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PubMed1983

Automated versus self-monitoring of 'up-time' in chronic low-back pain patients: a comparative study.

The study compared up-time data gathered with automated and self-monitoring measurement systems. Six chronic low-back pain inpatients, 6 psychiatric inpatients and 6 hospital staff members were used as subjects. Concurrent recordings of up-time were taken over 4 consecutive days with the two measurement systems. Results showed that: (a) subjects across all 3 groups reported significantly less absolute up-time values from self-monitoring than automated monitoring, (b) non-patient staff subjects exhibited greater absolute up-time levels from both measurement methods than those reported by low-back pain or psychiatric inpatients, (c) low-back pain subjects showed a greater discrepancy between absolute up-time measures from the two measurement systems than differences found for psychiatric or staff subjects, and (d) automated and self-monitoring up-time values were positively correlated within each group of subjects. It was concluded that automated and self-monitoring up-time data were not directly comparable. Expanded development and usage of automated measurement systems was recommended.

Adult↗
PubMed1995

Automation of polymerase chain reaction tests. Reduction of human errors leading to contamination.

We compared the performance over 21 months of manually performed polymerase chain reaction (PCR)-based DNA analysis experiments with 25 months of automated PCR performed by a Zymark robotic system. Automation of the PCR technique resulted in a sixfold reduction in the number of experiments reporting carryover contamination and decreased the overall rate of contamination among total reactions 68-fold. Whereas contamination occurrences among manual experiments were evenly dispersed over the study interval and correlated with the lack of experience of laboratory personnel, the contamination that occurred with the robotic system was confined to the first 10 months of operation. In manual experiments, many of the 81 no-target false positives were sufficiently strong to result in the invalidation of 151 samples and positive controls. The seven no-target control false positives in the automated system were weak bands that were easily subtracted as background. Because none of the negative samples had DNA bands, no sample on the automated system has ever been invalidated as a result of contamination. Automation of PCR tests appears to offer great promise in reducing contamination to acceptable levels (e.g., < or = 0.1%).

DNA↗
PubMed1990

A comparison of two automated monitors in the measurement of blood pressure reactivity. Trials of Hypertension Prevention Collaborative Research Group.

Cardiovascular reactivity is the change in blood pressure, pulse, and other parameters of cardiovascular function in response to a challenging task. During the conduct of cardiovascular reactivity protocols, researchers frequently use automated blood pressure devices to measure blood pressure reactivity. However, the accuracy of automated devices in measuring blood pressure reactivity is unknown. To investigate the accuracy and precision of the Dinamap 1846 SXP and the VitaStat 2600B in the measurement of blood pressure reactivity, we compared blood pressure reactivity recorded by the VitaStat and Dinamap with that obtained by observers using a conventional mercury sphygmomanometer. At three sites, 159 normotensive subjects performed the same task twice, once with blood pressure reactivity measured by the manual observers and once by the VitaStat (n = 79) or Dinamap (n = 80), with the order determined at random. Ratios (VitaStat/Dinamap) of aggregate within-person variance for baseline and task, systolic and diastolic blood pressures ranged from 1.53 to 4.93 (all P < 0.01), suggesting that the Dinamap has better precision than the VitaStat. For both diastolic and systolic blood pressure reactivity and for both types of automated devices, the mean differences in blood pressure reactivity between manual and automated measurements were small (range, -1.8 to 0.8 mm Hg). However, the VitaStat versus manual scatter plot of diastolic blood pressure reactivity showed greater dispersion (correlation coefficient r = 0.16, P = 0.15) than the Dinamap versus manual scatter plot (r = 0.36, P = 0.001). For systolic blood pressure reactivity, the VitaStat versus manual and Dinamap versus manual scatter plots were similar. Our data indicate that the Dinamap is superior to the VitaStat in the measurement of blood pressure reactivity. The substantial performance differences between the VitaStat and Dinamap suggest that other automated blood pressure monitors must be evaluated prior to use in cardiovascular reactivity studies.

Adult↗
PubMed2004

Automated lung segmentation for thoracic CT impact on computer-aided diagnosis.

