
This Research Topic aims to provide a comprehensive platform for studies utilizing traditional methods, AI approaches, or a combination of both in the quest to identify novel biomarkers, drug targets, and therapeutic mechanisms—including those underlying known drug treatments. We seek to explore the challenges and opportunities presented by each methodology independently, as well as their integration. Traditional methods offer robustness and a deep understanding of biological systems, while AI brings efficiency and the ability to analyze complex, large-scale datasets. By welcoming research from both domains, we hope to foster innovation, encourage cross-disciplinary collaboration, and address the limitations inherent in each approach when used in isolation. This collection will showcase how diverse methodologies contribute to advancements in drug discovery and development, ultimately leading to more effective therapeutic strategies.
We invite submissions that utilize traditional experimental methods, artificial intelligence approaches, or a combination of both to advance the discovery of novel biomarkers, drug targets, and therapeutic mechanisms. Topics of interest include:
Discovery of new biomarkers and drug targets using omics technologies, molecular biology techniques, and other traditional methods.
Unveiling novel therapeutic mechanisms in existing drug treatments, including the identification of new biomarkers.
Application of AI methods (e.g., machine learning, deep learning) in biomarker and drug target discovery, therapeutic mechanism elucidation, and drug repurposing strategies.
Studies integrating traditional methods and AI to enhance discovery and validation processes.
Comparative analyses of traditional and AI approaches in pharmacological research.
Development of innovative methodologies or tools that improve the reliability and interpretability of findings.
We welcome a variety of article types, including under the following categories: Original Research, Review, Mini Review, Brief Research Report, and Perspective.
This Research Topic aims to provide a comprehensive platform for studies utilizing traditional methods, AI approaches, or a combination of both in the quest to identify novel biomarkers, drug targets, and therapeutic mechanisms—including those underlying known drug treatments. We seek to explore the challenges and opportunities presented by each methodology independently, as well as their integration. Traditional methods offer robustness and a deep understanding of biological systems, while AI brings efficiency and the ability to analyze complex, large-scale datasets. By welcoming research from both domains, we hope to foster innovation, encourage cross-disciplinary collaboration, and address the limitations inherent in each approach when used in isolation. This collection will showcase how diverse methodologies contribute to advancements in drug discovery and development, ultimately leading to more effective therapeutic strategies.
We invite submissions that utilize traditional experimental methods, artificial intelligence approaches, or a combination of both to advance the discovery of novel biomarkers, drug targets, and therapeutic mechanisms. Topics of interest include:
Discovery of new biomarkers and drug targets using omics technologies, molecular biology techniques, and other traditional methods.
Unveiling novel therapeutic mechanisms in existing drug treatments, including the identification of new biomarkers.
Application of AI methods (e.g., machine learning, deep learning) in biomarker and drug target discovery, therapeutic mechanism elucidation, and drug repurposing strategies.
Studies integrating traditional methods and AI to enhance discovery and validation processes.
Comparative analyses of traditional and AI approaches in pharmacological research.
Development of innovative methodologies or tools that improve the reliability and interpretability of findings.
We welcome a variety of article types, including under the following categories: Original Research, Review, Mini Review, Brief Research Report, and Perspective.
Keywords: Drug Targets, Biomarkers, Traditional Methods, AI, Artificial Intelligence, Therapeutic Mechanisms
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.
