omation mbers - Society for Laboratory Automation and Screening

4:30 pm Tuesday, February 3 High Throughput Screening – Ion Channels Room A2
Christa Nutzhorn
CYTOCENTRICS GmbH
Taeleswiesenstraße 3
Reutlingen, 72770 Germany
vanbergen@cytocentrics.com
CytoPatch – Automated Patch Clamping
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Co-Author(s)
Thomas Knott
Alfred Stett
Timm Danker
The gold standard of ion channel analysis is patch clamping. This manual technique is time and cost consuming.
Even a good electrophysiologist might patch only ten cells per day. This is a bottleneck for the pharmaceutical
industry who wants to screen thousands of compounds. Automation of patch clamping is a reliable approach
for ion channel drug discovery. CYTOCENTRICS has methods ready to run for voltage-gated and ligand-gated
ion channels. Its modular CytoPatch accelerates discovery, characterisation and screening of novel drug
compounds. This technology is top edge in quality, flexibility and high throughput. It reduces time and costs
significantly.
8:00 am Wednesday, February 4 High Throughput Screening – Informatics Room A2
Roy Goodacre
UMIST
P.O. Box 88
Sackville Street
Manchester, M60 1QD United Kingdom
R.Goodacre@umist.ac.uk
Interpretation of Metabolomic Data Using Explanatory Machine Learning
Post-genomic science is producing bounteous data floods, and the extraction of the most meaningful parts of
these data is key to the generation of useful new knowledge. A typical metabolic fingerprint or metabolomics
experiment is expected to generate thousands of data points (samples times variables) of which only a handful
might be needed to describe the problem adequately. Rule induction (RI) methods and evolutionary algorithms
(EAs) are ideal strategies for mining such data to generate useful relationships, rules and predictions. This
presentation will give an overview of some of the metabolomic studies that are currently in progress in UMIST
that exploit these explanatory machine learning algorithms. Within this context we have been developing Fourier
transform infrared (FT-IR) spectrospcopy as a high throughput (1 s is typical per sample) “holistic” metabolic
fingerprinting screening approach and flow-injection electrospray ionization mass spectrometry (FI-ESI-MS) as a
metabolic profiling technique. The following examples will be presented: (1) the detection of the adulteration of
virgin olive oil, (2) the detection of a spore-specific chemical biomarker in bacterial spores; and (3) the quantitative
detection of metabolic markers for food spoilage.