RATIONALE AND OBJECTIVES: Automated lung segmentation in thoracic computed tomography scans is essential for the development of computer-aided diagnostic (CAD) methods. A core segmentation method may be developed for general application; however, modifications may be required for specific clinical tasks. MATERIALS AND METHODS: An automated lung segmentation method has been applied (1) as preprocessing for automated lung nodule detection and (2) as the foundation for computer-assisted measurements of pleural mesothelioma tumor thickness. The core method uses gray-level thresholding to segment the lungs within each computed tomography section. The segmentation is revised through separation of right and left lungs along the anterior junction line, elimination of the trachea and main bronchi from the lung segmentation regions, and suppression of the diaphragm. Segmentation modifications required for nodule detection include a rolling ball algorithm to include juxtapleural nodules and morphologic erosion to eliminate partial volume pixels at the boundary of the segmentation regions. RESULTS: For automated lung nodule detection, 4 of 82 actual nodules (4.9%) were excluded from the lung segmentation regions when the core segmentation method was modified compared with 14 nodules (17.1%) excluded without modifications. The computer-assisted quantification of mesothelioma method achieved a correlation coefficient of 0.990 with 134 manual measurements when the core segmentation method was used alone; correlation was reduced to 0.977 when the segmentation modifications, as adapted for the lung nodule detection task, were applied to the mesothelioma measurement task. CONCLUSION: Different CAD applications impose different requirements on the automated lung segmentation process. The specific approach to lung segmentation must be adapted to the particular CAD task.

Algorithms↗
PubMed2005

Problems with the estimation of urine protein by automated assays.

OBJECTIVES: Most clinical laboratories replaced their manual precipitation techniques for the determination of urinary protein with automated dye binding assays or benzethonium chloride-turbidimetric assays. Few studies have validated these assays for the measurement of urinary proteins in the normal range. DESIGN AND METHODS: This study compares four automated assays for the measurement of urinary protein to a manual Ponceau S/TCA precipitation assay. We evaluated the linearity, the precision, the analytical sensitivity, the accuracy and the recovery of different proteins for each assay. RESULTS: All assays showed good linearity with the theoretical concentration of albumin present in the sample. The coefficient of variation was below 10% at a concentration of 0.142 g/L. However, the manual Ponceau S/TCA assay demonstrated superior analytical sensitivity. Accuracy determinations showed a variable positive bias and poor correlations at concentrations below 0.1 g/L when compared to the Ponceau S/TCA assay. Small molecular weight peptides particularly affected the pyrogallol red assays but other urinary components also interfered with the automated assays. CONCLUSIONS: Most automated assays show high imprecision and poor accuracy for the measurement of urinary protein in the normal range. The Ponceau S/TCA offers a precise and accurate manual alternative to these automated assays.

Albuminuria↗
PubMed2004

Assessment of donor liver steatosis: pathologist or automated software?

Steatosis in donor liver biopsy specimens has been shown to correlate with graft dysfunction after orthotopic liver transplantation. This 2-part (laboratory pilot, clinical retrospective) study compared the traditional interpretation of steatosis by a pathologist with an automated measurement determined by an image analysis system. In our pilot study, Sprague-Dawley rats were studied prospectively by feeding them a choline-deficient diet for up to 7 days. In our clinical group, data from 49 consecutive recipients of cadaveric liver transplantation were reviewed retrospectively. In both studies, the percentages of microvesicular fat, macrovesicular fat, and total fat content within liver biopsy specimens were determined by an automated image analysis software program and a pathologist using the same set of slides. The association between fat content of the donor liver and patient survival and graft survival, along with levels of aspartate aminotransferase, alanine aminotransferase, prothrombin time, and total bilirubin after transplantation, were also examined in the clinical study. A direct correlation was observed between levels of macrovesicular fat determined by a pathologist and the automated software using livers from rats fed a choline-deficient diet and livers from deceased donors. A significant association was observed between macrovesicular fat content in the donor liver biopsy and graft survival by both techniques. We conclude that an image analysis system can be used to automate the determination of fat content in liver biopsy specimens, and that its findings correlate with both the visual interpretation by a pathologist and graft survival. Further study is needed to determine the role of an automated technique in the evaluation of donor livers for transplantation.

