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| Author | : Zunnan Huang |
| Publisher | : Frontiers Media SA |
| Total Pages | : 135 |
| Release | : 2021-03-15 |
| Genre | : Science |
| ISBN | : 2889666018 |
| Author | : Ganji Purnachandra Nagaraju |
| Publisher | : Elsevier |
| Total Pages | : 460 |
| Release | : 2023-03-22 |
| Genre | : Computers |
| ISBN | : 0443152810 |
Computational Methods in Drug Discovery and Repurposing for Cancer Therapy provides knowledge about ongoing research as well as computational approaches for drug discovery and repurposing for cancer therapy. The book also provides detailed descriptions about target molecules, pathways, and their inhibitors for easy understanding and applicability. The book discusses tools and techniques such as integrated bioinformatics approaches, systems biology tools, molecular docking, computational chemistry, artificial intelligence, machine learning, structure-based virtual screening, biomarkers, and transcriptome; those are discussed in the context of different cancer types, such as colon, pancreatic, glioblastoma, endometrial, and retinoblastoma, among others. This book is a valuable resource for researchers, students, and members of the biomedical and medical fields who want to learn more about the use of computational modeling to better tailor the treatment for cancer patients. Discusses in silico remodeling of effective phytochemical compounds for discovering improved anticancer agents for substantial/significant cancer therapy Covers potential tools of bioinformatics that are applied toward discovering new targets by drug repurposing and strategies to cure different types of cancers Demonstrates the significance of computational and artificial intelligence approaches in anticancer drug discovery Explores how these various advances can be integrated into a precision and personalized medicine approach that can eventually enhance patient care
| Author | : Javier Luque |
| Publisher | : Royal Society of Chemistry |
| Total Pages | : 443 |
| Release | : 2012 |
| Genre | : Medical |
| ISBN | : 1849733538 |
This title covers a wide range of topics relevant to the development of drugs. It provides a comprehensive description of the major methodological strategies available for rational drug discovery.
| Author | : Tripathi, Rati Kailash Prasad |
| Publisher | : IGI Global |
| Total Pages | : 337 |
| Release | : 2024-04-22 |
| Genre | : Medical |
| ISBN | : |
The world of pharmaceutical research is moving at lightning speed, and the age-old approach to drug discovery faces many challenges. It's a fascinating time to be on the cutting edge of medical innovation, but it's certainly not without its obstacles. The process of developing new drugs is often time-consuming, expensive, and fraught with uncertainty. Researchers are constantly seeking ways to streamline this process, reduce costs, and increase the success rate of bringing new drugs to market. One promising solution lies in the convergence of pharmacy science and engineering, particularly in computational drug discovery. Converging Pharmacy Science and Engineering in Computational Drug Discovery presents a comprehensive solution to these challenges by exploring the transformative synergy between pharmacy science and engineering. This book demonstrates how researchers can expedite the identification and development of novel therapeutic compounds by harnessing the power of computational approaches, such as sophisticated algorithms and modeling techniques. Through interdisciplinary collaboration, pharmacy scientists and engineers can revolutionize drug discovery, paving the way for more efficient and effective treatments. This book is an invaluable resource for pharmaceutical scientists, researchers, and engineers seeking to enhance their understanding of computational drug discovery. This book inspires future innovations by showcasing cutting-edge methodologies and innovative research at the intersection of pharmacy science and engineering. It contributes to the ongoing evolution of pharmaceutical research. It offers practical insights and solutions that will shape the future of drug discovery, making it essential reading for anyone involved in the pharmaceutical industry.
| Author | : Alessandro Laganà |
| Publisher | : Springer Nature |
| Total Pages | : 341 |
| Release | : 2022-03-01 |
| Genre | : Medical |
| ISBN | : 303091836X |
Precision medicine holds great promise for the treatment of cancer and represents a unique opportunity for accelerated development and application of novel and repurposed therapeutic approaches. Current studies and clinical trials demonstrate the benefits of genomic profiling for patients whose cancer is driven by specific, targetable alterations. However, precision oncologists continue to be challenged by the widespread heterogeneity of cancer genomes and drug responses in designing personalized treatments. Chapters provide a comprehensive overview of the computational approaches, methods, and tools that enable precision oncology, as well as related biological concepts. Covered topics include genome sequencing, the architecture of a precision oncology workflow, and introduces cutting-edge research topics in the field of precision oncology. This book is intended for computational biologists, bioinformaticians, biostatisticians and computational pathologists working in precision oncology and related fields, including cancer genomics, systems biology, and immuno-oncology.
