Riding the Rising Waves: New Visions on Systems and Molecular Pharmacology

Dear Colleagues,

Knowing how diseases emerge is key to understanding the underpinning mechanisms that drive disease initiation and progression, and it is a critical motivation for developing effective therapeutics. However, many disease phenotypes have complex traits involving the interplay of a myriad of genes and pathways needed to sustain functional fitness and survival of pathological cells, cellular states, and tissues. Further, there are unmet challenges to understand mechanisms of naïve and acquired drug resistance and factors that affect treatment outcomes. Recent burgeoning of state-of-the-art next-generation sequencing technologies, including single-cell and spatially resolved sequencing methods, have provided unprecedented precision to dissect disease molecular mechanisms right to the cell resolution. In addition, the development of computational algorithms, in particular, the use of systems biology and artificial intelligence (AI), has caused a paradigm shift on how disease targets can be identified and new drugs discovered. Nonetheless, we have not capitalized on the full advantages of the “rising waves” of these cutting-edge technologies to push pharmacology to the next wave of resolution.

In this Special Issue, we welcome original research articles and reviews, but are not limited to, the following areas to “ride” on the rising waves of new-age pharmacology:

• Use of state-of-the-art sequencing technologies to generate multi-dimensional data that help to understand disease etiology and inspire drug discovery.
• Design sequencing and analysis pipelines that facilitate target identification and drug discovery.
• Development of new resources for drug-testing and strategies for novel drug interventions.
• Systems-based mechanistic studies to decipher disease etiology, including understanding drug resistance at single-cell level.
• Build novel computational methods including systems biology and AI that help characterize disease etiology, target identification, and drug development.
• Development of new conceptual ideas on how diseases can be perceived and how new intervention regimens can be designed.

Dr. Cristina Correia
Dr. Choong Ung
Guest Editors

Manuscript Submission Information

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• systems pharmacology
• systems biology
• target identification
• drug discovery and screening
• disease etiology
• artificial intelligence
• machine learning
• state-of-the-art technologies
• conceptual models