Animals↗
PubMed2004

Brain tumor target volume determination for radiation treatment planning through automated MRI segmentation.

PURPOSE: To assess the effectiveness of two automated magnetic resonance imaging (MRI) segmentation methods in determining the gross tumor volume (GTV) of brain tumors for use in radiation therapy treatment planning. METHODS AND MATERIALS: Two automated MRI tumor segmentation methods (supervised k-nearest neighbors [kNN] and automatic knowledge-guided [KG]) were evaluated for their potential as "cyber colleagues." This required an initial determination of the accuracy and variability of radiation oncologists engaged in the manual definition of the GTV in MRI registered with computed tomography images for 11 glioma patients. Three sets of contours were defined for each of these patients by three radiation oncologists. These outlines were compared directly to establish inter- and intraoperator variability among the radiation oncologists. A novel, probabilistic measurement of accuracy was introduced to compare the level of agreement among the automated MRI segmentations. The accuracy was determined by comparing the volumes obtained by the automated segmentation methods with the weighted average volumes prepared by the radiation oncologists. RESULTS: Intra- and inter-operator variability in outlining was found to be an average of 20% +/- 15% and 28% +/- 12%, respectively. Lowest intraoperator variability was found for the physician who spent the most time producing the contours. The average accuracy of the kNN segmentation method was 56% +/- 6% for all 11 cases, whereas that of the KG method was 52% +/- 7% for 7 of the 11 cases when compared with the physician contours. For the areas of the contours where the oncologists were in substantial agreement (i.e., the center of the tumor volume), the accuracy of kNN and KG was 75% and 72%, respectively. The automated segmentation methods were found to be least accurate in outlining at the edges of the tumor volume. CONCLUSIONS: The kNN method was able to segment all cases, whereas the KG method was limited to enhancing tumors and gliomas with clear enhancing edges and no cystic formation. Both methods undersegment the tumor volume when compared with the radiation oncologists and performed within the variability of the contouring performed by experienced radiation oncologists based on the same data.

Aged↗
PubMed2005

Automated 96-well solid phase extraction and hydrophilic interaction liquid chromatography-tandem mass spectrometric method for the analysis of cetirizine (ZYRTEC) in human plasma--with emphasis on method ruggedness.

A high-throughput bioanalytical method based on automated sample transfer, automated solid phase extraction, and hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS) analysis, has been developed for the determination of cetirizine, a selective H(1)-receptor antagonist. Deuterated cetirizine (cetirizine-d(8)) was synthesized as described and was used as the internal standard. Samples were transferred into 96-well plates using an automated sample handling system. Automated solid phase extraction was carried out using a 96-channel programmable liquid-handling workstation. Solid phase extraction 96-well plate on polymer sorbent (Strata X) was used to extract the analyte. The extracted samples were injected onto a Betasil silica column (50 x 3, 5 microm) using a mobile phase of acetonitrile-water-acetic acid-trifluroacetic acid (93:7:1:0.025, v/v/v/v) at a flow rate of 0.5 ml/min. The chromatographic run time is 2.0 min per injection, with retention time of cetirizine and cetirizine-d(8) both at 1.1 min. The system consisted of a Shimadzu HPLC system and a PE Sciex API 3000 or API 4000 tandem mass spectrometer with (+) ESI. The method has been validated over the concentration range of 1.00-1000 ng/ml cetirizine in human plasma, based on a 0.10-ml sample size. The inter-day precision and accuracy of the quality control (QC) samples demonstrated <3.0% relative standard deviation (R.S.D.) and <6.0% relative error (RE). Stability of cetirizine in stock solution, in plasma, and in reconstitution solution was established. The absolute extraction recovery was 85.8%, 84.5%, and 88.0% at 3, 40, and 800 ng/ml, respectively. The recovery for the internal standard was 84.1%. No adverse matrix effects were noticed for this assay. The automation of the sample preparation steps not only increased the analysis throughput, but also increased method ruggedness. The use of a stable isotope-labeled internal standard further improved the method ruggedness. Practical issues of analyzing incurred samples were discussed. This HILIC-MS/MS method for analysis of citirizine in human plasma was successfully used to support clinical studies.

