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As per available reports about 24 relevant Journals, 47 Conferences are presently dedicated exclusively to Chemoinformatics and about 570 articles are being published on Chemoinformatics.
Chemoinformatics is a relatively new discipline. Actually, it has emerged from several older disciplines such as computational chemistry, computer chemistry, chemometrics, QSAR, chemical information, etc. The names identifying these older disciplines can be controversial, but they have been studied for many years. Cheminformatics involves the use of computer technologies to process chemical data. chemoinformatics should be able to extract knowledge from large-scale raw HTS databases in a shorter time periods, chemoinformatics should be able to provide efficient in silico tools to predict ADMET properties, This is normally very hard to do. One of the earliest chemoinformatics studies involved chemical structure representations, such as structural descriptors. Chemoinformatics and advanced informative technology in Chemical sciences are the wings included in Medicinal Chemistry including subsessions chemometrics, QSAR, chemical information, Computer Aided Drug Design
The focus is placed on four traditional research areas: chemical database systems, computer-assisted structure elucidation systems, computer-assisted synthesis design systems, and 3D structure builders. Considering the fact that computer technology has been one of the major driving forces of the development of chemoinformatics, each section will start from a brief description of the new advances in computer technology of each decade. The summary and future prospects are given in the last section. Concepts are constantly evolving in response to changing economic opportunities and technological advancements. Traditional medicinal chemistry paradigms, relying initially on ‘wet’ chemistry followed by screening and lead optimizations, are expensive and time consuming. On the other hand, initial in silico screening that guides the synthesis and screening of selected compounds has proven to be a better approach to accelerate drug discovery and reduce the cost of the discovery phase.
Chemoinformatics is a relatively new discipline. Actually, it has emerged from several older disciplines such as computational chemistry, computer chemistry, chemometrics, QSAR, chemical information, etc. The names identifying these older disciplines can be controversial, but they have been studied for many years. Cheminformatics involves the use of computer technologies to process chemical data.The average cost of creating a NCE in a major pharmaceutical company was estimated at around $7,500/compound. In order to reduce costs, pharmaceutical companies have had to find new technologies to replace the old “hand-crafted” synthesis and testing NCE approaches. Since 1980, with the advent of high throughput screening (HTS), automated techniques have made possible robotized screening. In response to the increased demand for new compounds by biologists, chemists started using combinatorial chemical technologies to produce more new compounds in shorter periods. By increasing the capabilities of making and testing compounds, it was hoped that the drug discovery process could be accelerated dramatically. Unfortunately, this did not turn out to be the case. Seeking the reasons for these disappointing results, it was believed that increasing the chemical diversity of compound libraries would enhance the drug discovery process. Chemoinformatics approaches would now be introduced in order to optimize the chemical diversity of libraries.
Initial activities in the field started with chemical document processing. What differentiates chemical data processing from other data processing is that chemical data involves the requirement to work with chemical structures. This requirement necessitated the introduction of special approaches to represent, store and retrieve structures in a computer system. Another challenge faced by this new field was to establish clear relationships between structural patterns and activities or properties, chemoinformatics should be able to extract knowledge from large-scale raw HTS databases in a shorter time periods, chemoinformatics should be able to provide efficient in silico tools to predict ADMET properties, This is normally very hard to do. One of the earliest chemoinformatics studies involved chemical structure representations, such as structural descriptors.
Market Analysis:
The global chemoinformatics market was valued at nearly $2.8 billion in 2011, nearly $3.2 billion in 2012, and is forecast to grow to nearly $7.5 billion by 2017 after increasing at a compound annual growth rate (CAGR) of 18.7%. Analyses of global market trends, with data from 2011 and 2012, and projections of compound annual growth rates (CAGRs) through 2017.
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This page was last updated on May 11, 2025
