Limited-sampling strategy models for estimating the pharmacokinetic parameters of 4-methylaminoantipyrine, an active metabolite of dipyrone

Suarez‐Kurtz, Guilherme; Ribeiro, Frederico Mota; Estrela, Rita C. E.; Vicente, Flávio L.; Struchiner, Cláudio J.

doi:10.1590/s0100-879x2001001100017

Cited by 15 publications

(10 citation statements)

References 12 publications

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“…The results for T max were consistent with the results (range 1-2) reported by Levy M et al and Volz M et al 3,9 . The mean (SD) t 1/2 was 6.99±1.23 hours for the test formulation and 6.79±2.74 hours for the reference formulation which was slightly longer than the t 1/2 (4.4 ± 2.8 h) reported by Suarez-Kurtz G et al 2 .…”

Section: Resultscontrasting

confidence: 49%

“…Because the analgesic effect of dipyrone correlates with the time course of 4-methyl aminoantipyrine concentrations in serum 2,7 , pharmacokinetic parameters pertaining to this active metabolite are appropriate for assessing the bioequivalence of dipyrone formulations. Most of a dose is excreted in the urine as metabolites.…”

Section: Dhaneshwar Shepmentioning

confidence: 99%

“…Dipyrone is a prodrug, and its pharmacokinetics has been extensively investigated 2,3 . After oral or intravenous administration, dipyrone is rapidly hydrolyzed to the active moiety 4-methylamino antipyrine (MAA) 4,5 .…”

Section: Introductionmentioning

confidence: 99%

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2012

IJPSR

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Background: Metamizole (Dipyrone) is widely used and has effective analgesic, antipyretic, and antispasmodic properties. After oral or intravenous administration, dipyrone is rapidly hydrolyzed to the active moiety 4-methylaminoantipyrine. Aim: The aim of this study was to assess the bioequivalence of 2 oral formulations of Metamizole 500 mg. Methods: This double blind, randomized, single-dose, 2-period crossover study in healthy Indian adult volunteers was conducted at PERD Centre, Ahmedabad. Subjects received Metamizole 500 mg of either test or reference formulation with a washout period of 7 days. After study drug administration, serial blood samples were collected over a period of 24 hours. Plasma concentration of 4-methylaminoantipyrine was measured by pre-validated LC-MS method. Pharmacokinetic (PK) parameters C max , T max , t 1/2 , AUC 0-t , AUC 0-∞ , and k el , were determined for test and reference formulations. The formulations were to be considered bioequivalent if the log-transformed ratios of C max , AUC 0-t , and AUC 0-∞ were within the predetermined bioequivalence range of 80% to 125%. Results: A total of 14 subjects were enrolled. No significant differences were found based on analysis of variance, with mean values and 90% confidence intervals of test/reference ratios for these parameters as follows: C max , 18.24 versus 18.44 μg/mL (92.68 -106.61); AUC 0-t , 92.97 Versus 91.37 μg.hr/mL (89.49 -113.09); and AUC 0-∞ , 96.64 Versus 94.65 μg.hr/mL (92.31 -111.63). Conclusion: Since the 90% confidence intervals for C max , AUC 0-t , and AUC 0−∞ were within the interval of 80-125%, it was concluded that both formulations were bioequivalent, according to both the rate and extent of absorption.

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Section: Resultscontrasting

confidence: 49%

Section: Dhaneshwar Shepmentioning

confidence: 99%

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2012

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“…Jackknife validation of the limited sampling strategy equations was performed using sas 9.1 (SAS Inc., Cary, NC, USA) [16]. For jackknife validation, the regression equation for the prediction of AUC 0–12 was derived in a subset of patients (28 patients) including concentrations at n fixed time points.…”

