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Author: Jianling Wang
Publisher: John Wiley & Sons
ISBN: 1118783409
Category : Medical
Languages : en
Pages : 604
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Book Description
This book helps readers integrate in silico, in vitro, and in vivo ADMET (absorption, distribution, metabolism, elimination and toxicity) and PK (pharmacokinetics) data with routine testing applications so that pharmaceutical scientists can diagnose ADMET problems and present appropriate recommendations to move drug discovery programs forward. The book introduces the current clinical practice for drug discovery and development along with the impact on early risk assessment; consolidates the tools and models to intelligently integrate existing in silico, in vitro and in vivo ADMET data; and demonstrates successful cases and lessons learned from real drug discovery and development. In short, it is a book aimed to provide a practical road map for drug discovery and development scientists to generate efficacious and safe drugs for unmet medical needs.
Author: Jianling Wang
Publisher: John Wiley & Sons
ISBN: 1118783409
Category : Medical
Languages : en
Pages : 604
Get Book Here
Book Description
This book helps readers integrate in silico, in vitro, and in vivo ADMET (absorption, distribution, metabolism, elimination and toxicity) and PK (pharmacokinetics) data with routine testing applications so that pharmaceutical scientists can diagnose ADMET problems and present appropriate recommendations to move drug discovery programs forward. The book introduces the current clinical practice for drug discovery and development along with the impact on early risk assessment; consolidates the tools and models to intelligently integrate existing in silico, in vitro and in vivo ADMET data; and demonstrates successful cases and lessons learned from real drug discovery and development. In short, it is a book aimed to provide a practical road map for drug discovery and development scientists to generate efficacious and safe drugs for unmet medical needs.
Author: Li Di
Publisher: Elsevier
ISBN: 0080557619
Category : Science
Languages : en
Pages : 549
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Book Description
Of the thousands of novel compounds that a drug discovery project team invents and that bind to the therapeutic target, typically only a fraction of these have sufficient ADME/Tox properties to become a drug product. Understanding ADME/Tox is critical for all drug researchers, owing to its increasing importance in advancing high quality candidates to clinical studies and the processes of drug discovery. If the properties are weak, the candidate will have a high risk of failure or be less desirable as a drug product. This book is a tool and resource for scientists engaged in, or preparing for, the selection and optimization process. The authors describe how properties affect in vivo pharmacological activity and impact in vitro assays. Individual drug-like properties are discussed from a practical point of view, such as solubility, permeability and metabolic stability, with regard to fundamental understanding, applications of property data in drug discovery and examples of structural modifications that have achieved improved property performance. The authors also review various methods for the screening (high throughput), diagnosis (medium throughput) and in-depth (low throughput) analysis of drug properties. - Serves as an essential working handbook aimed at scientists and students in medicinal chemistry - Provides practical, step-by-step guidance on property fundamentals, effects, structure-property relationships, and structure modification strategies - Discusses improvements in pharmacokinetics from a practical chemist's standpoint
Author: Bernard Testa
Publisher: IOS Press
ISBN: 158603703X
Category : Computers
Languages : en
Pages : 268
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Book Description
A significant contributing factor to the evolution in drug discovery was the methodological and technological revolution with the advent of combinatorial chemistry. This volume summarizes discussions of three aspects of modern drug discovery, that is, priority for targets, early ADMET assessment, and in silico screening.
Author: Katya Tsaioun
Publisher: John Wiley & Sons
ISBN: 0470922818
Category : Medical
Languages : en
Pages : 454
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Book Description
This book guides medicinal chemists in how to implement early ADMET testing in their workflow in order to improve both the speed and efficiency of their efforts. Although many pharmaceutical companies have dedicated groups directly interfacing with drug discovery, the scientific principles and strategies are practiced in a variety of different ways. This book answers the need to regularize the drug discovery interface; it defines and reviews the field of ADME for medicinal chemists. In addition, the scientific principles and the tools utilized by ADME scientists in a discovery setting, as applied to medicinal chemistry and structure modification to improve drug-like properties of drug candidates, are examined.
