3.3 Evaluation of drug–drug interaction
Drug efficacy was predicted using the PK–PD model and the estimated extraction ratios in the liver part. The extraction ratio of CPT-11 in the liver part in concomitant administration of SV was set to 0.2% because the CES2 expression would be half. On the other hand, the extraction ratio of CPT-11 in the liver part in concomitant administration of RTV was set to 0.4%, which is the same value as that without concomitant administration, because CYP3A4 expression is extremely low in HepG2, and CYP3A4 inhibition may be no effect on pharmacokinetics. The extraction ratio of SN-38 in the liver part was set to 8.4%. A549 cells density ratios exposed to CPT-11 for 72 h without metabolic inhibitors, with RTV, and with SV were predicted to be 35.5%, 35.5% and 25.6%, respectively, of the control, i.e., no drugs (Fig. 4A). Meanwhile, their experimental values using the MO–MPS were 29.5%, 20.3% and 38.8%, respectively. The cell density ratio with SV is significantly higher than that without metabolic inhibitors. No statistically significant difference was observed between without metabolic inhibitor and with RTV although cell density with RTV was lower than that without metabolic inhibitor (Fig. 4B).
Drug efficacy declined in the concomitant administration of SV because SV suppresses CES2 expression, which metabolizes CPT-11 to SN-38. As expected, drug efficacy did not change in the concomitant administration of RTV, which was used as CYP3A4 inhibitor, because CYP3A4 expression on HepG2 is quite low. However, drug efficacy in concomitant administration of RTV was markedly increased in the experiment. SN-38 metabolism to SN-38G is decreased by the concomitant administration of anti-HIV drugs, suggesting that anti-HIV drugs impact the metabolism by UGT1A1.(Corona et al., (2008)) HepG2 has low levels of CYP3A4 activity but still express UGT1A1.(Westerink and Schoonen, (2007)) The increase in drug efficacy may have been caused by the inhibition of UGT1A1 because the AUC of SN-38 increased by the inhibition of not only CPT-11 metabolism to APC and NPC but also SN-38 metabolism to SN-38G. Our findings involving DDI of inhibitor chemicals were quite similar to the results of previous studies, indicating that the DDI evaluation using PK-PD model and MPS is useful.
Conclusion
Although MPS is useful for pharmacokinetic studies, it has not yet been applied to DDI studies. Here, we proposed a series of DDI evaluation methods using an MPS and a PK-PD model, and demonstrated their usefulness. We established a microfluidics-based MO–MPS and its PK–PD model. From the experimental results using CPT-11, we confirmed that the MO–MPS could be used to evaluate the effect of metabolites on a drug target model. Drug-specific parameters were estimated from the PK–PD model and from the experimental results using the MO–MPS. DDI was evaluated by comparing the calculated drug efficacy of the anti-cancer drug by the PK–PD model with experimental results obtained using metabolism inhibitor. The effect of concomitantly administered drugs on the pharmacokinetic changes occurring in MPS can be more clearly identified by evaluating DDI by the PK–PD model, using parameters inferred from the experimental results. Our proposed method is useful in evaluating not only liver metabolism but also the DDI effects for different organ functions such as absorption and excretion. Furthermore, this method can be applied to the evaluation of organ–organ interaction using multi-organ MPS that reproduces enterohepatic circulation. In this study, DDI was evaluated only in terms of drug efficacy. For a more in-depth understanding of DDI, evaluating the changes in drug concentration and metabolic capacity through mathematical models and experiments is necessary. For this kind of evaluation, the contents of the culture medium and cells in the MO–MPS should be measured using liquid chromatography–mass spectrometry and PCR; we aim to perform this in our future studies. Despite this limitation, our method still proved to be valuable for the study and analysis of DDI.
Acknowledgements
This study was funded by the Program for Grant-in-Aid for Scientific Research (B) 18H01849 and the Japan Agency for Medical Research and Development (AMED).
References
Abaci HE, Shuler ML. (2015). Human-on-a-chip design strategies and principles for physiologically based pharmacokinetics/pharmacodynamics modeling. Integrative Biology (United Kingdom) , 7 , 383–391. doi: 10.1039/c4ib00292j.
Beijnen JH, Schellens JHM. (2004). Drug interactions in oncology.Lancet Oncology , 5 , 489–496. doi: 10.1016/S1470-2045(04)01528-1.
Bhatia SN, Ingber DE. (2014). Microfluidic organs-on-chips. Nature Biotechnology , 32 , 760–772. doi: 10.1038/nbt.2989.
