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.
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© 1997 Plenum Press, New York
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Dunne, A., O’Hara, T., Devane, J. (1997). Approaches to IVIVR Modelling and Statistical Analysis. In: Young, D., Devane, J.G., Butler, J. (eds) In Vitro-in Vivo Correlations. Advances in Experimental Medicine and Biology, vol 423. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-6036-0_6
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DOI: https://doi.org/10.1007/978-1-4684-6036-0_6
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