(1)H-Nuclear magnetic resonance-based metabolic profiling of nonsteroidal anti-inflammatory drug-induced adverse effects in rats.

Nonsteroidal anti-inflammatory drugs (NSAIDs), which are globally prescribed, exhibit mainly anti-inflammatory and analgesic effects but also can cause adverse effects including gastrointestinal erosions, ulceration, bleeding, and perforation. The purpose of this study was to investigate surrogate biomarkers associated with the gastrointestinal (GI) damage caused by NSAID treatment using pattern recognition analysis of (1)H-nuclear magnetic resonance ((1)H NMR) spectra of rat urine. Urine was collected for 5h after oral administration of the following NSAIDs at low or high doses: acetylsalicylic acid (10 or 200mgkg(-1)), diclofenac (0.5 or 15mgkg(-1)), piroxicam (1 or 10mgkg(-1)), indomethacin (1 or 25mgkg(-1)), or ibuprofen (10, or 150mgkg(-1)) as nonselective COX inhibitors and celecoxib (10 or 100mgkg(-1)) as a COX-2 selective inhibitor. The urine was analyzed using 500MHz (1)H NMR for spectral binning and targeted profiling and the level of gastric damage was examined. The nonselective COX inhibitors caused severe gastric damage while no lesions were observed in the celecoxib-treated rats. The (1)H NMR urine spectra were divided into spectral bins (0.04ppm) for global profiling, and a total of 44 endogenous metabolites were assigned for targeted profiling. Multivariate data analyses were performed to recognize the spectral pattern of endogenous metabolites related to NSAIDs using partial least square-discrimination analysis (PLS-DA). The (1)H NMR spectra clustered differently according to gastric damage score in global profiling. In targeted profiling, the endogenous metabolites of citrate, allantoin, 2-oxoglutarate, acetate, benzoate, glycine, and trimethylamine N-oxide were selected as putative biomarkers for gastric damage caused by NSAIDs. These putative biomarkers might be useful for predicting the risk of adverse effects caused by NSAIDs in the early stage of drug development process.

Nuclear magnetic resonance-based metabolomics for prediction of gastric damage induced by indomethacin in rats.

Non-steroidal anti-inflammatory drugs (NSAIDs) have side effects including gastric erosions, ulceration and bleeding. In this study, pattern recognition analysis of the (1)H-nuclear magnetic resonance (NMR) spectra of urine was performed to develop surrogate biomarkers related to the gastrointestinal (GI) damage induced by indomethacin in rats. Urine was collected for 5 h after oral administration of indomethacin (25 mg kg(-1)) or co-administration with cimetidine (100 mg kg(-1)), which protects against GI damage. The (1)H-NMR urine spectra were divided into spectral bins (0.04 ppm) for global profiling, and 36 endogenous metabolites were assigned for targeted profiling. The level of gastric damage in each animal was also determined. Indomethacin caused severe gastric damage; however, indomethacin administered with cimetidine did not. Simultaneously, the patterns of changes in their endogenous metabolites were different. Multivariate data analyses were carried out to recognize the spectral pattern of endogenous metabolites related to indomethacin using partial least square-discrimination analysis. In targeted profiling, a few endogenous metabolites, 2-oxoglutarate, acetate, taurine and hippurate, were selected as putative biomarkers for the gastric damage induced by indomethacin. These metabolites changed depending on the degree of GI damage, although the same dose of indomethacin (10 mg kg(-1)) was administered to rats. The results of global and targeted profiling suggest that the gastric damage induced by NSAIDs can be screened in the preclinical stage of drug development using a NMR based metabolomics approach.

Simple determination of azasetron in rat plasma by column-switching high-performance liquid chromatography.

For the quantification of azasetron in rat plasma samples, a column-switching HPLC method was developed and validated. Following dilution of plasma samples with mobile phase A (17 mM potassium phosphate buffer (pH 3.0)) and simple protein precipitation by addition of perchloric acid (60%), the mixture was directly injected onto the pre-column. After endogenous plasma substances were eluted to waste, the analyte was transferred to the trap column by switching the system. Then, the analyte was back-flushed to the analytical column for separation with mobile phase B (a 22:78 v/v mixture of acetonitrile and 17 mM potassium phosphate buffer (pH 3.0)) and detected at 250 nm using a photodiode array detector. A linear standard curve was obtained in the concentration range of 10-800 ng/mL with the correlation coefficient (r) of 0.9998. The intra- and inter-day precision and accuracy values for azasetron were in the ranges of 0.3-12.9% and 89.7-101.4%, respectively. The method was valid in terms of specificity, precision, and accuracy. In addition, this efficient analytical method was successfully applied to determine plasma concentrations of azasetron following oral administration of azasetron at a dose of 4.0 mg/kg to rats.

Toxicometabolomics approach to urinary biomarkers for mercuric chloride (HgCl2)-induced nephrotoxicity using proton nuclear magnetic resonance (¹H NMR) in rats.

