Drug discovery process overview

This chapter has provided an overview of the main issues for computing and computational methods to support this work. For the past decade or so, the main limitations that have emerged are not in the amount or type of computational hardware that is available. The real issues are in providing a computational environment for informatics support and streamlining of the calculations. It is here that major efforts are still required to ensure effective integration of the methods and data generated into the drug discovery process. 

This chapter will review some of the important methods for carrying out in vivo absorption and bioavailability studies, as well as attempt to provide an overview of how the information may be used in the drug discovery process. The chapter is aimed at medicinal chemists and thus will focus on the use of animals in discovery phase absorption, distribution, metabolism, and excretion/pharmacokinetic (ADME/PK) studies, rather than the design of studies that are for regulatory submission, or part of a development safety package. 

We will highlight this system by first giving a brief overview of the architecture, followed by some practical examples that cover several common tasks in the drug discovery process. The goal is not to give a detailed account of the methods employed, but rather to illustrate how the system functions in practice. We will present as examples some of the most widely used chemoinformatics applications customized database access, similarity and substructure searching, reactant selection, and library design. 

Having access to metabolism data in the early discovery stage is invaluable. For example, hepatic metabolism data could be used to characterize the pharmacokinetic behavior of a perspective lead. Several studies have reported how metabolism databases and software systems have been used at various settings (272). In this section, we will provide an overview of recent databases, software systems, websites, tools, and services that could be potential starting points for metabolism modeling at various stages in drug discovery process (271,273). 

This introductory chapter gave a quick overview of the drug discovery process. Normal activities required from molecule discovery to launch of the product are... 

Todeschini R, Consonni V (2000) Handbook of molecular descriptors. In Mannhold R, Kubinyi H, Timmerman H (eds), Methods and principles in medicinal chemistry 11. WILEY-VCH, Weinheim. Walters WP, Stahl MT, Murcko MA (1998) Virtual screening — and overview. Drug Discov Today 3 160—178. Ward JH (1963) Hierarchical grouping to optimize an objective function. J Am Stat Assoc 58 236—244. Warmuth MK, Liao J, Ratsch G et al. (2003) Active learning with support vector machines in the drug discovery process. J Chem Inf Comput Sci 43 667—673. 

Without the need of completeness, we discuss the most state-of-the art structure-based VS that are generally used at pharmaceutical industries during the drug discovery process. Our attempt was also to give a picturesque overview on the structure-based VS process and show its effectiveness or its failures through a case study and some success stories during the CADD processes. 

With more than 180 illustrations and an eight-page color insert, this valuable reference explores multiple modern mass spectrometry techniques and strategies. It includes an excellent overview of the entire drug discovery process plus the latest developments on how mass spectrometry is used to support this endeavor. 

After a short overview of existing methods, we will highlight in this chapter on several practical aspects of HR MAS NMR. We will underline the efficiency of HR MAS NMR studies by introducing experiments to quantitatively monitor solid-phase supported reactions and describing a method that allows the use of protonated solvent. Recently published reviews covering NMR methods, analytical tools in combinatorial chemistry and in the drug discovery process may be used to have an easy access to this exciting field [2-4]. 

In Chapter 2, Ganesan gives a historical overview of the development of natural products research and shows the importance of combinatorial chemistry approaches to such compounds in the drug discovery process. Examples from his research help to illustrate the value and future of such an integrated approach to drug discovery using natural-product-like libraries. 

The authors of our chapters are highly experienced industrial ehemists or academics, and it is our hope that the reader of this book will gain an overview of how synthetic organic chemistiy impacts the drug discovery process and a perspective on the current state of the art (and limitations) in this key area. 

Overview of the Current Process of New Drug Discovery and Development... 

The first edition1 of this book was published approximately 13 years ago. Its primary objective was to present an overview and a "roadmap" of the process of new drug discovery and development, particularly oriented to individuals or companies entering the pharmaceutical field. It was written by one of the authors (Smith), with no contributors, and drawn on Smith s experiences in the industry and field over the course of nearly 40 years. In the second edition, the scope of the first book has been expanded and technical details in the form of hard data have been included. In addition to the editors own commentary and contributions, the major part of the book is the result of contributions of experts in the industry. New chapters on risk assessment, international harmonization of drug development and regulation, dietary supplements, patent law, and entrepreneurial startup of a new pharmaceutical company have been added. Some of the important, basic operational aspects of drug discovery and development (e.g., organizational matters, staff requirements, pilot plant operations, etc.) are not repeated in this book but can be found in the first edition. 

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