| Author | : William T. Loging |
| Publisher | : Cambridge University Press |
| Total Pages | : 255 |
| Release | : 2016-03-17 |
| Genre | : Science |
| ISBN | : 1316538818 |
Computational biology drives discovery through its use of high-throughput informatics approaches. This book provides a road map of the current drug development process and how computational biology approaches play a critical role across the entire drug discovery pipeline. Through the use of previously unpublished, real-life case studies the impact of a range of computational approaches are discussed at various phases of the pipeline. Additionally, a focus section provides innovative visualisation approaches, from both the drug discovery process as well as from other fields that utilise large datasets, recognising the increasing use of such technology. Serving the needs of early career and more experienced scientists, this up-to-date reference provides an essential introduction to the process and background of drug discovery, highlighting how computational researchers can contribute to that pipeline.
| Author | : Rupesh Kumar Gautam |
| Publisher | : Elsevier |
| Total Pages | : 364 |
| Release | : 2023-02-15 |
| Genre | : Medical |
| ISBN | : 0323993737 |
Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics. Explains computer use in pharmacology using real-life case studies Provides information about biological activities using computer technology, thus allowing for the possible reduction of the number of animals used for research Describes the role of AI in pharmacology and applications of CADD in various diseases
| Author | : Azam Peyvandipour |
| Publisher | : |
| Total Pages | : 137 |
| Release | : 2020 |
| Genre | : Bioinformatics |
| ISBN | : |
The traditional drug discovery process is extremely slow and costly. More than 90% of drugs fail to pass beyond the early stage of development and toxicity tests, and many of the drugs that go through early phases of the clinical trials fail because of adverse reactions, side effects, or lack of efficiency. In spite of unprecedented investments in research and development (R&D), the number of new FDA-approved drugs remains low, reflecting the limitations of the current R&D model. In this context, finding new disease indications for existing drugs sidesteps these issues and can therefore increase the available therapeutic choices at a fraction of the cost of new drug development. In this thesis, we introduce a drug repurposing approach that takes advantage of prior knowledge of drug targets, disease-related genes, and signaling pathways to construct a drug-disease network composed of the genes that are most likely perturbed by a drug. Systems biology can be used as an effective platform in drug discovery and development by leveraging the understanding of interactions between the different system components. By performing a system-level analysis on this network, our approach estimates the amount of perturbation caused by drugs and diseases and discovers drugs with the potential desired effects on the given disease. Next, we develop a stable clustering method that employs a bootstrap approach to identify the stable clusters of cells. We show that strong patterns in single cell data will remain despite small perturbations. The results, that are validated based on well-known metrics, show that using this approach yields improvement in correctly identifying the cell types, compared to other existing methods.
| Author | : Josep Bassaganya-Riera |
| Publisher | : Springer |
| Total Pages | : 88 |
| Release | : 2018-04-25 |
| Genre | : Medical |
| ISBN | : 3319732382 |
Accelerated Path to Cures provides a transformative perspective on the power of combining advanced computational technologies, modeling, bioinformatics and machine learning approaches with nonclinical and clinical experimentation to accelerate drug development. This book discusses the application of advanced modeling technologies, from target identification and validation to nonclinical studies in animals to Phase 1-3 human clinical trials and post-approval monitoring, as alternative models of drug development. As a case of successful integration of computational modeling and drug development, we discuss the development of oral small molecule therapeutics for inflammatory bowel disease, from the application of docking studies to screening new chemical entities to the development of next-generation in silico human clinical trials from large-scale clinical data. Additionally, this book illustrates how modeling techniques, machine learning, and informatics can be utilized effectively at each stage of drug development to advance the progress towards predictive, preventive, personalized, precision medicine, and thus provide a successful framework for Path to Cures.
| Author | : Nosheen Masood |
| Publisher | : Springer Nature |
| Total Pages | : 499 |
| Release | : 2020-03-20 |
| Genre | : Medical |
| ISBN | : 9811510679 |
This book concisely describes the role of omics in precision medicine for cancer therapies. It outlines our current understanding of cancer genomics, shares insights into the process of oncogenesis, and discusses emerging technologies and clinical applications of cancer genomics in prognosis and precision-medicine treatment strategies. It then elaborates on recent advances concerning transcriptomics and translational genomics in cancer diagnosis, clinical applications, and personalized medicine in oncology. Importantly, it also explains the importance of high-performance analytics, predictive modeling, and system biology in cancer research. Lastly, the book discusses current and potential future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.