Author: Souzan B. Yanni
Publisher: John Wiley & Sons
ISBN: 1118838270
Category : Medical
Languages : en
Pages : 354
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Book Description
Serving as a practical handbook about ADMET for drug therapy, this book presents effective technologies, methods, applications, data interpretation, and decision-making tactics for pharmaceutical and preclinical scientists. Chapters cover case studies and in vivo, in vitro, and computational tools for drug discovery and development, with new translational approaches to clinical drug investigations in various human populations. Illustrates ADME properties, from bedside to bench and bench to bedside, for the design of safe and effective medicine in human populations Provides examples that demonstrate the integration of in vitro, in vivo, and in silico data to address human PKPD and TKTD and help determine the proper therapeutic dosage Presents successful tools for evaluating drugs and covers current translational ADMET with regulatory guidelines Offers a hands-on manual for researchers and scientists to design and execute in vitro, in silico, preclinical, and clinical studies Includes discussion of IND / NDA filing and drug labeling to support drug registration and approval
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 1509
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Book Description
In the evolving environment of bioinformatics, genomics, and computational biology, academic scholars are facing a challenging challenge – keeping informed about the latest research trends and findings. With unprecedented advancements in sequencing technologies, computational algorithms, and machine learning, these fields have become indispensable tools for drug discovery, disease research, genome sequencing, and more. As scholars strive to decode the language of DNA, predict protein structures, and navigate the complexities of biological data analysis, the need for a comprehensive and up-to-date resource becomes paramount. The Research Anthology on Bioinformatics, Genomics, and Computational Biology is a collection of a carefully curated selection of chapters that serves as the solution to the pressing challenge of keeping pace with the dynamic advancements in these critical disciplines. This anthology is designed to address the informational gap by providing scholars with a consolidated and authoritative source that sheds light on critical issues, innovative theories, and transformative developments in the field. It acts as a single reference point, offering insights into conceptual, methodological, technical, and managerial issues while also providing a glimpse into emerging trends and future opportunities.
Author: Patrick Schnider
Publisher: Royal Society of Chemistry
ISBN: 1839160497
Category : Science
Languages : en
Pages : 541
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Book Description
The Medicinal Chemist’s Guide to Solving ADMET Challenges summarizes a series of design strategies and tactics that have been successfully employed across pharmaceutical and academic laboratories to solve common ADMET issues. These are exemplified with a curated collection of concrete examples displayed in a highly visual “table-of-contents” style format, allowing readers to rapidly identify the most promising approaches applicable to their own challenges. Each ADMET parameter is introduced in a concise yet comprehensive manner and includes background, relevance and screening strategies. Medicinal chemistry knowledge of how best to modify molecular structure to solve ADMET issues is challenging to retrieve from the literature, public databases and even corporate data warehouses. The Medicinal Chemist’s Guide to Solving ADMET Challenges addresses this gap by presenting state-of-the-art design strategies put together by a global group of experienced medicinal chemists and ADMET experts across academia and the pharmaceutical industry.
Author: Prati Pal Singh
Publisher: Springer Nature
ISBN: 9819923026
Category : Medical
Languages : en
Pages : 774
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Book Description
This book covers several important aspects of pharmaceutical research and innovations. It presents important topics on drug delivery, novel microsponge, nanocrystals, polymeric nanoparticles, peptide synthesis, biopharmaceuticals, pharmacodynamics, yeast flocculation, neuromodulators, innovative drug discovery, pharmacoinformatics, aminoquinoline, thiourea crystals for API synthesis, FDCs and formulations research, ayurveda and natural products, and innovations to militate anti-microbial resistance (AMR). A chapter is devoted to the applications of Artificial Intelligence and Machine Learning in diverse sectors of the pharmaceutical industry, including drug discovery and development, drug repurposing, and improving pharmaceutical productivity. The book also reviews the role of pharmacogenomics and pharmacogenetics in drug development and precision medicine. Further, the book presents an updated summary of recent advances in the fields of nanomedicines and nano-based drug delivery systems. This book is useful to pharmaceutical sciences students, researchers, educators, and professionals in the pharmaceutical industry to understand the intricacies of new drug research and innovations.
