An In Silico Transwell Device for the Study of Drug Transport and Drug–Drug Interactions
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Validate and exemplify a discrete, componentized, in silico, transwell device (ISTD) capable of mimicking the in vitro passive transport properties of compounds through cell monolayers. Verify its use for studying drug–drug interactions.
We used the synthetic modeling method. Specialized software components represented spatial and functional features including cell components, semi-porous tight junctions, and metabolizing enzymes. Mobile components represented drugs. Experiments were conducted and analyzed as done in vitro.
Verification experiments provided data analogous to those in the literature. ISTD parameters were tuned to simulate and match in vitro urea transport data; the objects representing tight junction (effective radius of 6.66 Å) occupied 0.066% of the surface area. That ISTD was then tuned to simulate pH-dependent, in vitro alfentanil transport properties. The resulting ISTD predicted the passive transport properties of 14 additional compounds, individually and all together in one in silico experiment. The function of a two-site enzymatic component was cross-validated with a kinetic model and then experimentally validated against in vitro benzyloxyresorufin metabolism data. Those components were used to exemplify drug–drug interaction studies.
The ISTD is an example of a new class of simulation models capable of realistically representing complex drug transport and drug–drug interaction phenomena.
Key wordsagent-based modeling discrete event drug transport drug–drug interaction emergent properties simulation
a P450 enzyme
in silico transwell device
This research was funded in part by grant R21CDH00101 from the CDH Research Foundation (of which CAH is a trustee). We thank Professors John Verboncoeur and George Sensabaugh for encouragement. We thank the members of Biosystems Group for helpful discussions, with special thanks going Teddy Lam, Sean Kim, Mark Grant, and Li Yan for commentary on the manuscript, to Sunwoo Park for technical support, and Glen Ropella for his support and keen technical and theoretical insights.
- 3.G. E. Ropella, C. A. Hunt, and D. A. Nag. Using heuristic models to bridge the gap between analytic and experimental models in biology. In L. Yilmaz (ed), Agent-Directed Simulation Symposium, Vol. Simulation Series 37(2) (ADS’05). SCS Press, San Diego, CA, 2005, pp. 182–190.Google Scholar
- 4.G. E. P. Ropella, C. A. Hunt, and S. Sheikh-Bahaei. Methodological considerations of heuristic modeling of biological systems. 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Orlando, FL, 2005.Google Scholar
- 6.S. Sheikh-Bahaei and C. A. Hunt. Prediction of in vitro hepatic biliary excretion using stochastic agent-based modeling and fuzzy clustering. In: L. F. Perrone et al. (eds.), Proc. of the 37th Conference on Winter Simulation, 1617–24 (2006).Google Scholar
- 9.R. Hine. Membrane, The Facts on File Dictionary of Biology, Checkmark, New York, 1999, pp. 198.Google Scholar
- 10.P. Ball. Introduction to discrete event simulation, 2nd DYCOMANS workshop on "Management and Control: Tools in Action,” Algarve, Portugal, 1996, pp. 367–76.Google Scholar
- 11.T. H. Cormen, C. E. Leiserson, and R. L. Rivest. Introduction to algorithms, McGraw-Hill, New York, 1990.Google Scholar
- 17.M. Shou, Y. Lin, P. Lu, C. Tang, Q. Mei, D. Cui, W. Tang, J. S. Ngui, C. C. Lin, R. Singh, B. K. Wong, J. A. Yergey, J. H. Lin, P. G. Pearson, T. A. Baillie, A. D. Rodrigues, and T. H. Rushmore. Enzyme kinetics of cytochrome P450-mediated reactions. Current Drug Metabolism 2:17–36 (2001).PubMedCrossRefGoogle Scholar
- 18.K. R. Korzekwa, N. Krishnamachary, M. Shou, A. Ogai, R. A. Parise, A. E. Rettie, F. J. Gonzalez, and T. S. Tracy. Evaluation of atypical cytochrome P450 kinetics with two-substrate models: evidence that multiple substrates can simultaneously bind to cytochrome P450 active sites. Biochemistry 37:4137–4147 (1998).PubMedCrossRefGoogle Scholar
- 26.B. Faller. Enhancing knowledge through combination of in-silico and in-vitro ADME profiling assays, 1st annual phys. chem. symposium: early ADME and medical chemistry, Obernai, France, (2004). http://www.acdlabs.com/download/publ/2004/eum04/adme.pdf/. Cited 3/27/07.
- 31.B. P. Zeigler, H. Praehofer, and T. G. Kim. Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems, Academic, San Diego, 2000.Google Scholar