Section: Methodsmentioning

confidence: 99%

A limited sampling strategy for tacrolimus in renal transplant patients

Mathew¹,

Fleming²,

Jeyaseelan³

et al. 2008

Brit J Clinical Pharma

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WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Tacrolimus trough concentration is being currently used for dose individualization.• Limited sampling strategies (LSS) have been developed and validated for renal transplant patients.• Earlier literature has suggested that measurement of tacrolimus AUC is more reliable than trough with respect to both rejection and nephrotoxicity. WHAT THIS STUDY ADDS• Four thousand renal transplants take place annually in India, with many patients prescribed tacrolimus in combination with mycophenolate and steroid.• In this study a LSS with two points, i.e. trough and 1.5 h postdose was developed and validated to estimate AUC0-12.• The added benefit of only a single additional sample with completion of blood collection in 1.5 h and minimum additional cost makes this a viable LSS algorithm in renal transplant patients.• In patients having tacrolimus trough concentrations outside the recommended range (<3 and >10 ng ml -1 in the treatment protocol in our institution) or having side-effects in spite of trough concentrations in the desired range, we can estimate AUC using this LSS for a better prediction of exposure. AIMSTo develop and validate limited sampling strategy (LSS) equations to estimate area under the curve (AUC0-12) in renal transplant patients. METHODSTwenty-nine renal transplant patients (3-6 months post transplant) who were at steady state with respect to tacrolimus kinetics were included in this study. The blood samples starting with the predose (trough) and collected at fixed time points for 12 h were analysed by microparticle enzyme immunoassay. Linear regression analysis estimated the correlations of tacrolimus concentrations at different sampling time points with the total measured AUC0-12. By applying multiple stepwise linear regression analysis, LSS equations with acceptable correlation coefficients (R 2 ), bias and precision were identified. The predictive performance of these models was validated by the jackknife technique. RESULTSThree models were identified, all with R 2 Ն 0.907. Two point models included one with trough (C0) and 1.5 h postdose (C1.5), another with trough and 4 h postdose. Increasing the number of sampling time points to more than two increased R 2 marginally (0.951 to 0.990). After jackknife validation, the two sampling time point (trough and 1.5 h postdose) model accurately predicted AUC0-12. Regression coefficient R 2 = 0.951, intraclass correlation = 0.976, bias [95% confidence interval (CI)] 0.53% (-2.63, 3.69) and precision (95% CI) 6. 35% (4.36, 8.35). CONCLUSIONThe two-point LSS equation .C0) + (3.33.C1.5)] can be used as a predictable and accurate measure of AUC0-12 in stable renal transplant patients prescribed prednisolone and mycophenolate.

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“…As the first active metabolite of metamizole, 4‐MAA reaches its peak plasma concentration within 1 to 2 hours and is further metabolized in the liver to both a second active metabolite, 4‐aminoantipyrine (4‐AA), via N‐demethylation, and a first inactive metabolite, 4‐formylaminoantipyrine (4‐FAA), via C‐oxidation . Up to now, hepatic metabolism of 4‐MAA was known to be mediated by the cytochrome P450 (CYP) 3A4 system .…”

Section: Hepatic Metabolism Of Metamizolementioning

confidence: 99%

Metamizole (Dipyrone) and the Liver: A Review of the Literature

Lutz

2019

The Journal of Clinical Pharma

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Metamizole, also known as dipyrone, was introduced to the market nearly a century ago. Due to its excellent analgesic, antipyretic, and spasmolytic properties combined with its mostly favorable gastrointestinal tolerability, the drug was extensively applied worldwide during the first decades after its market introduction. Although rare, agranulocytosis is a well‐known adverse event of metamizole and led to its withdrawal from the market in a number of countries beginning in the 1960s. Nevertheless, metamizole is still a frequently used drug worldwide either legally (by prescription in some countries, over the counter in other countries) or without official approval (especially by immigrants knowing the drug from their home countries) or even illegally (due to its growing application as an adulterant in illicit drugs). Metamizole undergoes extensive metabolism in the liver and cases of potential metamizole‐associated hepatotoxicity have been described. Here, the literature is extensively reviewed for the first time regarding hepatic effects associated with the use of metamizole.

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Limited-sampling strategy models for estimating the pharmacokinetic parameters of 4-methylaminoantipyrine, an active metabolite of dipyrone

Cited by 15 publications

References 12 publications

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A limited sampling strategy for tacrolimus in renal transplant patients

Metamizole (Dipyrone) and the Liver: A Review of the Literature

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