scholarly journals Computational chemistry, data mining, high-throughput synthesis and screening - informatics and integration in drug discovery

2001 ◽  
Vol 23 (6) ◽  
pp. 191-192 ◽  
Author(s):  
Charles J. Manly
Keyword(s):  
Data Mining ◽  
Drug Discovery ◽  
Computational Chemistry ◽  
High Throughput ◽  
Combinatorial Chemistry ◽  
High Throughput Screening ◽  
Pharmaceutical Research ◽  
Technical Note ◽  
Laboratory Automation ◽  
Chemistry Data

Drug discovery today includes considerable focus of laboratory automation and other resources on both combinatorial chemistry and high-throughput screening, and computational chemistry has been a part of pharmaceutical research for many years. The real benefit of these technologies is beyond the exploitation of each individually. Only recently have significant efforts focused on effectively integrating these and other discovery disciplines to realize their larger potential. This technical note will describe one example of these integration efforts.

scholarly journals Managing laboratory automation: integration and informatics in drug discovery

2000 ◽  
Vol 22 (6) ◽  
pp. 169-170 ◽  
Author(s):  
Charles J. Manly
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
Combinatorial Chemistry ◽  
High Throughput Screening ◽  
Laboratory Automation ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Modern Drug

Drug discovery today requires the focused use of laboratory automation and other resources in combinatorial chemistry and high-throughput screening (HTS). The ultimate value of both combinatorial chemistry and HTS technologies and the lasting impact they will have on the drug discovery process is a chapter that remains to be written. Central to their success and impact is how well they are integrated with each other and with the rest of the drug discovery processes-informatics is key to this success. This presentation focuses on informatics and the integration of the disciplines of combinatorial chemistry and HTS in modern drug discovery. Examples from experiences at Neurogen from the last five years are described.

Drug Discovery

2019 ◽  
pp. 1-46
Author(s):  
S. Lakshmana Prabu
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
Combinatorial Chemistry ◽  
High Throughput Screening ◽  
Development Stage ◽  
Synthetic Chemistry ◽  
Success Rates ◽  
Herbal Plants ◽  
Pharmaceutical Industries ◽  
The 1960S

Modern chemistry foundations were made in between the 18th and 19th centuries and have been extended in 20th century. R&D towards synthetic chemistry was introduced during the 1960s. Development of new molecular drugs from the herbal plants to synthetic chemistry is the fundamental scientific improvement. About 10-14 years are needed to develop a new molecule with an average cost of more than $800 million. Pharmaceutical industries spend the highest percentage of revenues, but the achievement of desired molecular entities into the market is not increasing proportionately. As a result, an approximate of 0.01% of new molecular entities are approved by the FDA. The highest failure rate is due to inadequate efficacy exhibited in Phase II of the drug discovery and development stage. Innovative technologies such as combinatorial chemistry, DNA sequencing, high-throughput screening, bioinformatics, computational drug design, and computer modeling are now utilized in the drug discovery. These technologies can accelerate the success rates in introducing new molecular entities into the market.

scholarly journals High throughput drug profiling

2000 ◽  
Vol 22 (6) ◽  
pp. 171-173 ◽  
Author(s):  
Michael Entzeroth ◽  
Béatrice Chapelain ◽  
Jacques Guilbert ◽  
Valérie Hamon
Keyword(s):  
Data Mining ◽  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Great Increase

High throughput screening has significantly contributed to advances in drug discovery. The great increase in the number of samples screened has been accompanied by increases in costs and in the data required for the investigated compounds. High throughput profiling addresses the issues of compound selectivity and specificity. It combines conventional screening with data mining technologies to give a full set of data, enabling development candidates to be more fully compared.

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
Data Mining ◽  
Refractive Index ◽  
High Throughput ◽  
First Principles ◽  
High Throughput Screening ◽  
Large Scale ◽  
Computational Study ◽  
High Refractive Index ◽  
Structural Features ◽  
Learning Program

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>

Upscaling and Automation of Electrophysiology: Toward High Throughput Screening in Ion Channel Drug Discovery

2003 ◽  
Vol 9 (1) ◽  
pp. 49-58
Author(s):  
Margit Asmild ◽  
Nicholas Oswald ◽  
Karen M. Krzywkowski ◽  
Søren Friis ◽  
Rasmus B. Jacobsen ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Ion Channel ◽  
High Throughput ◽  
High Throughput Screening
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