AI-Driven Drug Discovery and Repurposing Frameworks
Why This Special Issue?
The global pharmaceutical landscape is undergoing a transformative shift driven by artificial intelligence (AI), computational biology, and data-driven therapeutic innovation. Traditional drug discovery pipelines are often time-consuming, costly, and associated with high failure rates. In contrast, AI-powered frameworks are enabling faster, more precise, and scalable approaches to identify novel drug targets, optimize molecular design, and repurpose existing therapeutics.
Emerging technologies such as deep learning, network pharmacology, and in silico modeling are redefining how we understand disease pathways and therapeutic interventions. These approaches are accelerating translational outcomes across oncology, infectious diseases, and precision medicine.
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Aim & Scope of This Special Issue
This Special Issue focuses on integrating artificial intelligence, computational pharmacology, and systems biology to advance drug discovery and therapeutic innovation.
We seek high-impact research that bridges:
• AI-driven drug design
• Pharmacogenomics and personalized medicine
• Computational target discovery
• Translational and clinical therapeutics
Topics of Interest Include (but are not limited to)
• AI-driven drug design and molecular optimization
• Deep learning-based drug discovery models
• Drug repurposing and repositioning strategies
• Network pharmacology and systems drug discovery
• In silico screening and virtual compound libraries
• Target identification using computational approaches
• Predictive toxicology and safety modeling
• Precision pharmacogenomics
• Multi-omics integration for therapeutic discovery
• Translational AI in drug development
Editorial Board
Lead Guest Editor
To be Announced
(A senior international expert in AI-driven drug discovery is under final confirmation)
Guest Editor
Dr. Gu Panpan, Ph.D.
Associate Director, Program Management
Takeda Asia Development Center, Shanghai, China
Academic Background:
• Ph.D. in Biology and Medicine – Shanghai Fudan University
• M.Sc. in Biochemistry and Molecular Biology – Fudan University
• B.Sc. in Biotechnology – Jiangsu Normal University
Professional Expertise:
Dr. Gu Panpan is a translational research and pharmaceutical development professional with extensive experience across leading global organizations, including Takeda, GSK, Pfizer, and Boehringer Ingelheim. She specializes in oncology and inflammation therapeutic areas, with a strong focus on drug development strategy, clinical pipeline acceleration, and global regulatory alignment.
Her expertise includes:
• AI-informed drug development strategy and asset progression
• Oncology therapeutics (PD-1, TIGIT, BCMA, and immunotherapy pipelines)
• Translational medicine and clinical development planning
• Cross-functional leadership across global R&D teams
• Regulatory strategy (IND/NDA processes and global submissions)
Research Contributions:
• CRISPR-based molecular diagnostics for antimicrobial resistance (MRSA detection)
• Cancer genomics research (TET2 mutations in breast cancer)
Editorial Role:
As Guest Editor, Dr. Gu brings a unique industry-driven translational perspective, bridging computational drug discovery with real-world clinical and regulatory applications. She supports the evaluation of submissions related to AI-enabled therapeutics, drug repurposing strategies, and next-generation pharmacological innovations.
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Why Submit to This Special Issue?
• Rapid peer review (decision within ~2 weeks)
• Global visibility via open access
• Interdisciplinary exposure (AI + pharmacology + clinical research)
• Editorial leadership with strong industry and translational expertise
• Continuous publication for faster dissemination
Manuscript Submission & Guidelines
Submission Open: April 2026
Final Submission Deadline: August 31, 2026
Submission Portal: https://www.igminresearch.com/quick-submission
Optional: Submit a 250-word abstract for pre-submission feedback.
Article Types Accepted
• Original Research
• Review Articles
• Systematic Reviews
• Short Communications
• Perspectives & Commentaries
Publication Timeline
• Initial Screening: 2–3 days
• First Decision: ~2 weeks
• Revision: 2–3 weeks
• Final Decision: ~1 week
• Publication: 10–14 days post-acceptance
Total: ~5–6 weeks
Ethics & Peer Review
All submissions follow COPE-compliant ethical standards and undergo rigorous double-blind peer review. Final decisions are made independently by the editorial board.
Keywords:
AI drug discovery, drug repurposing, deep learning drug design, network pharmacology, predictive toxicology, pharmacogenomics, in silico screening, computational therapeutics.
