A 1-step Bayesian predictive approach for evaluating in vitro in vivo correlation (IVIVC)

IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a functio...

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Bibliographic Details
Published in:Biopharmaceutics & drug disposition 2009-10, Vol.30 (7), p.366-388
Main Authors: Gould, A. Lawrence, Agrawal, Nancy G. B., Goel, Thanh V., Fitzpatrick, Shaun
Format: Article
Language:English
Subjects:
Absorption
Administration, Oral
Area Under Curve
bioavailability
Chemistry, Pharmaceutical - statistics & numerical data
Computational Biology - methods
Excipients - pharmacokinetics
Humans
Mathematics
pharmacokinetic
prediction
Solubility
Statistics as Topic
Therapeutic Equivalency
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Summary:IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a function of the cumulative in vivo absorption. The absorption is not directly observable, so is estimated by the cumulative dissolution of the drug formulation in in vitro dissolution trials. The calculations conventionally entail the complex and potentially unstable mathematical operations of convolution and deconvolution, or approximations aimed at omitting their need. This paper describes, and illustrates with data on a controlled‐release formulation, a Bayesian approach to evaluating IVIVC that does not require convolution, deconvolution or approximation. This approach incorporates between‐ and within‐subject (or replicate) variability without assuming asymptotic normality. The plasma concentration curve is expressed in terms of the in vitro dissolution percentage instead of time, recognizing that this correspondence may be noisy because of the various sources of error. All conventional functions of the concentration curve such as AUC, Cmax and Tmax can be expressed in terms of dissolution percentage, with uncertainties arising from variability in measuring absorption and dissolution accounted for explicitly. Copyright © 2009 John Wiley & Sons, Ltd.
ISSN:0142-2782
1099-081X
DOI:10.1002/bdd.672