September 9, 2010
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About Us

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Bio-IT World provides breaking news, analysis, and opinion on enabling technologies that drive biomedical research and drug development, with emphasis on predictive biology, drug discovery, informatics, personalized medicine, and clinical trials. Bio-IT World focuses on the technologies deployed and strategic decisions made by companies in these areas, and their impact on performance.

As the biopharma industry transforms itself from empirical trial-and-error experimentation to an industry reliant upon information, computation, and prediction of outcomes, technologies such as high-throughput genotyping, microarray analysis, and bioinformatics are providing the means of gathering, interpreting, and analyzing biological, chemical, and clinical data to further drug discovery and development. Bio-IT World covers the latest developments in these fields.

Focus areas include:
Genomic analysis: next-generation sequencing, genome-wide association mapping, and data integration

Discovery informatics: collection, analysis and workflows of compound, microarray, proteomic, imaging, and pre-clinical and clinical data

Systems biology: gene, protein, metabolite, and network/pathway information

Computational modeling: biosimulations of pathways, drug action, and clinical data

Predictiveness: in vitro assays, biomarkers, and animal models

Cheminformatics: structure-based drug design, compound characterization, ADME-Tox, and selectivity

Correlation of biological data: disease diagnosis, patient selection, and drug response

Target data: biological, pathway, interaction, patent, and family

IT infrastructure: grid computing and high-performance computing

Text mining: internal documents and published literature

Semantic web: next-generation data sharing and social networking

Clinical research: electronic data capture, patient recruitment, and adaptive trials

Pharmacogenomics: diagnostics for therapeutics, patient stratification

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White Papers & Special Reports

sas_f0910
Rethinking Clinical Trials Data Integration
Sponsored by SAS

There is a gap between the need for data integration and fully integrated systems. To find out why, SAS and Pharmaceutical Executive conducted confidential telephone interviews with senior pharmaceutical executives and CROs. This article discusses recommendations on how to achieve optimal clinical data integration, based on those interviews.



ClearTrial_BriefingOn
eClinical Trial Technologies Revolutionizing Clinical Development Efficiency
Sponsored by ClearTrial
This Bio-IT World BriefingON report, sponsored by ClearTrial, presents a selection of recent stories from Bio•IT World and sister publication, eCliniqua, that illustrate how new technologies and approaches can have a profound impact on the management and execution of clinical trials.


oracle_RDC
Remote Data Capture:Acquisition and Analysis
Sponsored by Oracle

See why Electronic Data Capture (EDC) is gaining traction in the pharmaceutical
clinical trials arena. Today approximately half of all clinical trials are conducted
electronically, and the figure is rapidly rising. Report includes contributions from
Oracle Health Sciences, Pfizer, PPD, and C3i.

 



Life Science Webcasts & Podcasts

Bio-IT World & CHI

Impact of the 1000 Genomes Project on the Next Wave of Pharmacogenomic Discovery
1000genomeInterview with M. Eileen Dolan, Ph.D., Professor, Medicine, University of Chicago and Speaker at Next-Generation Sequencing Data Management, September 27-29, 2010, Providence, RI  

The 1000 Genomes Project aims to provide detailed genetic variation data on >1000 genomes from worldwide populations using the next-generation sequencing technologies. Some of the samples utilized for the 1000 Genomes Project are the International Hap-Map samples that are composed of lymphoblastoid cell lines (LCLs) derived from individuals of different world populations. The detailed map of human genetic variation promised by the 1000 Genomes project will allow a more in-depth analysis of the contribution of genetic variation to drug response. Future studies utilizing this new resource can greatly enhance our understanding of the genetic basis of drug response and other complex traits.


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More Podcasts

Job Openings

mskc logo
Software Engineer – Computational Biology Center

Memorial Sloan-Kettering Cancer Center seeks an Engineer to design and develop complex data analysis systems in support of cancer genomics research projects at the Computational Biology Center. Qualified candidate will have a BA, 5+ years of software development experience and expert knowledge of Java, SQL, and HTML.

Apply: www.mskcciscareers.org.  Equal opportunity and affirmative action employer.

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