The primary objective of this study was to determine and characterize surrogate biomarkers that can predict nephrotoxicity induced by mercuric chloride (HgCl2) using urinary proton nuclear magnetic resonance (¹H NMR) spectral data. A procedure for (1)H NMR urinalysis using pattern recognition was proposed to evaluate nephrotoxicity induced by HgCl2 in Sprague-Dawley rats. HgCl2 at 0.1 or 0.75 mg/kg was administered intraperitoneally (i.p.), and urine was collected every 24 h for 6 days. Animals (n=6 per group) were sacrificed 3 or 6 days post-dosing in order to perform clinical blood chemistry tests and histopathologic examinations. Urinary ¹H NMR spectroscopy revealed apparent differential clustering between the control and HgCl2 treatment groups as evidenced by principal component analysis (PCA) and partial least square (PLS)-discriminant analysis (DA). Time- and dose-dependent separation of HgCl2-treated animals from controls was observed by PCA of ¹H NMR spectral data. In HgCl2-treated rats, the concentrations of endogenous urinary metabolites of glucose, acetate, alanine, lactate, succinate, and ethanol were significantly increased, whereas the concentrations of 2-oxoglutarate, allantoin, citrate, formate, taurine, and hippurate were significantly decreased. These endogenous metabolites were selected as putative biomarkers for HgCl2-induced nephrotoxicity. A dose response was observed in concentrations of lactate, acetate, succinate, and ethanol, where severe disruption of the concentrations of 2-oxoglutarate, citrate, formate, glucose, and taurine was observed at the higher dose (0.75 mg/kg) of HgCl2. Correlation of urinary (1)H NMR PLS-DA data with renal histopathologic changes suggests that ¹H NMR urinalysis can be used to predict or screen for HgCl2-induced nephrotoxicity.

Pattern recognition analysis for the prediction of adverse effects by nonsteroidal anti-inflammatory drugs using 1H NMR-based metabolomics in rats.

Nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly used to treat rheumatoid arthritis, osteoarthritis, acute pain, and fever. However, NSAIDs have side effects that include gastric erosions, ulceration, bleeding, and perforation, etc. Selective cyclooxygenase (COX)-2 inhibitors have been developed to avoid the adverse drug reaction of traditional NSAIDs. The COX-2 inhibitors have a different mechanism of action from nonselective COX inhibitors. In this study, pattern recognition analysis of the (1)H nuclear magnetic resonance (NMR) spectra of urine was performed to develop surrogate biomarkers related to the gastrointestinal (GI) damage induced by NSAIDs in rats. Urine was collected for 5 h after administering the following NSAIDs at high doses: celecoxib (133 mg kg(-1), p.o.), a COX-2-selective inhibitor; and indomethacin (25 mg kg(-1), p.o.) or ibuprofen (800 mg kg(-1), p.o.), nonselective COX inhibitors. The urine was analyzed using 600 M (1)H NMR for spectral binning and targeted profiling. The level of gastric damage in each animal was also determined. Indomethacin and ibuprofen caused severe gastric damage, but no lesions were observed in the celecoxib-treated rats. The (1)H NMR urine spectra were divided into spectral bins (0.04 ppm) for global profiling, and 36 endogenous metabolites were assigned for targeted profiling. Multivariate data analyses were carried out to recognize the spectral pattern of endogenous metabolites related to NSAIDs using partial least-squares discrimination analysis (PLS-DA). There were different clusterings of (1)H NMR spectra according to the gastric damage scores in global profiling. In targeted profiling, a few endogenous metabolites of allantoin, taurine, and dimethylamine were selected as putative biomarkers for the gastric damage induced by NSAIDs. The results of global and targeted profilings suggest that the gastric damage induced by NSAIDs can be screened in the preclinical stage of drug development using a current metabolomics study. In addition, the putative biomarkers might also be useful for predicting the risk of adverse effects caused by NSAIDs.

Metabolomics approach to risk assessment: methoxyclor exposure in rats.

The primary objective of this study was to develop exposure biomarkers that "correlate with the endocrine-disrupting effects induced by methoxyclor (MTC), an organochlorine pesticide, using" urinary (1)H nuclear magnetic resonance (NMR) spectral data. Exposure biomarkers play an important role in risk assessment. MTC is an environmental endocrine disruptor with estrogenic, anti-estrogenic, and anti-androgenic properties. A new approach of proton nuclear magnetic resonance ((1)H NMR) urinalysis using pattern recognition was proposed for exposure biomarkers of MTC in female rats. The endocrine disruptor was expected to induce estrogenic effects in a dose dependent manner which, was confirmed by the uterotrophic assay. MTC [50, 100, or 200 m g/kg/d, orally (p.o.) or subcutaneously (s.c.)] was administered to ovariectomized female Sprague-Dawley (SD) rats for 3 d consecutively and urine was collected every 24 h. The animals were sacrificed 24 h after the last dose. All animals treated orally with MTC showed a significant increase in uterine and vaginal weight at all doses. However, in the s.c. route, only a high dose of 200 mg MTC/kg induced a significant increase in uterine and vaginal weight. (1)H NMR spectroscopy revealed evident separate clustering between pre- and post-treatment groups using global metabolic profiling through principal component analysis (PCA) and partial least square (PLS) discrimination analysis (DA) after different exposure routes. With targeted profiling, the endogenous metabolites of acetate, alanine, benzoate, lactate, and glycine were selected as putative exposure biomarkers for MTC. Data suggest that the proposed putative exposure biomarkers may be useful in a risk assessment of the endocrine-disrupting effects produced by MTC.

