A Road Map for 21st Century Drug Discovery
May 26, 2016
Bioinformatics and Computational Biology in Drug Discovery and Development
William Loging, editor
Cambridge University Press, 2016
William Loging, editor
Cambridge University Press, 2016
By Mary Chitty, Library Director & Taxonomist, Cambridge Healthtech Institute
May 26, 2016 | William T. Loging is Associate Professor of Genetics and Genomic Sciences, and Director of Production Bioinformatics at the Icahn School of Medicine at Mount Sinai, New York. He has assembled a Cracker Jack team of interdisciplinary experts, with both deep experience and fresh ideas to outline a road map for 21st century drug discovery and development. Written to bridge the gaps between informatics scientists, managers, and biologists, Bioinformatics and Computational Biology in Drug Discovery and Development offers a guide to critical transformative changes.
We currently hold over-simplified views of disease, Loging contends, but to take advantage of new technologies to understand individual variations in disease processes, our understanding must advance to a deeper view of biological networks, pathways, and the causal relationships that may better predict drug efficacy. Better grasping these relationships will be the foundation for interrupting the current paradigm of diminishing marginal investment returns in pharmaceutical research and development.
Bioinformatics, computational biology, and technology are clearly important parts of the equation. But it is also welcome to see acknowledgment that IT is not a silver bullet, and user-centric design is a key component. Encouraging earlier (and cheaper) failing of compounds—and repurposing of existing compounds—can be important.
Since the Human Genome was “sequenced” in 2003, the amount of money spent on pharmaceutical Research & Development and the number of compounds in development have increased, but the average number of drugs approved by the FDA has declined. This is clearly not sustainable. At the same time there are areas of unmet medical need, and we are beginning to see evidence that companies which focus on better understanding of biology and mechanisms are enjoying greater success. The bar has also been raised both on demonstrating drug efficacy and safety. Many silos need to be bridged, and highly complex systems with high dimensional data must be analyzed as we combine data from electronic medical records, PET and MRI scans, DNA or RNA sequencing, tissue samples, pathology reports, and wearables producing ever increasing quantities of longitudinal real world data.
This title represents a model of how to start—and continue—to think differently about the enormously promising but challenging business of pharmaceuticals and precision medicine. This is not textbook, but bleeding edge, pushing-the-envelope science, aiming to transform lives and alleviate suffering. There are many ways to fail and a limited number of chances to succeed. This book offers both powerful and practical guidelines, real life case studies, and insights into the art and science of drug discovery.
Recommended for people working in these trenches and for any of those trying to understand and improve productivity in the long, expensive, and complicated process of getting new drugs to market—and keeping them there.
May 26, 2016 | William T. Loging is Associate Professor of Genetics and Genomic Sciences, and Director of Production Bioinformatics at the Icahn School of Medicine at Mount Sinai, New York. He has assembled a Cracker Jack team of interdisciplinary experts, with both deep experience and fresh ideas to outline a road map for 21st century drug discovery and development. Written to bridge the gaps between informatics scientists, managers, and biologists, Bioinformatics and Computational Biology in Drug Discovery and Development offers a guide to critical transformative changes.
We currently hold over-simplified views of disease, Loging contends, but to take advantage of new technologies to understand individual variations in disease processes, our understanding must advance to a deeper view of biological networks, pathways, and the causal relationships that may better predict drug efficacy. Better grasping these relationships will be the foundation for interrupting the current paradigm of diminishing marginal investment returns in pharmaceutical research and development.
Bioinformatics, computational biology, and technology are clearly important parts of the equation. But it is also welcome to see acknowledgment that IT is not a silver bullet, and user-centric design is a key component. Encouraging earlier (and cheaper) failing of compounds—and repurposing of existing compounds—can be important.
Since the Human Genome was “sequenced” in 2003, the amount of money spent on pharmaceutical Research & Development and the number of compounds in development have increased, but the average number of drugs approved by the FDA has declined. This is clearly not sustainable. At the same time there are areas of unmet medical need, and we are beginning to see evidence that companies which focus on better understanding of biology and mechanisms are enjoying greater success. The bar has also been raised both on demonstrating drug efficacy and safety. Many silos need to be bridged, and highly complex systems with high dimensional data must be analyzed as we combine data from electronic medical records, PET and MRI scans, DNA or RNA sequencing, tissue samples, pathology reports, and wearables producing ever increasing quantities of longitudinal real world data.
This title represents a model of how to start—and continue—to think differently about the enormously promising but challenging business of pharmaceuticals and precision medicine. This is not textbook, but bleeding edge, pushing-the-envelope science, aiming to transform lives and alleviate suffering. There are many ways to fail and a limited number of chances to succeed. This book offers both powerful and practical guidelines, real life case studies, and insights into the art and science of drug discovery.
Recommended for people working in these trenches and for any of those trying to understand and improve productivity in the long, expensive, and complicated process of getting new drugs to market—and keeping them there.
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