Author: RASTOGI, S.C.
Publisher: PHI Learning Pvt. Ltd.
ISBN: 9354437419
Category : Science
Languages : en
Pages : 624
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Book Description
Designed as a comprehensive text for students and professionals pursuing careers in the fields of bioinformatics, molecular biology, pharmacy and drug research, the Fifth Edition continues to offer a fascinating and authoritative treatment of the entire spectrum of bioinformatics, covering a wide range of high-throughput technologies. The content can be used for four core courses: bioinformatics fundamentals, genomics, proteomics and drug discovery and design. The Fifth Edition takes a completely new pedagogical approach and the book is divided into eight distinct Units for the ease of learning: Bioinformatics Fundamentals, Sequence Alignment, Phylogenetic Analysis, Genomics, Protein Structure and Function, Drug Discovery Methods, Drug Design and Development and Integrative Topics. Accordingly, all the chapters are revised and updated in the new edition, besides introduction of seven new chapters and another seven completely re-written chapters. As a student-friendly text, it embodies several pedagogical features such as detailed examples, numerous tables, a large number of diagrams, flow charts and web resources. The book in its present edition should prove an invaluable asset to the students and researchers in the fields of bioinformatics, biotechnology, computer-aided drug design, information technology, medical diagnostics, molecular biology and pharmaceutical sciences. NEW TO THE FIFTH EDITION • Re-written chapters — Biological database search and data retrieval, Pair-wise alignment of sequences, PSSMs and Hidden Markov Models, Gene Mapping, Gene Prediction, Protein Structure Overview and Protein Structure Prediction. • Inclusion of new chapters—Scoring Matrices, Gene Sequencing, Regulatory Elements Prediction, Comparative Genomics, Protein Structure Databases, Protein Function Prediction and Potential Drug Targets. KEY FEATURES • Covers the field of bioinformatics in a complete and integrated approach – moving from the fundamentals to theory and practical applications. • State-of-the-art technologies for gene identification, molecular modeling and monitoring of cellular processes. • Data mining, data curation and analysis, classification, interpretation and efficient structure determination of genomes and proteomes. • Companion website provides useful resources for the teachers as well as for the students. So, visit Learning Centre https:// www.phindia.com/bioinformatics_mendiratta_rastogi to have access of Lecture notes, solutions manual, MCQs, problems set for practice, glossary of important terms, etc. TARGET AUDIENCE • UG and PG Students of Bioinformatics, Biotechnology, Molecular Biology and Pharmacy.
Author: Huixiao Hong
Publisher: Springer Nature
ISBN: 3031207300
Category : Medical
Languages : en
Pages : 654
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Book Description
This book is a collection of machine learning and deep learning algorithms, methods, architectures, and software tools that have been developed and widely applied in predictive toxicology. It compiles a set of recent applications using state-of-the-art machine learning and deep learning techniques in analysis of a variety of toxicological endpoint data. The contents illustrate those machine learning and deep learning algorithms, methods, and software tools and summarise the applications of machine learning and deep learning in predictive toxicology with informative text, figures, and tables that are contributed by the first tier of experts. One of the major features is the case studies of applications of machine learning and deep learning in toxicological research that serve as examples for readers to learn how to apply machine learning and deep learning techniques in predictive toxicology. This book is expected to provide a reference for practical applications of machine learning and deep learning in toxicological research. It is a useful guide for toxicologists, chemists, drug discovery and development researchers, regulatory scientists, government reviewers, and graduate students. The main benefit for the readers is understanding the widely used machine learning and deep learning techniques and gaining practical procedures for applying machine learning and deep learning in predictive toxicology.
