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Tseng E, Eng H, Lin J, Cerny MA, Tess DA, Goosen TC, Obach RS. Static and Dynamic Projections of Drug-Drug Interactions Caused by Cytochrome P450 3A Time-Dependent Inhibitors Measured in Human Liver Microsomes and Hepatocytes. Drug Metab Dispos 2021; 49:947-960. [PMID: 34326140 DOI: 10.1124/dmd.121.000497] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 07/01/2021] [Indexed: 11/22/2022] Open
Abstract
Cytochrome P450 3A (CYP3A) is a frequent target for time-dependent inhibition (TDI) that can give rise to drug-drug interactions (DDI). Yet many drugs that exhibit in vitro TDI for CYP3A, do not result in DDI. Twenty-three drugs with published clinical DDI were evaluated for CYP3A TDI in human liver microsomes (HLM) and hepatocytes (HHEP), and these data were utilized in static and dynamic models for projecting DDI caused by inactivation of CYP3A in both liver and intestine. TDI parameters measured in HHEP, particularly kinact, were generally lower than those measured in HLM. In static models, the use of average unbound organ exit concentrations offered the most accurate projections of DDI with geometric mean fold errors of 2.2 and 1.7 for HLM and HHEP, respectively. Use of maximum organ entry concentrations yielded marked overestimates of DDI. When evaluated in a binary fashion (i.e. projection of DDI of 1.25-fold or greater), data from HLM offered the greatest sensitivity (100%) and specificity (42%) and yielded no missed DDI when average unbound organ exit concentrations were used. In dynamic physiologically-based pharmacokinetic modeling, accurate projections of DDI were obtained with geometric mean fold errors of 1.7 and 1.6 for HLM and HHEP, respectively. Sensitivity and specificity were 100% and 67% when using TDI data generated in HLM and Simcyp modeling. Overall, DDI caused by CYP3A-mediated TDI can be reliably projected using dynamic or static models. For static models, average organ unbound exit concentrations must be used as input values otherwise DDI will be markedly overestimated. Significance Statement CYP3A time-dependent inhibitors are important in design and development of new drugs. The prevalence of CYP3A TDI is high among newly synthesized drug candidates and understanding the potential need for running clinical DDI studies is essential during drug development. Ability to reliably predict DDI caused by CYP3A TDI has been difficult to achieve. We report a thorough evaluation of CYP3A TDI and demonstrate that DDI can be predicted when using appropriate models and input parameters generated in HLM or HHEP.
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Affiliation(s)
- Elaine Tseng
- Pharmacokinetics, Dynamics, and Metabolism, Pfizer Global Research and Development, United States
| | - Heather Eng
- Pharmacokinetics, Dynamics, and Metabolism, Pfizer Global Research and Development, United States
| | | | | | | | - Theunis C Goosen
- Pharmacokinetics, Dynamics & Metabolism, Pfizer, Inc, United States
| | - R Scott Obach
- Groton Laboratories, Pfizer Global Research and Development, United States
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Eng H, Tseng E, Cerny MA, Goosen TC, Obach RS. Cytochrome P450 3A Time-Dependent Inhibition Assays Are Too Sensitive for Identification of Drugs Causing Clinically Significant Drug-Drug Interactions: A Comparison of Human Liver Microsomes and Hepatocytes and Definition of Boundaries for Inactivation Rate Constants. Drug Metab Dispos 2021; 49:442-450. [PMID: 33811106 DOI: 10.1124/dmd.121.000356] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Accepted: 03/18/2021] [Indexed: 02/06/2023] Open
Abstract
Time-dependent inhibition (TDI) of CYP3A is an important mechanism underlying numerous drug-drug interactions (DDIs), and assays to measure this are done to support early drug research efforts. However, measuring TDI of CYP3A in human liver microsomes (HLMs) frequently yields overestimations of clinical DDIs and thus can lead to the erroneous elimination of many viable drug candidates from further development. In this investigation, 50 drugs were evaluated for TDI in HLMs and suspended human hepatocytes (HHEPs) to define appropriate boundary lines for the TDI parameter rate constant for inhibition (kobs) at a concentration of 30 µM. In HLMs, a kobs value of 0.002 minute-1 was statistically distinguishable from control; however, many drugs show kobs greater than this but do not cause DDI. A boundary line defined by the drug with the lowest kobs that causes a DDI (diltiazem) was established at 0.01 minute-1 Even with this boundary, of the 33 drugs above this value, only 61% cause a DDI (true positive rate). A corresponding analysis was done using HHEPs; kobs of 0.0015 minute-1 was statistically distinguishable from control, and the boundary was established at 0.006 minute-1 Values of kobs in HHEPs were almost always lower than those in HLMs. These findings offer a practical guide to the use of TDI data for CYP3A in early drug-discovery research. SIGNIFICANCE STATEMENT: Time-dependent inhibition of CYP3A is responsible for many drug interactions. In vitro assays are employed in early drug research to identify and remove CYP3A time-dependent inhibitors from further consideration. This analysis demonstrates suitable boundaries for inactivation rates to better delineate drug candidates for their potential to cause clinically significant drug interactions.
