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Approaches to IVIVR Modelling and Statistical Analysis

  • Adrian Dunne
  • Tom O’Hara
  • John Devane
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 423)

Abstract

The current general approach to the development of a level A in vivo-in vitro correlation (IVIVC) is open to criticism in two major respects. The statistical methodology used is not based on the statistical properties of the data being analysed and consequently parameter estimates may be biased and the analysis may be inefficient. The second criticism is that a linear model is used and this is clearly very restrictive and limits the number of instances where we might expect to find such a relationship. This chapter addresses both of these issues. New statistical methods for the current linear model are proposed and their effectiveness demonstrated by means of a simulation experiment. In addition, new non-linear models which are generalisations of the linear model are proposed together with appropriate statistical methodology for fitting them. These models are shown to have some promise by using them to describe the in vivo-in vitro relationship for a number of batches of an extended release drug product.

Keywords

Fitted Curve Dosage Unit Proportional Odds Model Chlorpheniramine Maleate Operating Characteristic Curve 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Plenum Press, New York 1997

Authors and Affiliations

  • Adrian Dunne
    • 1
  • Tom O’Hara
    • 2
  • John Devane
    • 2
  1. 1.IVIVR Co-operative Working Group Department of StatisticsUniversity College DublinDublin 4Ireland
  2. 2.IVIVR Co-operative Working GroupÉlan Corporation plcMonksland, AthloneIreland

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