Indirect bioequivalence assessment using network meta-analyses

Aims For market approval, new drug formulations (test) must demonstrate bioequivalence (BE) to at least one approved formulation (reference). If several formulations of a drug are already on the market, one might have to show BE to more than one reference formulation. Similarly, if several test form...

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Bibliographic Details
Published in:	European journal of clinical pharmacology Vol. 70; no. 8; pp. 947 - 955
Main Authors:	Ring, A., Morris, T. B. S., Hohl, K., Schall, R.
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01-08-2014 Springer Springer Nature B.V
Subjects:	Bioavailability Biological and medical sciences Biomedical and Life Sciences Biomedicine Cross-Over Studies Drug therapy Humans Hypoglycemic Agents - pharmacokinetics Medical sciences Meta-analysis Meta-Analysis as Topic Metformin - pharmacokinetics Models, Statistical Pharmacokinetics and Disposition Pharmacology. Drug treatments Pharmacology/Toxicology Statistical analysis Therapeutic Equivalency Metformin Bioequivalence Indirect comparison Mixed-treatment comparison Human Evaluation Metaanalysis Hypoglycemic agent Biguanides Treatment Mixed Network Pharmacokinetics Comparative study
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Summary:	Aims For market approval, new drug formulations (test) must demonstrate bioequivalence (BE) to at least one approved formulation (reference). If several formulations of a drug are already on the market, one might have to show BE to more than one reference formulation. Similarly, if several test formulations have shown BE to a reference formulation, it will be of interest whether the test formulations are bioequivalent to each other. Methods An enhanced statistical model to assess BE indirectly through a network meta-analysis is provided. Statistical properties of a parallel and a bridging approach are derived, in particular the relative statistical efficiency of the two approaches. The analysis is illustrated using individual subject data from two 3×3 crossover trials of metformin formulations, which have one of the formulations in common. Results The parallel estimate of relative bioavailability is confounded with between-trial differences, while the bridging estimate is not. The standard errors of the formulation differences using the bridging approach are smaller than the standard errors using the parallel approach if the within-subject correlation in each trial of the network is larger than 0.5. This is the condition for a crossover trial to be more efficient than a parallel trial, and thus is usually fulfilled in pharmacokinetic crossover trials. Conclusions Indirect BE assessment offers the opportunity to efficiently determine the relative bioavailability of drug formulations that have not been studied in the same randomized BE trial. The methodology developed here allows estimating formulation differences across a larger network.
ISSN:	0031-6970 1432-1041
DOI:	10.1007/s00228-014-1691-0