Van Der Bol JM, Loos WJ, De Jong FA, Van Meerten E, Konings IRHM, Lam MH, De Bruijn P, Wiemer EAC, Verweij J, Mathijssen RHJ. (2011). Effect of omeprazole on the pharmacokinetics and toxicities of irinotecan in cancer patients: A prospective cross-over drug-drug interaction study.European Journal of Cancer , 47 , 831–838. doi: 10.1016/j.ejca.2010.11.030.
Chuah YJ, Kuddannaya S, Lee MHA, Zhang Y, Kang Y. (2015). The effects of poly(dimethylsiloxane) surface silanization on the mesenchymal stem cell fate. Biomaterials Science , 3 , 383–390. doi: 10.1039/c4bm00268g.
Corona G, Vaccher E, Sandron S, Sartor I, Tirelli U, Innocenti F, Toffoli G. (2008). Lopinavir-ritonavir dramatically affects the pharmacokinetics of irinotecan in HIV patients with Kaposi’s sarcoma.Clinical Pharmacology and Therapeutics , 83 , 601–606. doi: 10.1038/sj.clpt.6100330.
Dehne EM, Hasenberg T, Marx U. (2017). The ascendance of microphysiological systems to solve the drug testing dilemma.Future Science OA , 3 , FSO185. doi: 10.4155/fsoa-2017-0002.
Diasio RB. (1998). Sorivudine and 5-fluorouracil; A clinically significant drug-drug interaction due to inhibition of dihydropyrimidine dehydrogenase. British Journal of Clinical Pharmacology ,46 , 1–4. doi: 10.1046/j.1365-2125.1998.00050.x.
Eagling VA, Back DJ, Barry MG. (1997). Differential inhibition of cytochrome P450 isoforms by the protease inhibitors, ritonavir, saquinavir and indinavir. British Journal of Clinical Pharmacology , 44 , 190–194. doi: 10.1046/j.1365-2125.1997.00644.x.
Esch EW, Bahinski A, Huh D. (2015). Organs-on-chips at the frontiers of drug discovery. Nature Reviews Drug Discovery , 14 , 248–260. doi: 10.1038/nrd4539.
Fukami T, Takahashi S, Nakagawa N, Maruichi T, Nakajima M, Yokoi T. (2010). In vitro evaluation of inhibitory effects of antidiabetic and antihyperlipidemic drugs on human carboxylesterase activities.Drug Metabolism and Disposition , 38 , 2173–2178. doi: 10.1124/dmd.110.034454.
Huch M, Gehart H, Van Boxtel R, Hamer K, Blokzijl F, Verstegen MMA, Ellis E, Van Wenum M, Fuchs SA, De Ligt J, Van De Wetering M, Sasaki N, Boers SJ, Kemperman H, De Jonge J, Ijzermans JNM, Nieuwenhuis EES, Hoekstra R, Strom S, Vries RRG, Van Der Laan LJW, Cuppen E, Clevers H. (2015). Long-term culture of genome-stable bipotent stem cells from adult human liver. Cell , 160 , 299–312. doi: 10.1016/j.cell.2014.11.050.
Ishida S. (2018). Organs-on-a-chip: Current applications and consideration points for in vitro ADME-Tox studies. Drug Metabolism and Pharmacokinetics , 33 , 49–54. doi: 10.1016/j.dmpk.2018.01.003.
Kimura H, Yamamoto T, Sakai H, Sakai Y, Fujii T. (2008). An integrated microfluidic system for long-term perfusion culture and on-line monitoring of intestinal tissue models. Lab on a Chip , 8 , 741–746. doi: 10.1039/b717091b.
Kurita A, Kaneda N. (1999). High-performance liquid chromatographic method for the simultaneous determination of the camptothecin derivative irinotecan hydrochloride, CPT-11, and its metabolites SN-38 and SN-38 glucuronide in rat plasma with a fully automated on-line solid-phase ext. Journal of Chromatography B: Biomedical Sciences and Applications , 724 , 335–344. doi: 10.1016/S0378-4347(98)00554-4.
Lee DW, Lee SH, Choi N, Sung JH. (2019). Construction of pancreas–muscle–liver microphysiological system (MPS) for reproducing glucose metabolism. Biotechnology and Bioengineering , 116 , 3433–3445. doi: 10.1002/bit.27151.
Lee H, Kim DS, Ha SK, Choi I, Lee JM, Sung JH. (2017). A pumpless multi-organ-on-a-chip (MOC) combined with a pharmacokinetic–pharmacodynamic (PK–PD) model. Biotechnology and Bioengineering , 114 , 432–443. doi: 10.1002/bit.26087.
