International Conference on Computational Approaches in Medicinal Chemistry (ICCAIMC - 26)

This track focuses on the latest advancements in molecular modeling techniques that enhance the understanding of drug interactions at the molecular level. Researchers are invited to present their findings on novel computational methods and their applications in medicinal chemistry.

This session will explore innovative computational approaches to drug design, emphasizing the integration of artificial intelligence and machine learning. Contributions that showcase successful case studies and methodologies are highly encouraged.

This track will cover the methodologies and applications of virtual screening in identifying potential drug candidates. Participants are invited to discuss advancements in lead optimization strategies that enhance the efficacy and safety of drug candidates.

This session aims to delve into computational approaches for predicting pharmacokinetics and drug metabolism. Researchers are encouraged to share their insights on modeling absorption, distribution, metabolism, and excretion (ADME) properties.

This track will focus on the development and application of structure-activity relationship (SAR) models in drug discovery. Presentations should highlight novel computational techniques that correlate chemical structure with biological activity.

This session will explore the role of bioinformatics in advancing medicinal chemistry research. Topics may include data mining, genomic analysis, and the integration of biological data with chemical information to facilitate drug discovery.