Call for Chapters: AI-Powered Advances in Pharmacology

Editors

Aminabee Shaik, V. V. Institute of Pharmaceutical Sciences, India, India

Call for Chapters

Proposals Submission Deadline: January 21, 2024
Full Chapters Due: May 30, 2024
Submission Date: May 30, 2024

Introduction

In the rapidly evolving landscape of pharmaceutical sciences, the integration of artificial intelligence (AI) has emerged as a transformative force, propelling the field into new frontiers of discovery and innovation. "AI-Powered Advances in Pharmacology" delves into the intersection of artificial intelligence and pharmacological research, providing an insightful exploration of how cutting-edge technologies are reshaping drug discovery, development, and personalized medicine. This book navigates through the synergistic relationship between AI algorithms, big data analytics, and traditional pharmacological approaches, offering a comprehensive overview of the revolutionary impact AI is making on understanding diseases, predicting drug responses, and optimizing therapeutic interventions. As we stand at the confluence of artificial intelligence and pharmacology, this book illuminates the potential to accelerate drug development, enhance patient outcomes, and usher in a new era of precision medicine.

Objective

This book seeks to accomplish a thorough exploration of the integration of artificial intelligence (AI) into pharmacological research, aiming to elucidate its transformative impact on drug discovery, development, and personalized medicine. By providing a comprehensive overview and delving into practical applications, it aspires to serve as a valuable resource for researchers, practitioners, and students in the field. The book aims to bridge the gap between traditional pharmacological approaches and AI methodologies, offering insights into how AI advancements can address challenges and propel current research forward. Through case studies and discussions of emerging trends, the book contributes to the evolving landscape of pharmacology, fostering a deeper understanding of diseases, optimizing therapeutic interventions, and shaping the future of precision medicine.

Target Audience

This book is tailored for a diverse audience within the fields of pharmacology, pharmaceutical sciences, and artificial intelligence. Researchers and scientists engaged in drug discovery and development will find valuable insights into how AI technologies can enhance their work, accelerating the identification of potential drug candidates and optimizing therapeutic interventions. Practitioners in the pharmaceutical industry, including pharmacists and clinicians, can benefit from the book's exploration of how AI contributes to personalized medicine and treatment optimization. Additionally, graduate students and academics in pharmacology and related disciplines will find the book to be a comprehensive resource, providing a nuanced understanding of the integration of AI into current research practices. By catering to a broad spectrum of professionals and scholars, the book aims to foster collaboration and inspire further advancements at the intersection of artificial intelligence and pharmacology.

Recommended Topics

Explainable AI in Pharmacology, Quantum Computing Applications in Drug Discovery, AI in Predictive Toxicology, Deep Reinforcement Learning in Pharmacokinetics, AI-Driven Drug Repurposing, Neuropharmacology and Brain-Computer Interfaces, Blockchain in Pharmaceutical Data Management, Genomic Data Integration for Precision Pharmacology, AI-Enhanced Nanomedicine Design, Natural Language Processing in Literature Mining for Drug Discovery.

Submission Procedure

Researchers and practitioners are invited to submit on or before January 21, 2024, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by February 1, 2024 about the status of their proposals and sent chapter guidelines.Full chapters are expected to be submitted by May 30, 2024, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, AI-Powered Advances in Pharmacology. All manuscripts are accepted based on a double-blind peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.



Publisher

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2024.



Important Dates

January 21, 2024: Proposal Submission Deadline
February 1, 2024: Notification of Acceptance
May 30, 2024: Full Chapter Submission
April 7, 2024: Review Results Returned
June 4, 2024: Final Acceptance Notification
June 4, 2024: Final Chapter Submission



Inquiries

Aminabee Shaik
V. V. Institute of Pharmaceutical Sciences, India
aminaammi786@gmail.com



Classifications


Business and Management; Medicine and Healthcare; Media and Communications; Security and Forensics; Social Sciences and Humanities; Physical Sciences and Engineering
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