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omation mbers - Society for Laboratory Automation and Screening

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TP072<br />

Burkhard Schaefer<br />

National Institute of St<strong>and</strong>ards <strong>and</strong> Technology<br />

Analytical Chemistry Division<br />

100 Bureau Drive; Building 227; Room A-159<br />

Gaithersburg, Maryl<strong>and</strong> 20899-8394<br />

burkhard.schaefer@nist.gov<br />

Creating the Analytical In<strong>for</strong>mation Markup Language (AnIML)<br />

182<br />

Co-Author(s)<br />

Gary Kramer<br />

Multiple, vendor-specific, proprietary data <strong>for</strong>mats have made it difficult to interchange analytical result data<br />

between instruments <strong>and</strong> applications. When data are interchanged, metadata are rarely included, often<br />

rendering the datasets useless after the particulars of the experiment have been <strong>for</strong>gotten. The few existing<br />

data exchange st<strong>and</strong>ards are not compliant with modern network-based data interchange technologies. A few<br />

years ago NIST began to develop a markup language <strong>for</strong> uv/visible spectrometry data based on the Extensible<br />

Markup Language (XML). The result, SpectroML, showed the power of this approach <strong>and</strong> is now integral to<br />

NIST’s data h<strong>and</strong>ling in its optical filter St<strong>and</strong>ard Reference Materials program.ASTM subcommittee E13.15 on<br />

Analytical Data Management was <strong>for</strong>med in part to develop a general markup language, such as SpectroML, <strong>for</strong><br />

all spectroscopic <strong>and</strong> chromatographic result data. Work has begun on the initial task to develop a core schema<br />

representing the in<strong>for</strong>mation that is common to all analytical techniques. If a general core can be developed <strong>and</strong><br />

adopted, st<strong>and</strong>ard applications can be written to utilize this core <strong>and</strong> accomplish simple functions such as data<br />

visualization, importing data into applications such as spreadsheets, etc. With a simple applet a web browser such<br />

as Microsoft’s Internet Explorer could display any spectral or chromatographic trace. More sophisticated concepts<br />

such as integrating peak areas, leveling baselines, etc. will require more complicated software, but having a single<br />

technique-independent routine to view data, paste the visual image into reports, or import data into other programs<br />

<strong>for</strong> further processing will be of enormous utility. This presentation will describe the current status of the AnIML<br />

development ef<strong>for</strong>ts <strong>and</strong> point out possible uses in various application domains.<br />

TP073<br />

Sadhana Sharma<br />

The Ohio State University<br />

Davis Heart <strong>and</strong> Lung Research Institute (326 HLRI)<br />

473 W. 12th Avenue<br />

Columbus, Ohio 43212<br />

sharma.119@osu.edu<br />

Rapid <strong>and</strong> Sensitive Determination of Cardiovascular Drugs in Mouse Plasma Using<br />

Solid-phase Extraction <strong>and</strong> RP-HPLC<br />

Co-Author(s)<br />

John Shapiro<br />

Stephen C. Lee<br />

Mauro Ferrari<br />

Fast <strong>and</strong> sensitive determination of the drugs is essential <strong>for</strong> pharmaceutical aut<strong>omation</strong> <strong>and</strong> disease management.<br />

Capillary electrophoresis, liquid chromatography–mass spectrometry (LC–MS), immunoassays <strong>and</strong> high-per<strong>for</strong>mance<br />

liquid chromatography (HPLC) are some of the methods used <strong>for</strong> drug analysis. Of these, the HPLC methods<br />

have been used most frequently because of their simplicity, sensitivity, <strong>and</strong> selectivity. Drug analysis from blood/<br />

plasma samples requires sample pretreatment be<strong>for</strong>e actual HPLC analysis. This can be achieved using solidphase<br />

extraction (SPE), protein precipitation <strong>and</strong> SPE, liquid–liquid extraction (LLE), solvent extraction followed by<br />

column-switching, or solvent extraction <strong>and</strong> SPE. Higher number of pretreatment steps decreases efficiency <strong>and</strong><br />

increases analysis time. In addition, most of these HPLC methods require relatively large (a maximum of 0.5–1.0 ml)<br />

biological sample <strong>and</strong> multiple extraction steps. In cases where available sample volumes are in microliters, the<br />

HPLC methods with single LLE are generally not considered sensitive enough due to the presence of endogenous<br />

interferences. Solid phase extraction can be useful <strong>for</strong> such cases. In the present research ef<strong>for</strong>t, a rapid, simple <strong>and</strong><br />

sensitive method <strong>for</strong> the determination of simvastatin in mouse plasma is developed. This method utilizes Waters<br />

OASIS solid-phase extractor <strong>and</strong> Symmetry C8 reversed phase high-per<strong>for</strong>mance liquid chromatography column<br />

<strong>for</strong> micro-sample analysis <strong>and</strong> is useful <strong>for</strong> analysis of the drug released from microfabricated silicon nanoporous<br />

implant in mouse/human.

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