Clinical Trials and Translational Medicine CommentariesPhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 2: Comparative assessment of prediction methods of human volume of distribution
Section snippets
INTRODUCTION
The kinetic processes associated with drug entry into the body through to drug exit from the body are usually considered broadly as discrete events of absorption, distribution, metabolism, elimination, and excretion. An important component of the overall pharmacokinetics (PK) of a drug is the rate and extent to which it reversibly moves from the systemic circulation into the peripheral organs and tissues. Incorrectly predicting the extent of drug distribution can result in a poor estimation of
METHODS
Empirical, semimechanistic, and mechanistic models were used to predict human Vss. Furthermore, an analysis of the inaccurate predictions was also made.
RESULTS
The observed human Vss for each compound together with the predicted Vss from each model are listed inTable 3. The overall statistical summary in terms of accuracy, precision, and correlation are listed in Table 4. The fold error of predicted human Vss for all 18 drugs are shown in Figure 1. The plot of observed versus predicted Vss values for each method is shown in Figure 2.
DISCUSSION
The aim of this present study was to evaluate the accuracy of 24 different prediction methods for the prediction of Vss using 18 blinded compounds for which human IV data were available. This is a unique dataset, representing a range of novel compounds from several pharmaceutical companies. The intended scientific benefit of this study was to obtain a greater appreciation and understanding of the predictive performance of methods available in the public domain.
The top performing methods rely on
CONCLUSION
We have shown how understanding the data and tools available/applied can help identify whether a prediction is likely to be accurate or not. There are several methods that when applied to a range of compounds result in moderate to accurate predictions of human Vss. There is not simply one method that predicts Vss accurately for all compounds. As a compound progresses through the different stages of drug discovery, the properties of the compound as well as the available data should be viewed
Acknowledgements
The authors kindly acknowledge Natalie Bolea, Michael Garvin, and Vail Fucci at PhRMA, Leslie Z. Benet at UCSF, Gregg Ludeen at Lilly, and Ken Korzekwa for their assistance and support. PhRMA kindly acknowledges Simulation Plus, Inc. (Lancaster, California) for providing their distribution model.
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This work was undertaken by the Pharmaceutical Research and Manufacturers of America (PhRMA), 950 F ST NW, Washington, District of Columbia 20004; Clinical and Preclinical Development Committee (CDCDC); Predictive Models of Human Pharmacokinetics Limited Duration Key Issue Team (LDKIT), previously known as a working group under the Pharmaceutical Innovation Steering Committee (PISC).