An Introduction to Generative Drug Discovery

Front pages

List of contributors

Preface

Acknowledgments

Part I – Introduction to Generative Chemical Design

1.         Going Beyond Serendipity: Generative Artificial Intelligence for Drug Discovery

Sean Ekins

2.         Generative Drug Discovery

Quentin Vanhaelen, Alex Aliper and Alex Zhavoronkov

Part II - Generative Chemical Models Based on Language Processing

3.         De novo Drug Design by Chemical Language Modeling

Rıza Özçelik and Francesca Grisoni

Part III - Generative Models and Synthetic Accessibility

4.         Synthesis-based design — A Practical and Generalizable Approach to de novo Molecular Discovery

Wenhao Gao and Connor W. Coley

5.         A Medicinal Chemistry Perspective on Generative AI

Thane Jones and Sean Ekins

6.         MegaSyn for Generative Molecule Design

Joshua S. Harris, Fabio Urbina and Sean Ekins

Part IV - From Models to Practice

7.         Generative Topographic Mapping of Chemical Space in de novo Design

Dragos Horvath, Gilles Marcou and Alexandre Varnek

8.         In Silico ADME/Tox in the Generative AI Paradigm

Sean Ekins, Thomas R. Lane, Joshua S. Harris and Fabio Urbina

9.         The Dark Side - Dual Use Implications of Generative Drug Discovery

Sean Ekins

Part V – The Future

10. Future Labs – Generative Approaches in Self Driving Labs

Sean Ekins

11.       The Future of Generative Drug Discovery  

Fabio Urbina, Joshua S. Harris and Sean Ekins

Index

Biography

Sean Ekins is founder and CEO of Collaborations Pharmaceuticals, Inc (CPI). which is focused on using machine learning approaches for rare and neglected disease drug discovery. Sean graduated from the University of Aberdeen; receiving his M.Sc., Ph.D. in Clinical Pharmacology and D.Sc. in Science. He was a postdoctoral fellow at Lilly Research Laboratories, before working as a senior scientist at Pfizer and then Eli Lilly. He went on to join several startup companies at increasingly senior levels. Since 2005 he has been awarded numerous grants as PI for a wide array of companies totaling over $12.2M, and from 2016 alone has won an additional 20 from NIH and DOD (STTR/SBIR grants, R21, UH2 and R01) totaling over $16.7M for CPI, as well as performing as a consultant on others. He has a passion for advancing new technologies for drug discovery and is a prolific collaborator. He has authored or co-authored >345 peer reviewed papers, book chapters, edited 5 books on different aspects of drug discovery research and topics such as the use of AI. Coverage of his research has also appeared in the Economist, Financial Times, Washington Post, Wired and Scientific American. Alex Tropsha, Ph.D., is K.H. Lee Distinguished Professor in the UNC Eshelman School of Pharmacy, UNC-Chapel Hill. He is an expert in the fields of computational chemistry, cheminformatics and structural bioinformatics who works to develop new methodologies and software tools for computer-assisted drug design. His particular expertise lies in the field of cheminformatics, a discipline where information and informatics methodologies are applied to storing, managing, exploring and exploiting chemical databases. Alex has authored more than 290 peer-reviewed papers and book chapters and edited 2 books on different aspects of drug discovery research. He joined the School’s faculty in 1991 as an assistant professor and director of the Laboratory for Molecular Modeling. He was promoted to associate professor in 1997 and to full professor in 2004 and holds appointments as an adjunct professor in the UNC Department of Biomedical Engineering, Department of Computer Science, Department of Applied Physical Sciences, and is a member of the UNC Lineberger Comprehensive Cancer Center.