Incorporating Interindividual Variability into “In Vitro – In Vivo Extrapolation”

A. Rostami-Hodjegan, A. Tooley, G.T.Tucker

University of Sheffield, Section of Medicine and Pharmacology, Clinical Sciences Division, Royal Hallamshire Hospital, Sheffield S102JF UK

There has been a growing interest in the possibility of predicting in vivo drug-drug interactions from in vitro data during last 10 years (1). Previous studies have based these predictions only on mean data (2). Clearly, there is a degree of uncertainty associated with using such data in that the risk to individuals is not evaluated. Recently, it has been re-emphasised that interpretation of interaction studies should focus on the observed and theoretically conceivable extreme effects in individual subjects (3).

Using SIMCYP, a program written in MathCad 6.0, we have been able to show the impact of inter-individual variability with respect to the short term inhibition of drug metabolism (4). In predicting “long-term” interactions, however, variability in induction should also be considered. For instance, simulation of acute interaction between ritonavir and methadone (day 1) resulted in a mean 1.4 fold increase in Css of methadone (95% likelihood of 1.2-1.8). However, continued ritonavir therapy (day 21) showed return of methadone Css to its pre-ritonavir-treatment level in the population average (95% likelihood 0.6-1.3 fold). Thus, more than half of the population showed a fall in plasma methadone level rather than an increase which was consistent with recent reports on clinical consequences (withdrawal syndromes) following long-term co-administration of ritonavir (or other similar antiviral drugs) and methadone (5).

More emphasis should be placed on considering inter-individual variability and the importance of study design in relation to exposure time during interaction studies.

References

  1. Tucker GT: The rational selection of drug-interaction studies implications of recent advances in drug metabolism. Int J Clin Pharm Ther 30 (1992) 550-553
  2. von Moltke LL Greenblatt DJ, Schmider J, Wright CE, Harmatz JS, Shader RI: In vitro approaches to predicting drug interactions in vivo. Biochem Pharmacol 67 (1998) 335-341
  3. Krayenbühl JC, Vozeh S, Kondo-Oestreicher M, Dayer P. Drug-drug interactions of new active substances: mebefradil example. Eur J Clin Pharmacol 55 (1999) 559-565
  4. Tooley A, Rostami-Hodjegan A, Lennard MS, Tucker GT. Acute inhibition of methadone metabolism by ritonavir: projection of interindividual variability from in vitro data. Br J Clin Pharmacol 48 (199) 883P
  5. Geletcko SM, Erickson AD. Decreased methadone effect after ritonavir initiation. Pharmacotherapy 20 (2000) 93-94

 

Reference: PAGE 10 (2001) Abstr 234 [www.page-meeting.org/?abstract=234]

Poster: poster