Editorial Team
How to work with our Editors
Bio-IT World provides indispensable news, analysis, and opinion on the enabling technologies that are driving the drug discovery process.
As the biopharma industry is transforming itself from empirical trial-and-error experimentation to an industry reliant upon information, computation and prediction of outcomes, a plethora of post-genomic technologies -- including high-throughput genotyping, microarray analysis, systems biology, proteomics and metabolic profiling – is providing the informational foundation for sophisticated computational and informatics approaches to gather, interpret, and analyze biological, chemical, and clinical data.
From systems biology and in silico modeling to cheminformatics and electronic data capture, Bio-IT World shows how predictive information is the key to improving the efficiency of drug discovery, to clinical trials all the way through to personalized medicine. Critical to the goal of modeling and exploiting information is the IT and informatics infrastructure -- the hardware and software that facilitates the creation of databases, text mining and the conversion of information into hypotheses, models, and conclusions.
Bio-IT World aims to empower its audience of more than 25,000 subscribers – including scientists, informaticians, IT managers, and executives working in biopharma, biotech, academia, government – and also foster communication of ideas and solutions between biomedical researchers and IT professionals.
Departments In every Issue:
Each month content is delivered around four key departments:
Computational Biology (bioinformatics)
Computational Development (cheminformatics)
IT Informatics/Workflow
Clinical Reseach
Regular Contributors:
First Base: Kevin Davies, Editor-in-Chief, Bio-IT World editorial page
Inside the Box: The BioTeam - IT Integration for life science
Nothing Ventured: Michael Greeley, IDG Ventures - M&A, finance, business
The Russell Transcript: John Russell, Executive Editor - Technology and business, systems biology, regulatory affairs
Editorial Areas of Interest:
- Systems biology: gene, protein, metabolite and network/pathway information
- Computational modeling: biosimulations of pathways, drug action, clinical data
- Cheminformatics: structure-based drug design
- Compound characterization: mechanisms, pathway, ADME-Tox, selectivity
Predictiveness: in vitro assays, biomarkers, animal models
- Correlation of biological data: disease diagnosis, patient selection, drug response
Target data: biological, pathway, interaction, patent, family
- Discovery/ Informatics: collection, analysis and workflows of compound, microarray, proteomic, imaging, pre-clinical and clinical data
- IT Infrastructure: grid computing, high-performance computing
Text mining: internal documents and published literature
- Semantic web: next-generation data sharing, social networking
- Pharmacogenomics: diagnostics for therapeutics, patient stratification
- Clinical research: electronic data capture, adaptive trials