Cetirizine↗
PubMed2005

Validation of a semi-automated human hepatocyte assay for the determination and prediction of intrinsic clearance in discovery.

An automated high throughput human hepatocyte assay has been established with a 96-well format using a Tecan Genesistrade mark Workstation. Validation of this assay was performed with nine commercially available compounds and an additional 10 Pfizer compounds with varying hepatic extraction ratios (E(H)) ranging from 0.02 to approximately 1. The incubation conditions in the automated assay are readily and precisely controlled and cell viability of over 80% was achieved in the automated assay further confirming its utility for absorption, distribution, metabolism, and excretion (toxicity) (ADME (T)) screening. The results of the nine commercial compounds correlate with both manually executed (R(2)=0.97) and literature reported experimental results (R(2)=0.93). Overall, measured E(H)s were within two-fold of the literature values for approximately 90% of the 19 compounds tested. Additionally, good inter- and intra-day reproducibility was observed for all the 19 compounds. In conclusion, an automated and robust assay suitable for simultaneously testing up to 48 compounds with multiple time points has been validated. Throughput of 192 compounds per run can be achieved using 384-well plates to meet increasing needs in drug discovery. Currently, this automated assay is used to support early discovery profiling towards lead optimization of various discovery targets/programs.

Cell Survival↗
PubMedDate not supplied

Historical background: Why is it important to improve automated particle selection methods?

A current trend in single-particle electron microscopy is to compute three-dimensional reconstructions with ever-increasing numbers of particles in the data sets. Since manual--or even semi-automated--selection of particles represents a major bottleneck when the data set exceeds several thousand particles, there is growing interest in developing automatic methods for selecting images of individual particles. Except in special cases, however, it has proven difficult to achieve the degree of efficiency and reliability that would make fully automated particle selection a useful tool. The simplest methods such as cross correlation (i.e., matched filtering) do not perform well enough to be used for fully automated particle selection. Geometric properties (area, perimeter-to-area ratio, etc.) and the integrated "mass" of candidate particles are additional factors that could improve automated particle selection if suitable methods of contouring particles could be developed. Another suggestion is that data be always collected as pairs of images, the first taken at low defocus (to capture information at the highest possible resolution) and the second at very high defocus (to improve the visibility of the particle). Finally, it is emphasized that well-annotated, open-access data sets need to be established in order to encourage the further development and validation of methods for automated particle selection.

Algorithms↗
PubMed2006

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

Adult↗
PubMed2006

Automated brainstem co-registration (ABC) for MRI.

Group data analysis in brainstem neuroimaging is predicated on accurate co-registration of anatomy. As the brainstem is comprised of many functionally heterogeneous nuclei densely situated adjacent to one another, relatively small errors in co-registration can manifest in increased variance or decreased sensitivity (or significance) in detecting activations. We have devised a 2-stage automated, reference mask guided registration technique (Automated Brainstem Co-registration, or ABC) for improved brainstem co-registration. Our approach utilized a brainstem mask dataset to weight an automated co-registration cost function. Our method was validated through measurement of RMS error at 12 manually defined landmarks. These landmarks were also used as guides for a secondary manual co-registration option, intended for outlier individuals that may not adequately co-register with our automated method. Our methodology was tested on 10 healthy human subjects and compared to traditional co-registration techniques (Talairach transform and automated affine transform to the MNI-152 template). We found that ABC had a significantly lower mean RMS error (1.22 +/- 0.39 mm) than Talairach transform (2.88 +/- 1.22 mm, mu +/- sigma) and the global affine (3.26 +/- 0.81 mm) method. Improved accuracy was also found for our manual-landmark-guided option (1.51 +/- 0.43 mm). Visualizing individual brainstem borders demonstrated more consistent and uniform overlap for ABC compared to traditional global co-registration techniques. Improved robustness (lower susceptibility to outliers) was demonstrated with ABC through lower inter-subject RMS error variance compared with traditional co-registration methods. The use of easily available and validated tools (AFNI and FSL) for this method should ease adoption by other investigators interested in brainstem data group analysis.

