- Cancer Biology & Biomarkers
- Chromatography & Mass Spectrometry
- Contract Research, Clinical Trials and Outsourcing
- Drug Discovery
- Drug Targets
- Flow Cytometry
- Informatics & Lab Automation
- Ingredients, Excipients and Dosages
- Microbiology & RMMs
- NIR, PAT & QbD
- Raman Spectroscopy
- Screening, Assays & High-Content Analysis
- Thermal Processing
Wyeth Research - Articles and news items
High content screening (HCS) has now become integrated into all aspects of drug discovery from target identification and validation to hit generation and lead optimisation through to toxicological profiling. In neuroscience, the ability to perform automated neurite outgrowth and neuronal morphology screening has been a significant driver of HCS implementation. This approach has evolved significantly from relatively simple measures of total neurite length to detailed multi-parametric characterisation of neuronal morphology.
Despite marked advances in our understanding of chemical transmission, many of the complex processes, namely, our appreciation of the varying roles of neurochemicals in disease etiology, are still being investigated. To aid in this exploration and to monitor the extracellular levels of neurochemicals in living tissue systems, techniques such as in vivo microdialysis are routinely used.
Biomarkers (biological markers) have become an integral part of both drug discovery and drug development and play an important role in the transition of potential new drugs from discovery into clinical drug development. In the past, most biomarkers were proteins/peptides and metabolites measured by technologies such as immunoassays, enzymatic assays, HPLC and mass spectrometry.
Large and small drug development companies have used RNAi intensively for several years now1-3. The adoption of RNAi technologies by drug companies followed fairly closely with their adoption by academic research labs, and as such many of the challenges and problems that were a natural consequence of the rapid expansion of RNAi needed to be […]
The past decade has witnessed a growing interest in biomarkers, previously referred to as pharmacodynamic markers, PD markers, or pharmacologic read-outs. This increasing interest has been largely driven by evolutionary changes in drug discovery and development and in regulatory science1,2,3. One key driver has involved the increasing need to reach early go/no-go decisions about an increasing number of compounds entering early clinical development each year.
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