Levy G, Bomze D, Heinz S, Ramachandran SD, Noerenberg A, Cohen M, Shibolet O, Sklan E, Braspenning J, Nahmias Y. (2015). Long-term culture and expansion of primary human hepatocytes. Nature Biotechnology ,33 , 1264–1271. doi: 10.1038/nbt.3377.
Ma MK, Zamboni WC, Radomski KM, Furman WL, Santana VM, Houghton PJ, Hanna SK, Smith AK, Stewart CF. (2000). Pharmacokinetics of irinotecan and its metabolites SN-38 and APC in children with recurrent solid tumors after protracted low-dose irinotecan. Clinical Cancer Research , 6 , 813–819.
Marx U, Andersson TB, Bahinski A, Beilmann M, Beken S, Cassee FR, Cirit M, Daneshian M, Fitzpatrick S, Frey O, Gaertner C, Giese C, Griffith L, Hartung T, Heringa MB, Hoeng J, Jong WH De, Kojima H, Kuehnl J, Luch A, Sakharov D, Sips AJAM, Steger-hartmann T, Tagle A, Tonevitsky A, Tralau T, Tsyb S, Stolpe A Van De, Vulto P, Wang J, Wiest J, Rodenburg M, Roth A. (2017). Biology-inspired Microphysiological System Approaches to Solve the Prediction Dilemma of Substance Testing. ALTEX ,33 , 272–321. doi: 10.14573/altex.1603161.Biology-inspired.
McDonald JC, Whitesides GM. (2002). Poly(dimethylsiloxane) as a material for fabricating microfluidic devices. Accounts of Chemical Research , 35 , 491–499. doi: 10.1021/ar010110q.
Mijatovic T, De Beeck AO, Van Quaquebeke E, Dewelle J, Darro F, de Launoit Y, Kiss R. (2006). The cardenolide UNBS1450 is able to deactivate nuclear factor κB-mediated cytoprotective effects in human non-small cell lung cancer cells. Molecular Cancer Therapeutics ,5 , 391–399. doi: 10.1158/1535-7163.MCT-05-0367.
Mullangi R, Ahlawat P, Srinivas NR. (2010). Irinotecan and its active metabolite, SN-38: Review of bioanalytical methods and recent update from clinical pharmacology perspectives. Biomedical Chromatography , 24 , 104–123. doi: 10.1002/bmc.1345.
Nakayama H, Kimura H, Fujii T, Sakai Y. (2014). Image-based evaluations of distribution and cytotoxicity of Irinotecan (CPT-11) in a multi-compartment micro-cell coculture device. Journal of Bioscience and Bioengineering , 117 , 756–762. doi: 10.1016/j.jbiosc.2013.11.019.
Prantil-Baun R, Novak R, Das D, Somayaji MR, Przekwas A, Ingber DE. (2018). Physiologically Based Pharmacokinetic and Pharmacodynamic Analysis Enabled by Microfluidically Linked Organs-on-Chips.Annual Review of Pharmacology and Toxicology , 58 , 37–64. doi: 10.1146/annurev-pharmtox-010716-104748.
Shen Y, Shi Z, Yan B. (2019). Carboxylesterases: Pharmacological Inhibition Regulated Expression and Transcriptional Involvement of Nuclear Receptors and other Transcription Factors. Nuclear Receptor Research , 6 . doi: 10.32527/2019/101435.
Sung JH, Kam C, Shuler ML. (2010). A microfluidic device for a pharmacokinetic – pharmacodynamic ( PK – PD ) model on a chip †.Lab on a chip , 10 , 446–455. doi: 10.1039/b917763a.
Takahashi T. (1989). The Atlas of the Human Body. Tokyo: Kodansha Ltd.
Uchida K, Otake K, Tanaka K, Hashimoto K, Saigusa S, Matsushita K, Koike Y, Inoue M, Ueeda M, Okugawa Y, Inoue Y, Mohri Y, Kusunoki M. (2013). Clinical implications of CES2 RNA expression in neuroblastoma.Journal of Pediatric Surgery , 48 , 502–509. doi: 10.1016/j.jpedsurg.2012.10.004.
Westerink WMA, Schoonen WGEJ. (2007). Phase II enzyme levels in HepG2 cells and cryopreserved primary human hepatocytes and their induction in HepG2 cells. Toxicology in Vitro , 21 , 1592–1602. doi: 10.1016/j.tiv.2007.06.017.
Wilkening S, Stahl F, Bader A. (2003). Hepg2 With Regard To Their Biotransformation Properties. Drug Metabolism and Disposition ,31 , 1035–1042.