Impact of high-throughput screening in biomedical research

Ricardo Macarrón; Martyn Banks; Dejan Bojanic; David Burns; Dragan A. Cirovic; Tina Garyantes; Darren V. S. Green; Robert Hertzberg; William P. Janzen; Jeff W. Paslay; Ulrich Schopfer; G. Sitta Sittampalam

doi:10.1038/nrd3368

Keywords

Drug discoveryThroughputHigh-throughput screeningRisk analysis (engineering)BusinessPharmaceutical industryProductivityComputer scienceData scienceBiotechnologyBiologyBioinformaticsEconomicsEconomic growthTelecommunications

Affiliated Institutions

Related Publications

Diagnosing the decline of major pharmaceutical research laboratories: A prescription for drug companies

Jerry A. Weisbach , Walter H. Moos

Abstract Despite dramatically increasing expenditures for in‐house pharmaceutical research and development (R&D) at major drug companies, few internally discovered, breakthr...

1995 Drug Development Research 40 citations

A Structure-Based Drug Discovery Paradigm

Maria Batool , Sheikh Bilal Ahmad , Sangdun Choi

Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structura...

2019 International Journal of Molecular Sc... 671 citations

Enrichment of High-Throughput Screening Data with Increasing Levels of Noise Using Support Vector Machines, Recursive Partitioning, and Laplacian-Modified Naive Bayesian Classifiers

Meir Glick , Jeremy L. Jenkins , James H. Nettles +2 more

High-throughput screening (HTS) plays a pivotal role in lead discovery for the pharmaceutical industry. In tandem, cheminformatics approaches are employed to increase the probab...

2005 Journal of Chemical Information and M... 104 citations

Three-Dimensional in Vitro Cell Culture Models in Drug Discovery and Drug Repositioning

Sigrid A. Langhans

Drug development is a lengthy and costly process that proceeds through several stages from target identification to lead discovery and optimization, preclinical validation and c...

2018 Frontiers in Pharmacology 1449 citations

oncoPredict: an R package for predicting <i>in vivo</i> or cancer patient drug response and biomarkers from cell line screening data

Danielle Maeser , Robert F. Gruener , R. Stephanie Huang

Abstract Cell line drug screening datasets can be utilized for a range of different drug discovery applications from drug biomarker discovery to building translational models of...

2021 Briefings in Bioinformatics 1489 citations

Publication Info

Year: 2011
Type: review
Volume: 10
Issue: 3
Pages: 188-195
Citations: 1288
Access: Closed

External Links

View on DOI.org

Social Impact

Altmetric

Impact of high-throughput screening in biomedical research

PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

1288

OpenAlex

Cite This

APA Style

                            
                                
                                    Ricardo Macarrón, 
                                
                                    Martyn Banks, 
                                
                                    Dejan Bojanic
                                
                                et al.
                            
                            (2011). 
                            Impact of high-throughput screening in biomedical research. 
                            Nature Reviews Drug Discovery
                            , 10
                            (3)
                            , 188-195.
                            https://doi.org/10.1038/nrd3368
                        

Identifiers

DOI: 10.1038/nrd3368