Adult↗
PubMed2006

Properties of voltage-gated Na+ channels in the human rhabdomyosarcoma cell-line SJ-RH30: conventional and automated patch clamp analysis.

Conventional and automated patch clamp electrophysiology were used to characterise the Na+ current of the SJ-RH30 human rhabdomyosarcoma. In conventional recordings SJ-RH30 cells exhibited a fast activating, fast inactivating Na+ current at potentials positive to -40 mV; in full current-voltage curves maximum current occurred between -20 and -10 mV. Inactivation kinetics at 0 mV were biexponential with time constants of 0.5 and 3.7 ms. Deinactivation at -90 mV also exhibited two kinetic components. Tetrodotoxin (TTX) blocked the Na+ current completely at 1 microM. The NaV 1.4 selective toxin mu-CTx-GIIIB reversibly blocked the Na+ current approximately 60% at 10 microM. Very similar biophysical behaviour was observed in automated patch clamp and conventional recordings. For example, inactivation mid-point was -72+/-2 mV (slope factor 7.2+/-0.2) in automated patch clamp and -74+/-2 mV (slope factor 7.4+/-0.4) with conventional recording. The corresponding values for activation mid-point were -33.2+/-2.4 and -30.3+/-2.7 mV (slope 5.8+/-0.3 and 6.4+/-0.3, respectively). The throughput of the automated method was used to generate additional pharmacological data on inhibition of the Na+ current. TTX inhibited with an IC50 of 23 nM. Mu-CTx-GIIIB also inhibited the channel in a concentration-dependent manner. Inhibition produced by both tetracaine and amitriptyline were shown to be frequency-dependent. Our experiments indicate that the Na+ current of SJ-RH30 cells arises mainly from channels with a phenotype like recombinant NaV 1.4 channels. The suitability of these cells for automated patch clamp suggests they may be useful for higher throughput studies of the interaction of drugs with human skeletal muscle Na+ channels.

Action Potentials↗
PubMed2005

A manual and automated MRI study of anterior cingulate and orbito-frontal cortices, and caudate nucleus in obsessive-compulsive disorder: comparison with healthy controls and patients with schizophrenia.

Functional imaging and neuropsychological data suggest that interconnected brain structures including the orbito-frontal cortex (OFC), anterior cingulate cortex (ACC) and caudate nucleus (CN) are involved in the pathophysiology of obsessive-compulsive disorder (OCD), but structural imaging studies investigating these regions have yielded inconclusive results. This may be due to inconsistencies in the identification of anatomical boundaries and methodologies utilised (i.e. automated vs. manual tracing). This magnetic resonance imaging study used manual tracing to measure volumes of selected brain regions (OFC, ACC and CN) in OCD patients and compared them with samples of healthy (HC) and psychiatric (schizophrenia; SCZ) controls (n=18 in each group). Concurrently, automated voxel-based analysis was also used to detect subtle differences in cerebral grey and white matter. For the OCD vs. HC comparison, there were no significant volumetric differences detected using the manual or the automated method (although the latter revealed a deficit in the subcortical white matter of the right temporal region). A direct comparison of the two patient groups showed no significant differences using the manual method. However, a moderate effect size was detected for OFC grey matter (reduced in SCZ), which was supported by findings of reduced OFC volume in the automated analysis. Automated analyses also showed reduced volumes in the dorsal (white matter) and ventral ACC (grey and white matter), as well as the left posterior cingulate (grey and white matter) in SCZ. The findings suggest that in contrast to findings in SCZ, there are very few (if any) gross structural anomalies in OCD.

Adult↗
PubMed1997

Conjugate imagery in the automated reproduction of three dimensional coordinates from two dimensional coordinate data.

The three-dimensional video analysis of human motion commonly utilises automated image processing and digitisation processes to produce real-time unidentified two-dimensional coordinate data of segmental markers. In what can be a time-consuming process the two-dimensional data are then identified and tracked to produce three-dimensional coordinates. This paper presents an approach to the automated reproduction of three-dimensional coordinates from two-dimensional coordinates data. Conjugate imaging techniques were utilised in the development of four criterion measures for determining the validity of conjugate (corresponding) image points. An algorithm based on the criterion measures was then developed for the automated reproduction of three dimensional coordinates from camera image coordinate data. The algorithm was tested with a 55 point marker system viewed in four video cameras (digitisation error approx. 0.2%, lab point separation > or = 6 cm). The success of the algorithm was dependent on the closeness of markers, the accuracy of the photogrammetric system, and the number of markers visible in two camera images. The present research has developed techniques based on conjugate imagery for the automated reproduction of three-dimensional coordinates from two-dimensional data, and provided a bases for further development of automated three-dimensional tracking.

