Literature DB >> 7479556

The role of metabolites in bioequivalency assessment. II. Drugs with linear pharmacokinetics and first-pass effect.

M L Chen1, A J Jackson.   

Abstract

Simulations were conducted to address the question of whether metabolite data are required for bioequivalence evaluation of immediate release formulations with drugs exhibiting linear pharmacokinetics and first-pass effect. Plasma level-time profiles were generated for parent drug and metabolite using relevant rate constants obtained from a bivariate normal distribution and designated random error. Simulation results showed that the need for metabolite data (Cmax) in the assessment of bioequivalence depends on the relative variability between the absorption process of the drug and first-pass route for metabolite(s). The importance of metabolite Cmax data in the evaluation of rate of availability is clearly demonstrated for drugs with a high degree of intra-subject variation in the first-pass metabolism compared to the absorption process of the drug. Under such conditions, a wider confidence interval was found for the metabolite rather than parent drug. Opposite results were obtained when the intra-subject variance was high for drug absorption relative to first-pass effect. Discrepancies were observed for the scenarios in which the elimination pathway of the metabolite is more variable than the absorption process of the drug. The simulation results were in agreement with real bioequivalence data. It is thus recommended that, in the absence of the information on the relative variability of absorption and first-pass process, both parent drug and metabolite data be included for documentation of bioequivalence, should the metabolite(s) play an important role in the determination of efficacy and safety of the drug.

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Year:  1995        PMID: 7479556     DOI: 10.1023/a:1016259509257

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


  12 in total

1.  The role of metabolites in bioequivalency assessment. I. Linear pharmacokinetics without first-pass effect.

Authors:  M L Chen; A J Jackson
Journal:  Pharm Res       Date:  1991-01       Impact factor: 4.200

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3.  A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability.

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4.  Prediction of steady-state bioequivalence relationships using single dose data I-linear kinetics.

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8.  Conversational SAAM--an interactive program for kinetic analysis of biological systems.

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9.  An automated method for the determination of nortriptyline and its isomeric 10-hydroxylated metabolites in plasma by high pressure liquid chromatography.

Authors:  T I Lundgren; L Slørdal; R Jaeger; J E Whist; J Aarbakke
Journal:  Pharmacol Toxicol       Date:  1990-08

10.  Quantification of amitriptyline, nortriptyline, and 10-hydroxy metabolite isomers in plasma by capillary gas chromatography with nitrogen-sensitive detection.

Authors:  D R Jones; B J Lukey; H E Hurst
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  7 in total

1.  The role of metabolites in bioequivalency assessment. III. Highly variable drugs with linear kinetics and first-pass effect.

Authors:  A J Jackson
Journal:  Pharm Res       Date:  2000-11       Impact factor: 4.200

Review 2.  Metabolites and bioequivalence: past and present.

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3.  Physiological modeling to understand the impact of enzymes and transporters on drug and metabolite data and bioavailability estimates.

Authors:  Huadong Sun; K Sandy Pang
Journal:  Pharm Res       Date:  2010-04-06       Impact factor: 4.200

Review 4.  Effects of food on the clinical pharmacokinetics of anticancer agents: underlying mechanisms and implications for oral chemotherapy.

Authors:  Brahma N Singh; Bimal K Malhotra
Journal:  Clin Pharmacokinet       Date:  2004       Impact factor: 6.447

5.  Equivalence-by-design: targeting in vivo drug delivery profile.

Authors:  Mei-Ling Chen; Vincent H L Lee
Journal:  Pharm Res       Date:  2008-10-28       Impact factor: 4.200

Review 6.  Bioavailability and bioequivalence: focus on physiological factors and variability.

Authors:  Vangelis Karalis; Panos Macheras; Achiel Van Peer; Vinod P Shah
Journal:  Pharm Res       Date:  2008-06-13       Impact factor: 4.200

7.  The Two Main Goals of Bioequivalence Studies.

Authors:  Laszlo Endrenyi; Henning H Blume; Laszlo Tothfalusi
Journal:  AAPS J       Date:  2017-02-02       Impact factor: 4.009

  7 in total

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