RESPONSE: PREDICTING THE CLEARANCE OF CYP2C9 SUBSTRATES Received September 14, 2004; accepted September 14, 2004 The key message in the article is that the value of the available in vitro metabolism data must be confirmed before they reliably can be used for quantitative predictions of in vivo metabolic clearance. In the pharmaceutical industry, in vitro metabolism data are often used early in the discovery process as selection tools to identify useful com- pounds for further development. Microsomes or hepatocytes are used to measure metabolic stability of new chemical entities and the half-lives of the compound are used to estimate CL int . Factors such as blood-plasma ratio, microsomal binding, plasma protein binding, ex- trahepatic metabolism, hepatocellular concentrations, etc. are rarely known. Our experience is that many chemical programs in early discovery suffer from a serious lack of in vitro-in vivo correlation, with numerous examples of both under- and over-predictions. In many cases this is because relevant data are lacking, but for many com- pounds the predictions have also been poor in retrospective studies when the clearance mechanisms and the metabolism of the compound have been well described. One explanation for this may be that there are components used in the equations for scaling that are missing or uncertain. The estimation of CL int (including the protein binding factors) and the relevant concentration of the drug for calculation of drug-drug interaction potential (not discussed in this letter) should be areas of more research. With all the uncertainties in predicting clear- ance and drug-drug interaction potential of new chemical entities, the pharmaceutical industry should carefully evaluate their use of in vitro metabolism data as selection tools in order not to discard compounds that could be otherwise developed into valuable drugs. Rowland et al. (2004) comment on the importance of considering all metabolic pathways and to take fu b into account to be able to better estimate in vivo clearance of a study compound. Of course we agree that variables known to affect metabolic clearance should be consid- ered for scaling purposes. For the compounds used in our study, an abundance of information is available since they have been on the market for many years. Including fu b in the calculations would in- crease the predicted clearance but still greatly under-predict measured blood clearance for the tested drugs, except for fluvastatin. Fluvastatin was also well predicted in the article, even if an error was made for blood versus plasma ratio. Rowland et al. (2004) comment that we did not estimate the acyl glucuronidation of diclofenac, which is estimated to account for 10 to 20% of the in vivo clearance. When Kumar et al. (2002) included the CL int for the acyl glucuronidation pathway, the conjugation pathway was predicted to account for 75% of the total clearance. Rather than bringing clarity to how to predict in vivo clearance, the results point toward another problem: how to estimate CL int for glucuronidation. The other comment regarded ibuprofen, where we only measured the enzyme kinetics for the formation of 3-hydroxyibuprofen; this was done simply because the formation of the 2-hydroxy metabolite was too small to be reliably detected. The small fraction cleared via 2-hydroxylation in human liver microsomes would not change the overall picture of under-prediction of in vivo metabolic clearance. Rather than a tool in early discovery, scaling in vivo clearance from in vitro metabolism data may be useful as a retrospective exercise for well characterized drugs with all in vivo pharmacokinetic properties at hand. AstraZeneca Research and Development, Mo ¨lndal, Sweden TOMMY B. ANDERSSON EVA BREDBERG HANS ERICSSON HELENA SJO ¨ BERG References Kumar S, Samuel K, Subramanian R, Braun MP, Stearns RA, Lee SH, Evans DC, and Baillie TA (2002) Exatrapolation of diclofenac clearance from in vitro microsomal metabolism data: role of acyl glucuronidation and sequential oxidative metabolism of the acyl glucuronide. J Phar- macol Exp Ther 303:969 –978. Rowland Yeo K, Howgate EM, Tucker GT, and Rostami-Hodjegan A (2004) Predicting the clearance of 2C9 substrates. Drug Metab Dispos 32:1522. Article, publication date, and citation information can be found at http://dmd.aspetjournals.org. doi:10.1124/dmd.104.002329. 0090-9556/04/3212-1523$20.00 DRUG METABOLISM AND DISPOSITION Vol. 32, No. 12 Copyright © 2004 by The American Society for Pharmacology and Experimental Therapeutics 2329/1185129 DMD 32:1523, 2004 Printed in U.S.A. 1523 by guest on March 5, 2013 dmd.aspetjournals.org Downloaded from