Determination of the active metabolites of sibutramine in rat serum using column-switching HPLC.

A simple and direct analysis using column-switching HPLC method was developed and validated for the quantification of active metabolites of sibutramine, N-mono-desmethyl metabolite (metabolite 1, M1) and N-di-desmethyl metabolite (metabolite 2, M2) in the serum of rats administered sibutramine HCl (5.0 mg/kg, p.o.). Rat serum was directly injected onto the precolumn without sample prepreparation step following dilution with mobile phase A, i. e., methanol-ACN-20 mM ammonium phosphate buffer (pH 6.0 with phosphoric acid) (8.3:4.5:87.2 by volume). After the endogenous serum components were eluted to waste, the system was switched and the analytes were eluted to the trap column. Active metabolites M1 and M2 were then back-flushed to the analytical column for separation with mobile phase B, i. e., methanol-ACN-20 mM ammonium phosphate buffer (pH 6.0 with phosphoric acid) (35.8:19.2:45 by volume) and detected at 223 nm. The calibration curves of active metabolites M1 and M2 were linear in the range of 0.1-1.0 microg/mL and 0.15-1.8 microg/mL. This method was fully validated and shown to be specific, accurate (10.4-10.7% error), and precise (1.97-8.79% CV). This simple and rapid analytical method using column-switching appears to be useful for the pharmacokinetic study of active metabolites (M1 and M2) of sibutramine.

Column-switching high-performance liquid chromatographic analysis of fluvastatin in rat plasma by direct injection.

A column-switching high-performance liquid chromatographic (HPLC) method has been developed and validated for quantification of fluvastatin in rat plasma. Plasma samples were diluted with an equal volume of mobile phase, i.e. acetonitrile-5 mM potassium phosphate buffer (pH 6.8) (15:85, v/v), and the mixture was directly injected onto the HPLC system. The analyte was enriched in a pre-treatment column, while endogenous components were eluted to waste. The analyte was then back-flushed onto an analytical column and quantified with fluorescence detection (lambdaex=305 nm; lambdaem=390 nm). The standard curve for the drug was linear in the range 0.5-100 ng mL(-1) in rat plasma. The limit of quantitation for plasma was found to be 0.5 ng mL(-1). This method has been fully validated and shown to be specific, accurate and precise. The method is simple and rapid because of a minimized sample preparation and appears to be useful for the pharmacokinetic study of fluvastatin.

Prediction of the permeability of drugs through study on quantitative structure-permeability relationship.

This study is to research the quantitative structure-permeability relationship of 20 drugs having similar structure. Permeability was determined by using the Caco-2 cell in vitro model. The apparent permeability coefficient (Papp) of each drug both of apical to basolateral side and basolateral to apical side was measured at the concentration corresponding to 0.1 times the highest dose strength of 250 mL dissolved buffer. In order to test the permeability system suitability, we measured the Papp of 19 model drugs out of 20 which presented in 'Waiver of In Vivo Bioavailability and Bioequivalence Studies for Immediate-Release Solid Oral Dosage Forms based on the Biopharmaceutics Classification System' of FDA guidance. Also, we demonstrated the functional expression of efflux systems (e.g., p-gp) by bi-directional transport studies with rhodamine 123. Also, as a result of the study on quantitative structure-permeability relationship by using the partial least square method, it was possible to predict the permeability of drugs from their 3D structure. The quantitative structure-permeability relationship provided a cross-validated q2=0.789, a normal r2=0.998. Considering all of above results, analysis on this quantitative structure-permeability relationship appears to be a very useful tool to predict the permeability.

Column-switching high-performance liquid chromatographic method for the determination of zaltoprofen in rat plasma.

A direct injection column-switching high-performance liquid chromatography (HPLC) method was developed and validated for quantification of zaltoprofen in rat plasma. Following dilution with mobile phase A, i.e. acetonitrile-10mM potassium phosphate buffer (pH 6.8) (12:88, v/v) samples were directly injected to the pre-column without sample pre-purification step. After endogenous plasma components were eluted to waste, the system was switched and the analyte was eluted to the trap column. Zaltoprofen was then back-flushed to the analytical column for separation with mobile phase B, i.e. acetonitrile-10mM potassium phosphate buffer (pH 6.8) (35:65, v/v) and quantification with an ultraviolet detector at 230 nm. The calibration curve was linear in the concentration range of 40-5000 ngmL(-1). This method has been fully validated and shown to be specific, accurate and precise. The method is simple, rapid and the sample preparation is minimal and appears to be useful for the pharmacokinetic study of zaltoprofen.