Grapefruit juice-nifedipine interaction: possible involvement of several mechanisms

Odou, Pascal; Ferrari, Nicoletta; Barthélémy, Christine; Brique, Serge A.; Lhermitte, Michel; Vincent, Anne; Libersa, Christian; Robert, H.

doi:10.1111/j.1365-2710.2004.00618.x

Cited by 26 publications

(18 citation statements)

References 22 publications

(27 reference statements)

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“…In particular, the similarity in the composition of GFJ and orange juice, which was used as baseline control in a number of studies and the failure of orange juice to change the AUC of a drug administered concomitantly made an effect of GFJ on F a unlikely. To our knowledge no conclusive data are available to confirm that the fraction absorbed is indeed unchanged under GFJ treatment as only three studies reported very limited data on the effect of GFJ on F a [42,89,90]. However, GFJ has recently been reported to inhibit intestinal uptake transporters (OATP1A2 and OATP2B1) [76][77][78][79][80].…”

Section: Limitations Of the Methods To Estimate F Gmentioning

confidence: 72%

Grapefruit Juice-Drug Interaction Studies as a Method to Assess the Extent of Intestinal Availability: Utility and Limitations

Gertz¹,

Davis²,

Harrison³

et al. 2008

CDM

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This study aims to assess utility and limitations of grapefruit juice (GFJ) interaction studies as alternative in vivo approach to estimate intestinal availability (F(G)) in comparison to the predominantly used i.v./oral method. The F(G) estimates were obtained from the ratio of AUC in the control and the GFJ group reported previously. Due to large variability in the study design, the following inclusion criteria were applied for the selection of clinical studies: no change in elimination half-life in the presence of GFJ, administration of GFJ with or up to 4 h before drug intake, and a reported significant increase in AUC in the presence of GFJ. Weighted mean F(G) values were compared to estimates from i.v./oral data. Additionally, inter-study and inter-individual variation of GFJ F(G) estimates was assessed by meta-analysis for drugs with multiple studies reported. F(G) values ranged from 0.07 to 0.92 for lovastatin and quinidine, respectively. Overall, the inter-individual variation in GFJ F(G) estimates (16-54%) was higher than the inter-study (5.7-39%) with the exception of nisoldipine and simvastatin where inter-study variations of 53-88% were observed. Weighted average GFJ F(G) estimates were comparable to i.v./oral, supporting the application of this approach as an alternative to i.v./oral data for predominantly metabolised drugs (r(2) = 0.65; n=10). In contrast, this approach is of limited use for drugs whose disposition is co-dependent on efflux/uptake transporters and metabolic enzymes. An area of high intestinal extraction (F(G) < or = 0.25) is identified as problematic, as availability of conclusive data is limited in this area.

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Section: Limitations Of the Methods To Estimate F Gmentioning

confidence: 72%

Grapefruit Juice-Drug Interaction Studies as a Method to Assess the Extent of Intestinal Availability: Utility and Limitations

Gertz¹,

Davis²,

Harrison³

et al. 2008

CDM

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“…In the PBPK approach, nifedipine was, in contrast to the other three APIs, treated as a neutral compound, as it was reasonable to assume that the API is not ionised under most gastrointestinal conditions …”

Section: Resultsmentioning

confidence: 99%

Forecasting oral absorption across biopharmaceutics classification system classes with physiologically based pharmacokinetic models

Hansmann

Darwich

Margolskee

et al. 2016

Journal of Pharmacy and Pharmacology

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“…Mean observed data are overlaid (filled circles: historical control profile taken from refs. 18 , 32 , 33 , 34 ; closed circles: T 3 profile taken from ref. 17 .…”

Section: Resultsmentioning

confidence: 99%

A PBPK Model to Predict Disposition of CYP3A‐Metabolized Drugs in Pregnant Women: Verification and Discerning the Site of CYP3A Induction

Nallani

Zhao

et al. 2012

CPT Pharmacom & Syst Pharma

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Besides logistical and ethical concerns, evaluation of safety and efficacy of medications in pregnant women is complicated by marked changes in pharmacokinetics (PK) of drugs. For example, CYP3A activity is induced during the third trimester (T3). We explored whether a previously published physiologically based pharmacokinetic (PBPK) model could quantitatively predict PK profiles of CYP3A-metabolized drugs during T3, and discern the site of CYP3A induction (i.e., liver, intestine, or both). The model accounted for gestational age-dependent changes in maternal physiological function and hepatic CYP3A activity. For model verification, mean plasma area under the curve (AUC), peak plasma concentration (Cmax), and trough plasma concentration (Cmin) of midazolam (MDZ), nifedipine (NIF), and indinavir (IDV) were predicted and compared with published studies. The PBPK model successfully predicted MDZ, NIF, and IDV disposition during T3. A sensitivity analysis suggested that CYP3A induction in T3 is most likely hepatic and not intestinal. Our PBPK model is a useful tool to evaluate different dosing regimens during T3 for drugs cleared primarily via CYP3A metabolism.

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Grapefruit juice-nifedipine interaction: possible involvement of several mechanisms

Abstract: This study shows that grapefruit juice interferes with the metabolism of NIF by inhibiting NIF metabolism and slowing down the rate of gastric emptying. This study also confirms that the metabolic inhibition is not a first pass effect, but is a secondary oxidative step.

Cited by 26 publications

References 22 publications

Grapefruit Juice-Drug Interaction Studies as a Method to Assess the Extent of Intestinal Availability: Utility and Limitations

Grapefruit Juice-Drug Interaction Studies as a Method to Assess the Extent of Intestinal Availability: Utility and Limitations

Forecasting oral absorption across biopharmaceutics classification system classes with physiologically based pharmacokinetic models

A PBPK Model to Predict Disposition of CYP3A‐Metabolized Drugs in Pregnant Women: Verification and Discerning the Site of CYP3A Induction

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