Artificial Intelligence and Machine Learning in Pharmaceutical Chemistry

The "Artificial Intelligence and Machine Learning in Pharmaceutical Chemistry" track at PHARMACEUTICAL CHEMISTRY 2025 explores the transformative impact of AI and machine learning technologies on drug discovery, development, and optimization. Researchers submitting abstracts for this track will investigate how advanced computational algorithms are revolutionizing pharmaceutical chemistry by enhancing predictive models, automating data analysis, and accelerating drug development pipelines.

Attendees can expect in-depth discussions on the integration of AI and machine learning in various aspects of pharmaceutical chemistry, including virtual screening, predictive modeling, and optimizing drug formulations. The track will highlight applications such as AI-driven drug discovery platforms, machine learning algorithms for predicting drug interactions and side effects, and the use of deep learning to analyze complex biological data.

Presentations will cover case studies demonstrating successful AI and machine learning applications, as well as challenges and future directions in this rapidly evolving field. By participating, attendees will gain valuable insights into how these technologies are shaping the future of pharmaceutical chemistry, driving innovation, and improving efficiency in drug development.

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