Algorithms↗
PubMed1996

Validation of an automated image analysis micronucleus scoring system.

The Loats Automated Micronucleus Scoring System was developed to assist with the evaluation of compounds for the ability to induce micronuclei in mouse bone marrow polychromatic erythrocytes (PCE). This image analysis system can identify PCE as well as normochromatic erythrocytes (NCE) and calculate the PCE/NCE ratio as an index for bone marrow toxicity. Two studies were conducted to provide slides for a comparison of micronucleated PCE values collected manually to those collected by the automated system. Mitomycin C was used as a micronucleus-inducing agent to elicit a positive response and Lilly compound 303497 was used as an example of a compound negative for the induction of micronuclei. No statistically significant differences were observed between micronucleus counts obtained manually and those obtained by the automated system. The PCE/NCE ratios calculated by the automated system were also similar to those determined from the manually collected PCE and NCE counts for the vehicle and positive controls, however, differences in the ratios were observed in compound treatment groups. These differences were attributed to a larger population of transitional cells in the treated groups. These results confirm that the Loats Automated Micronucleus Scoring System is an acceptable alternative to manual evaluation of mouse bone marrow slides for the incidence of micronucleated PCE.

Animals↗
PubMed1998

Reliability and reproducibility of automated contour analysis in intravascular ultrasound images of femoropopliteal arteries.

An automated contour analysis system was previously developed to increase reproducibility and facilitate quantitative analyses of intravascular ultrasound (IVUS) images. The aim of this study was to compare measurements by this automated system with those obtained by conventional manual tracing, and to determine the intra- and interobserver variability of the automated system. IVUS images obtained in the femoropopliteal artery (n = 12) were analyzed with both systems. Area measurements by the automated system agreed well with the results obtained by manual tracing, displaying low coefficients of variation (8.5 to 15.7%) and high correlation coefficients (r = 0.92 to 0.98). Intra- and interobserver comparison of lumen area, vessel area, plaque area and percentage area stenosis showed low coefficients of variation (6.0 to 15.3% and 5.7 to 14.0%, respectively) and high correlation coefficients (both: r = 0.93 to 0.99). These data indicate that the automated analysis system is a reliable tool for the quantitative assessment of vessel dimensions in IVUS images obtained during clinical examination of peripheral arteries.

Aged↗
PubMed1998

An automated method for the determination of subnanogram concentrations of eprinomectin in bovine plasma.

Eprinomectin is a potent anthelmintic compound that kills certain parasitic nematodes and arthropods of cattle. A sensitive and automated bioanalytical assay was developed for quantitation of eprinomectin in bovine plasma in support of clinical development of eprinomectin for use in all classes of cattle. This assay determined the concentration of eprinomectin in plasma by reversed-phase high performance liquid chromatography (HPLC) with fluorometric detection. Plasma sample preparation included liquid extraction performed by the Packard MultiPROBE robotics workstation, followed by solid phase extraction performed by the Gilson ASPEC XL automated workstation. The HPLC assay included automated pre-column derivatization with a fluorogenic reagent system which included trifluoroacetic anhydride and N-methylimidazole as the catalyst. This reversed-phase chromatographic analysis was based on the fluorescence detection of derivatized eprinomectin and an internal standard, L-648 548, which was similarly derivatized by the fluorogenic reagents. The assay was automated and validated for two concentration ranges of 0.05-10 and 0.5-200 ng ml-1. The lower limit of quantitation of eprinomectin in plasma was 0.05 ng ml-1. The %RSD of the assay was 10% or better at all concentrations. This automated analysis of eprinomectin was used for high-throughput clinical assays with acceptable accuracy and precision.

Animals↗