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Affiliation(s)
- Heather Eng
- Medicine Design, Pfizer Inc., Groton, Connecticut
| | - Elaine Tseng
- Medicine Design, Pfizer Inc., Groton, Connecticut
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Zhou H. Population-Based Assessments of Clinical Drug-Drug Interactions: Qualitative Indices or Quantitative Measures? J Clin Pharmacol 2013; 46:1268-89. [PMID: 17050792 DOI: 10.1177/0091270006294278] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Population-based assessments of drug-drug interactions have become more common since the introduction and acceptance of the population pharmacokinetic approach. Unlike traditional methods, population-based studies provide clinically relevant results that can be applied directly to a target patient population. Furthermore, population-based studies do not demand the traditional requirements of intensive pharmacokinetic sampling, rigorous inpatient stays, or stringent assessment schedules. As such, the population-based approach can effectively be used to confirm known drug-drug interactions and further characterize anticipated interactions. A prospectively designed analysis can also reveal drug-drug interactions that might otherwise have gone undetected with traditional methods. Ultimately, these results could help to alleviate clinicians' concerns about using widely marketed drugs in combination therapies and also reduce patients' risk of experiencing unacceptable side effects. This article intends to provide a balanced overview of the population-based approach and its merits, drawbacks, and potential utility in the assessment of drug-drug interactions during clinical drug development.
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Affiliation(s)
- Honghui Zhou
- Pharmacokinetics, Modeling & Simulation, Clinical Pharmacology & Experimental Medicine, Centocor Research & Development, Malvern, PA 19087, USA
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Natsui K, Mizuno Y, Tani N, Yabuki M, Komuro S. Identification of CYP3A4 as the primary cytochrome P450 responsible for the metabolism of tandospirone by human liver microsomes. Eur J Drug Metab Pharmacokinet 2007; 32:131-7. [PMID: 18062405 DOI: 10.1007/bf03190475] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
The present study was carried out to characterize the human P450 isoforms involved in the metabolism of tandospirone, an anxiolytic agent known for its superior efficacy and safety. Among 11 yeast-expressed recombinant P450 isoforms tested, CYP2D6 and CYP3A4 exhibited the highest tandospirone metabolic activity. Although there was no qualitative difference between the two isoforms, a quantitative difference in metabolite profiling was found i.e., M4 (hydroxylation of the pyrimidine ring) was the major metabolite formed with CYP2D6 while M2 (hydroxylation of the norbornan ring) and 1-PP (oxidative cleavage of the butyl chain) predominated with CYP3A4. The metabolite profile on incubation with CYP3A4 was qualitatively and quantitatively similar to that obtained with human liver microsomes. In vitro intrinsic clearance (CLint) values derived from kinetic analysis using both P450 isoforms were similar (2.2 and 1.6 ml/min/nmol P450), but the hepatic content of CYP3A4 was found to be more abundant than that of CYP2D6. The in vitro metabolism of tandospirone by human liver microsomes was markedly inhibited by ketoconazole (a CYP3A4 inhibitor) but not by quinidine (a CYP2D6 inhibitor). These results indicate that the metabolism of tandospirone by human liver microsomes primarily involves CYP3A4, and to a lesser extent CYP2D6.
