Impact of chronic inflammation on the pharmacokinetic–pharmacodynamic relationship of naproxen

Huntjens, Dymphy; Spalding, David J.; Danhof, Meindert; Pasqua, Oscar E. Del la

doi:10.1016/j.ejpain.2009.05.017

Cited by 4 publications

(5 citation statements)

References 21 publications

(24 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It was found that FCA-induced arthritic rats had higher basal levels of PGE 2 in the plasma, although no significance was found because of large inter-individual variability. A large degree of inter-individual variability for PGE 2 has also been shown in other reports [16,26] . Similarly, such variability is often observed in levels of other endogenous compounds [27,28] .…”

Section: Discussionsupporting

confidence: 78%

“…Due to the possibility of repeated measurements and increased reproducibility and sensitivity, PGE 2 could be a suitable alternative endpoint for investigations and comparisons of the time-course and potency of various drug candidates [23] . Several reports have shown the integrated PK-PD modeling of NSAIDs using hyperthermia, hyperalgesia, edema or PGE 2 as pharmacological endpoints [5,11,23] , but little attention has been paid to the impact of the disease status on drug effects [16] . The aim of this study was to characterize the PK-PD modeling of diclofenac in normal and FCA-induced arthritic rats using PGE 2 as a pharmacological endpoint.…”

Section: Discussionmentioning

confidence: 99%

“…This indicates that PGE 2 can be used as a specific biomarker to explain and understand the variability in the therapeutic of these drugs [12] . Recently, efforts have been made to establish the relationship between biomarkers, pain measurement and safety [13][14][15][16] . However, information on the integrated pharmacokinetic-pharmacodynamic profiles of these drugs under normal and chronic inflammatory conditions is still limited.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Pharmacokinetic-pharmacodynamic modeling of diclofenac in normal and Freund's complete adjuvant-induced arthritic rats

Zhang

Guo

et al. 2012

Acta Pharmacol Sin

View full text Add to dashboard Cite

Aim: To characterize pharmacokinetic-pharmacodynamic modeling of diclofenac in Freund's complete adjuvant (FCA)-induced arthritic rats using prostaglandin E 2 (PGE 2 ) as a biomarker. Methods: The pharmacokinetics of diclofenac was investigated using 20-day-old arthritic rats. PGE 2 level in the rats was measured using an enzyme immunoassay. A pharmacokinetic-pharmacodynamic (PK-PD) model was developed to illustrate the relationship between the plasma concentration of diclofenac and the inhibition of PGE 2 production. The inhibition of diclofenac on lipopolysaccharide (LPS)-induced PGE 2 production in blood cells was investigated in vitro. Results: Similar pharmacokinetic behavior of diclofenac was found both in normal and FCA-induced arthritic rats. Diclofenac significantly decreased the plasma levels of PGE 2 in both normal and arthritic rats. The inhibitory effect on PGE 2 levels in the plasma was in proportion to the plasma concentration of diclofenac. No delay in the onset of inhibition was observed, suggesting that the effect compartment was located in the central compartment. An inhibitory effect sigmoid I max model was selected to characterize the relationship between the plasma concentration of diclofenac and the inhibition of PGE 2 production in vivo. The I max model was also used to illustrate the inhibition of diclofenac on LPS-induced PGE 2 production in blood cells in vitro. Conclusion: Arthritis induced by FCA does not alter the pharmacokinetic behaviors of diclofenac in rats, but the pharmacodynamics of diclofenac is slightly affected. A PK-PD model characterizing an inhibitory effect sigmoid I max can be used to fit the relationship between the plasma PGE 2 and diclofenac levels in both normal rats and FCA-induced arthritic rats.

show abstract

Section: Discussionsupporting

confidence: 78%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Pharmacokinetic-pharmacodynamic modeling of diclofenac in normal and Freund's complete adjuvant-induced arthritic rats

Zhang

Guo

et al. 2012

Acta Pharmacol Sin

View full text Add to dashboard Cite

show abstract

“…The NPX concentration-response relationship in RA was explored (Dunagan et al, 1988;Day et al, 1995), but only a trend was obtained and the pharmacokinetics (PK) and pharmacodynamics (PD) of NPX were not quantitatively analyzed. Recent studies (Huntjens et al, 2006(Huntjens et al, , 2010 assessed the correlation between in vitro and in vivo exposure-effect relationships of NPX as well as the impact of chronic inflammation on the PK/PD of NPX. However, the nonlinear PK behavior of NPX was not considered.…”

Section: Introductionmentioning

confidence: 99%

Modeling Sex Differences in Pharmacokinetics, Pharmacodynamics, and Disease Progression Effects of Naproxen in Rats with Collagen-Induced Arthritis

