A Kinetic Study of Drug Elimination: The Excretion of Paracetamol and Its Metabolites in Manmetabolites in Man

Cummings, A. J.; King, Margaret L.; Martin, B. K.

doi:10.1111/j.1476-5381.1967.tb01948.x

Cited by 132 publications

(63 citation statements)

References 7 publications

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“…Acetaminophen is one of the most widely used nonprescription medicines in the world and its toxicology and metabolism have been extensively investigated over many years (14)(15)(16)(17)(18)(19)(20). However, we will show here that, even for this most familiar drug, pharmacometabonomic analysis will yield significantly increased understanding of its metabolic behavior in humans.…”

mentioning

confidence: 99%

Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism

Clayton

Baker

Lindon

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

696

573

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We provide a demonstration in humans of the principle of pharmacometabonomics by showing a clear connection between an individual's metabolic phenotype, in the form of a predose urinary metabolite profile, and the metabolic fate of a standard dose of the widely used analgesic acetaminophen. Predose and postdose urinary metabolite profiles were determined by 1 H NMR spectroscopy. The predose spectra were statistically analyzed in relation to drug metabolite excretion to detect predose biomarkers of drug fate and a human-gut microbiome cometabolite predictor was identified. Thus, we found that individuals having high predose urinary levels of p-cresol sulfate had low postdose urinary ratios of acetaminophen sulfate to acetaminophen glucuronide. We conclude that, in individuals with high bacterially mediated p-cresol generation, competitive O-sulfonation of p-cresol reduces the effective systemic capacity to sulfonate acetaminophen. Given that acetaminophen is such a widely used and seemingly well-understood drug, this finding provides a clear demonstration of the immense potential and power of the pharmacometabonomic approach. However, we expect many other sulfonation reactions to be similarly affected by competition with p-cresol and our finding also has important implications for certain diseases as well as for the variable responses induced by many different drugs and xenobiotics. We propose that assessing the effects of microbiome activity should be an integral part of pharmaceutical development and of personalized health care. Furthermore, we envisage that gut bacterial populations might be deliberately manipulated to improve drug efficacy and to reduce adverse drug reactions.T he effects of drug treatments can vary greatly between different individuals, and pharmacogenomics has been widely advocated as a potential means of personalizing human drug treatments to increase drug efficacy and to decrease adverse reactions (1-6). However, environmental factors (such as nutritional status, gut bacterial activities, age, disease, and other drug use) are also important determinants of individual metabolic phenotypes, which modulate drug metabolism, efficacy, and toxicity. Such environmental complications, which may also alter gene expression, will tend to limit the usefulness of predictions of drug-induced responses that are based only on genomic differences (7,8). For instance, for many classes of compound, enzyme induction state, which is environmentally determined, influences drug metabolism and toxicity and this is not captured in genomic data. Recognizing this important limitation of pharmacogenomics, a different approach to personalized drug treatment has recently been proposed wherein predose metabolite profiling would instead be used to predict a subject's responses to potential drug interventions (9). This ''pharmacometabonomic'' approach has a number of major advantages, which include the ready availability and relative ease of analysis of biofluids, such as urine and blood plasma, as well as the fact that ...

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mentioning

confidence: 99%

Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism

Clayton

Baker

Lindon

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

696

573

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“…The dye is absorbed from the blood into the liver so rapidly that the rate of uptake may be neglected in formulating the model. This approach is analogous to the pharmacokinetic practice of neglecting a rapid absorptive process in the determination of elimination rate constants after oral administration of drug (Cummings, King & Martin, 1967 The rate constant (k1) for the removal of the first methyl group from methyl orange was generally somewhat less than that for the second methyl group (I2). Taking into account the higher error of k2, and the fact that in group 3 (Table 3), k2 was actually a little less than ki, it may be concluded that there is not a large difference in the two rate constants.…”

Section: Discussionmentioning

confidence: 99%

“…Most studies have considered systems in which drug metabolism is represented as a single first-order process, for example, the acetylation of sulphonamides (Nelson & O'Reilly, 1960;Yamazaki, Aoki & Kamada, 1968). Somewhat more complex systems, in which several metabolites are produced by parallel first-order processes, have been studied by Cummings, King & Martin (1967) with paracetamol, and by Nogami, Hasegawa, Hanano & Imaoka (1968) with sulphonamides. The most common biochemical path for drug metabolism involves two successive reactions: first, metabolical alteration, and then conjugation of-the metabolite (Williams, 1959).…”

Section: Introductionmentioning

confidence: 99%

Pharmacokinetic model for the successive demethylation and biliary secretion of methyl orange in the rat

O'Reilly

Pitt

Ryan

1971

British J Pharmacology

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Summary1. A one-compartment pharmacokinetic model was developed in which a drug underwent two successive metabolical reactions (for example, metabolism followed by conjugation) and free drug and both metabolites were excreted. 2. Techniques were described whereby graphical estimates of the first-order rate constants may be derived from cumulative excretion data on the drug and its metabolites. Computer simulation techniques were used to show that the experimental data permit reasonably accurate estimation of the rate constants of the model by graphical and computer methods. 3. Tritiated methyl orange (2 mg) was administered to five groups of six rats with biliary cannulation. The bile produced by each animal was collected at hourly intervals for 6 h and the amounts of methyl orange and its metabolites, 4'sulpho-4-methylaminoazobenzene and 4'sulpho-4-aminoazobenzene, determined by thin layer chromatography and radioactive counting techniques. 4. The data were analysed graphically and with an iterative digital computer programme to yield the first-order rate constants for the successive demethylation steps in the metabolism of methyl orange. The removal of the first methyl group had a rate constant of 0-684+0-142 h-1 (+S.D.) and the second methyl group 100+0-302 h-1. The rate constant for biliary excretion of the free methyl orange was 0-164+0-042 h-1,-for the monomethyl derivative 0-672+ 0-461 h-i, and for the demethylated metabolite 6-413 + 3.222 h-1.

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“…Only 4% of ingested paracetamol is excreted unchanged in the urine. 8 In patients who develop liver damage, however, metabolism is delayed.5 The hepatic toxicity seems to occur rapidly after absorption of the drug and the slow metabolism is thought to be the result rather than the cause of the liver damage. Perhaps for this reason earlier treatments (including corticosteroids and antihistamines,9 heparin,'0 haemodialysis," and charcoalcolumn haemoperfusion12) all failed to prevent liver damage in severely poisoned patients.…”

Section: Treatment Of Acute Paracetamol Poisoningmentioning

confidence: 99%

Treatment of acute paracetamol poisoning.

Jones¹,

Thomas²

1977

BMJ

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A Kinetic Study of Drug Elimination: The Excretion of Paracetamol and Its Metabolites in Manmetabolites in Man

Cited by 132 publications

References 7 publications

Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism

Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism

Pharmacokinetic model for the successive demethylation and biliary secretion of methyl orange in the rat

Treatment of acute paracetamol poisoning.

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