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Affiliation(s)
- Kiyohi Natsui
- Pharmacokinetics Research Laboratories, Dainippon Sumitomo Pharma Co. Ltd, 1-98 Kasugade-naka 3-chome, Konohana-ku, Osaka, 554-0022, Japan
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Ito K, Chiba K, Horikawa M, Ishigami M, Mizuno N, Aoki J, Gotoh Y, Iwatsubo T, Kanamitsu SI, Kato M, Kawahara I, Niinuma K, Nishino A, Sato N, Tsukamoto Y, Ueda K, Itoh T, Sugiyama Y. Which concentration of the inhibitor should be used to predict in vivo drug interactions from in vitro data? AAPS PHARMSCI 2002; 4:E25. [PMID: 12645997 PMCID: PMC2751314 DOI: 10.1208/ps040425] [Citation(s) in RCA: 55] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
When the metabolism of a drug is competitively or noncompetitively inhibited by another drug, the degree of in vivo interaction can be evaluated from the [I]u/Ki ratio, where [I]u is the unbound concentration around the enzyme and Ki is the inhibition constant of the inhibitor. In the present study, we evaluated the metabolic inhibition potential of drugs known to be inhibitors or substrates of cytochrome P450 by estimating their [I]u/Ki ratio using literature data. The maximum concentration of the inhibitor in the circulating blood ([I]max), its maximum unbound concentration in the circulating blood ([I]max,u), and its maximum unbound concentration at the inlet to the liver ([I]in,max,u) were used as [I]u, and the results were compared with each other. In order to calculate the [I]u/Ki ratios, the pharmacokinetic parameters of each drug were obtained from the literature, together with their reported Ki values determined in in vitro studies using human liver microsomes. For most of the drugs with a calculated [I]in,max,u/Ki ratio less than 0.25, which applied to about half of the drugs investigated, no in vivo interactions had been reported or "no interaction" was reported in clinical studies. In contrast, the [I]max,u/Ki and [I]max/Ki ratio was calculated to be less than 0.25 for about 90% and 65% of the drugs, respectively, and more than a 1.25-fold increase was reported in the area under the concentration-time curve of the co-administered drug for about 30% of such drugs. These findings indicate that the possibility of underestimation of in vivo interactions (possibility of false-negative prediction) is greater when [I]max,u or [I]max values are used compared with using [I]in,max,u values.
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Affiliation(s)
- Kiyomi Ito
- School of Pharmaceutical Sciences, Kitasato University, 108-8641 Tokyo
| | - Koji Chiba
- Pharmacia, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Masato Horikawa
- Nissan Chemical Industries, Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Michi Ishigami
- Sankyo Co, Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Naomi Mizuno
- Mitsubishi-Tokyo Pharmaceuticals, Inc, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Jun Aoki
- Mitsui Pharmaceuticals Inc, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Yasumasa Gotoh
- Kissei Pharmaceutical Co, Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Takafumi Iwatsubo
- Yamanouchi Pharmaceutical Co, Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Shin-ichi Kanamitsu
- Otsuka Pharmaceutical Factory, Inc, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Motohiro Kato
- Chugai Pharmaceutical Co, Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Iichiro Kawahara
- Bayer Yakuhin Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Kayoko Niinuma
- Daiichi Pharmaceutical Co, Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Akiko Nishino
- Nippon Boehringer Ingelheim Co, Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Norihito Sato
- Shionogi & Co, Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Yuko Tsukamoto
- Nippon Roche KK, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Kaoru Ueda
- Teikoku Hormone Mfg Co, Ltd, The University of Tokyo, 113-0033 Tokyo, Japan
| | - Tomoo Itoh
- School of Pharmaceutical Sciences, Kitasato University, 108-8641 Tokyo
| | - Yuichi Sugiyama
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, 113-0033 Tokyo, Japan
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