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.

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.

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

A key resource for toxicologists across a broad spectrum of fields, this book offers a comprehensive analysis of molecular modelling approaches and strategies applied to risk assessment for pharmaceutical and environmental chemicals. • Provides a perspective of what is currently achievable with computational toxicology and a view to future developments • Helps readers overcome questions of data sources, curation, treatment, and how to model / interpret critical endpoints that support 21st century hazard assessment • Assembles cutting-edge concepts and leading authors into a unique and powerful single-source reference • Includes in-depth looks at QSAR models, physicochemical drug properties, structure-based drug targeting, chemical mixture assessments, and environmental modeling • Features coverage about consumer product safety assessment and chemical defense along with chapters on open source toxicology and big data

The sudden outbreak of the COVID-19 pandemic has curbed human lifestyle by imposing restrictions on regular daily movements that had been taken for granted. Due to the pandemic, the welfare segment has received more attention, and every possible effort is being made to prioritize the services at the top. This can be made possible while using the latest tools, technologies, and resources that impact the human culture and welfare of well-being. Novel methods and devices that make the welfare services more efficient, adaptive, transparent, and cost-effective need to be explored. The Handbook of Research on Lifestyle Sustainability and Management Solutions Using AI, Big Data Analytics, and Visualization offers extensive research on lifestyle management and services that contribute towards indication, detection, conduction, protection, and technological enhancement including machine learning, deep learning, artificial intelligence, big data analytics, and visualization. It also provides mechanisms that can improve lifestyle monitoring and help in increasing the immunity of the human body. Covering topics such as big data, robot therapy, and wearable technology, it is ideal for students, researchers, technologists, IT specialists, computer engineers, systems engineers, data scientists, doctors, hospital administrators, engineers, academicians, and technology providers.

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.

Computational Approaches for Novel Therapeutic and Diagnostic Designing to Mitigate SARS-CoV2 Infection: Revolutionary Strategies to Combat Pandemics compiles information about various computational bioinformatic approaches that can help combat viral infection. The book includes working knowledge of various molecular docking and molecular dynamic simulation approaches that have been exploited for drug repurposing and drug designing purpose. In addition, it sheds light on reverse vaccinomics and immunoinformatic approaches for vaccine designing against SARS-CoV2 infection. This book is an essential resource for researchers, bioinformaticians, computational biologists, computational chemists and pharmaceutical companies who are working on the development of effective and specific therapeutic interventions and point-of-care diagnostic devices using various computational approaches. - Covers computational based approaches for designing and repurposing drugs - Discusses immunoinformatic and reverse vaccinomic approaches for effective vaccine design - Categorizes information about artificial intelligence-based drug screening and diagnostic tools