DuBois

Almon

et al. 2017

Drug Metab Dispos

View full text Add to dashboard Cite

Naproxen (NPX) is a frequently used nonsteroidal anti-inflammatory drug for rheumatoid arthritis (RA). Lack of quantitative information about the drug exposure-response relationship has resulted in empirical dosage regimens for use of NPX in RA. Few studies to date have included sex as a factor, although RA predominates in women. A pharmacokinetic, pharmacodynamic, and disease progression model described the anti-inflammatory effects of NPX in collagen-induced arthritic (CIA) male and female rats. Three groups of rats were included for each sex: healthy animals, CIA controls, and CIA rats given a single 50-mg/kg dose of NPX intraperitoneally. Paw volumes of healthy rats indicated natural growth, and disease status was measured by paw edema. An innovative minimal physiologically based pharmacokinetic (mPBPK) model incorporating nonlinear albumin binding of NPX in both plasma and interstitial fluid (ISF) was applied. Arthritic rats exhibited lower plasma and ISF albumin concentrations and reduced clearances of unbound drug to explain pharmacokinetic profiles. The unbound ISF NPX concentrations predicted by the mPBPK model were used as the driving force for pharmacological effects of NPX. A logistic growth function accounting for natural paw growth and an indirect response model for paw edema and drug effects (inhibition of ) was applied. Female rats showed a higher incidence of CIA, earlier disease onset, and more severe symptoms. NPX had stronger effects in males, owing to higher unbound ISF NPX concentrations and lower IC values. The model described the pharmacokinetics, unbound NPX in ISF, time course of anti-inflammatory effects, and sex differences in CIA rats.

show abstract

“…The main modifications consisted of the additional collection of biomarker data from animals and the choice to treat histological observations as a continuous data type. The incorporation of biomarkers into the assessment of long‐term toxicity enabled us to further understand time dependencies and nonlinearities in downstream effects related to the primary pharmacological target (Huntjens et al ., ).…”

Section: Discussionmentioning

confidence: 98%

Model‐based prediction of the acute and long‐term safety profile of naproxen in rats

Sahota

Sanderson

Danhof

et al. 2015

British J Pharmacology

Self Cite

View full text Add to dashboard Cite

BACKGROUND AND PURPOSEDespite the increasing importance of biomarkers as predictors of drug effects, toxicology protocols continue to rely on the experimental evidence of adverse events (AEs) as a basis for establishing the link between indicators of safety and drug exposure. Furthermore, biomarkers may facilitate the translation of findings from animals to humans. Combined with a model-based approach, biomarker data have the potential to predict long-term effects arising from prolonged drug exposure. Here, we used naproxen as a paradigm to explore the feasibility of a biomarker-guided approach for the prediction of long-term AEs in humans. EXPERIMENTAL APPROACHAn experimental toxicology protocol was set up for evaluating the effects of naproxen in rats, in which four active doses were tested (7.5, 15, 40 and 80 mg·kg −1 ). In addition to AE monitoring and histology, a few blood samples were also collected for the assessment of drug exposure, TXB2 and PGE2 levels. Non-linear mixed effects modelling was used to analyse the data and identify covariate factors on the incidence and severity of AEs. KEY RESULTSModelling results showed that besides drug exposure, maximum PGE2 inhibition and treatment duration were also predictors of gastrointestinal ulceration. Although PGE2 levels were clearly linked to the incidence rates, it appeared that ulceration severity is better predicted by measures of drug exposure. CONCLUSIONS AND IMPLICATIONSThese results show that the use of a model-based approach provides the opportunity to integrate pharmacokinetics, pharmacodynamics and toxicity data, enabling optimization of the design, analysis and interpretation of toxicology experiments. AbbreviationsAUC, area under the concentration versus time curve; CAOC, cumulative area over biomarker concentration versus time profile; CMAX, maximum drug concentration over the period of 24 h; CMIN, maximum biomarker inhibition over the period of 24 h;

show abstract

Impact of chronic inflammation on the pharmacokinetic–pharmacodynamic relationship of naproxen

Cited by 4 publications

References 21 publications

Pharmacokinetic-pharmacodynamic modeling of diclofenac in normal and Freund's complete adjuvant-induced arthritic rats

Pharmacokinetic-pharmacodynamic modeling of diclofenac in normal and Freund's complete adjuvant-induced arthritic rats

Modeling Sex Differences in Pharmacokinetics, Pharmacodynamics, and Disease Progression Effects of Naproxen in Rats with Collagen-Induced Arthritis

Model‐based prediction of the acute and long‐term safety profile of naproxen in rats

Contact Info

Product

Resources

About