This book describes ways to invent and commercialize biomedicines in a more time and cost-efficient manner. Failure to translate a discovery into a marketed drug denies us an opportunity to improve the lives of patients who do not have access to effective therapies. Here, the authors provide a greater understanding of biopharmaceutical informatics.
This book describes ways to invent and commercialize biomedicines in a more time and cost-efficient manner. Failure to translate a discovery into a marketed drug denies us an opportunity to improve the lives of patients who do not have access to effective therapies. Here, the authors provide a greater understanding of biopharmaceutical informatics.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr. Sandeep Kumar is currently a Distinguished Fellow (Executive Director) at the department of Computational Science in Moderna Therapeutics, Cambridge, MA where he leads Molecular Design and Modeling team. Sandeep Kumar holds a Ph.D. in Computational Biophysics and has over 25 years of experience researching protein structure - Function relationships. Sandeep Kumar has so far contributed towards more than 100 research articles, reviews, book chapters, and has previously edited a book entitled "Developability of Biotherapeutics: Computational Approaches". Sandeep has been contributing towards discovery and development of numerous monoclonal antibodies, antibody drug conjugates, bispecific and multi-specific modalities, as well as vaccines. Based on the insights gained from these experiences, Sandeep has been advocating for Biopharmaceutical Informatics, a strategic vision dedicated to synergistic use of computation and experimentation towards a cost effective and more efficient discovery and development of Biotherapeutics. More recently, he is promoting the concept of DAbI (Discovery of Antibodies in silico) where he sees an opportunity for generative AI to not only accelerate biopharmaceutical drug design but also to expand the antigen space druggable by antibody-based biotherapeutics. Dr. Andrew Nixon is currently Vice President, Biotherapeutics Molecule Discovery at Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT, USA. Andy earned his Ph.D. in Physical Biochemistry from the University of London for studies completed at the MRC's National Institute for Medical Research. Andy has over 20 years of experience in biologic drug discovery and has contributed to over 100 antibody discovery programs resulting in numerous clinical candidates and approved biologics including TAKHZYRO, a fully human antibody inhibitor of plasma kallikrein.
Inhaltsangabe
Foreword Preface About the editors List of contributors 1. Biopharmaceutical Informatics: An Introduction 2. Digital transformation in the biopharmaceutical industry: rebuilding the way we discover complex therapeutics 3. Computational protein design strategies for optimization of antigen generation to drive antibody discovery 4. Bioinformatic Analyses of Antibody Repertoires and Their Roles in Modern Antibody Drug Discovery 5. Applications of Artificial Intelligence and Machine Learning Towards Antibody Discovery and Development 6. From Deep Generative Models to Structure-Based Simulations: Computational Approaches for Antibody Design 7. Computational biophysical analyses of antibody structure-function relationships with emphasis on therapeutic antibody-based biologics 8. Use of molecular simulations to understand structural dynamics of antibodies 9. Considerations of developability during the early stages of antibody drug discovery and design 10. In Silico Approaches to Deliver Better Antibodies by Design - The Past, the Present and the Future 11. Use of systems biology approaches towards target discovery, validation, and drug development 12. Recent advances in PK/PD and Quantitative Systems Pharmacology (QSP) models for biopharmaceuticals 13. The Artificial Intelligence Revolution: Transforming the Design and Optimization of Multispecific Antibodies Index.
Foreword Preface About the editors List of contributors 1. Biopharmaceutical Informatics: An Introduction 2. Digital transformation in the biopharmaceutical industry: rebuilding the way we discover complex therapeutics 3. Computational protein design strategies for optimization of antigen generation to drive antibody discovery 4. Bioinformatic Analyses of Antibody Repertoires and Their Roles in Modern Antibody Drug Discovery 5. Applications of Artificial Intelligence and Machine Learning Towards Antibody Discovery and Development 6. From Deep Generative Models to Structure-Based Simulations: Computational Approaches for Antibody Design 7. Computational biophysical analyses of antibody structure-function relationships with emphasis on therapeutic antibody-based biologics 8. Use of molecular simulations to understand structural dynamics of antibodies 9. Considerations of developability during the early stages of antibody drug discovery and design 10. In Silico Approaches to Deliver Better Antibodies by Design - The Past, the Present and the Future 11. Use of systems biology approaches towards target discovery, validation, and drug development 12. Recent advances in PK/PD and Quantitative Systems Pharmacology (QSP) models for biopharmaceuticals 13. The Artificial Intelligence Revolution: Transforming the Design and Optimization of Multispecific Antibodies Index.
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