Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib
Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were de...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Adiwidjaja, Jeffry [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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| Übergeordnetes Werk: |
Enthalten in: European journal of clinical pharmacology - Berlin : Springer, 1968, 78(2022), 4 vom: 20. Jan., Seite 597-611 |
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| Übergeordnetes Werk: |
volume:78 ; year:2022 ; number:4 ; day:20 ; month:01 ; pages:597-611 |
| Links: |
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| DOI / URN: |
10.1007/s00228-021-03266-y |
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| Katalog-ID: |
SPR046498729 |
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| 520 | |a Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies. | ||
| 650 | 4 | |a Imatinib |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Bosutinib |7 (dpeaa)DE-He213 | |
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| 650 | 4 | |a Berberine |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a McLachlan, Andrew J. |0 (orcid)0000-0003-4674-0242 |4 aut | |
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10.1007/s00228-021-03266-y doi (DE-627)SPR046498729 (SPR)s00228-021-03266-y-e DE-627 ger DE-627 rakwb eng Adiwidjaja, Jeffry verfasserin (orcid)0000-0002-6781-2113 aut Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies. Imatinib (dpeaa)DE-He213 Bosutinib (dpeaa)DE-He213 Goldenseal (dpeaa)DE-He213 Berberine (dpeaa)DE-He213 Interactions (dpeaa)DE-He213 Physiologically based pharmacokinetic (dpeaa)DE-He213 Boddy, Alan V. (orcid)0000-0002-8920-9286 aut McLachlan, Andrew J. (orcid)0000-0003-4674-0242 aut Enthalten in European journal of clinical pharmacology Berlin : Springer, 1968 78(2022), 4 vom: 20. Jan., Seite 597-611 (DE-627)253722829 (DE-600)1459058-X 1432-1041 nnns volume:78 year:2022 number:4 day:20 month:01 pages:597-611 https://dx.doi.org/10.1007/s00228-021-03266-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 78 2022 4 20 01 597-611 |
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10.1007/s00228-021-03266-y doi (DE-627)SPR046498729 (SPR)s00228-021-03266-y-e DE-627 ger DE-627 rakwb eng Adiwidjaja, Jeffry verfasserin (orcid)0000-0002-6781-2113 aut Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies. Imatinib (dpeaa)DE-He213 Bosutinib (dpeaa)DE-He213 Goldenseal (dpeaa)DE-He213 Berberine (dpeaa)DE-He213 Interactions (dpeaa)DE-He213 Physiologically based pharmacokinetic (dpeaa)DE-He213 Boddy, Alan V. (orcid)0000-0002-8920-9286 aut McLachlan, Andrew J. (orcid)0000-0003-4674-0242 aut Enthalten in European journal of clinical pharmacology Berlin : Springer, 1968 78(2022), 4 vom: 20. Jan., Seite 597-611 (DE-627)253722829 (DE-600)1459058-X 1432-1041 nnns volume:78 year:2022 number:4 day:20 month:01 pages:597-611 https://dx.doi.org/10.1007/s00228-021-03266-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 78 2022 4 20 01 597-611 |
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10.1007/s00228-021-03266-y doi (DE-627)SPR046498729 (SPR)s00228-021-03266-y-e DE-627 ger DE-627 rakwb eng Adiwidjaja, Jeffry verfasserin (orcid)0000-0002-6781-2113 aut Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies. Imatinib (dpeaa)DE-He213 Bosutinib (dpeaa)DE-He213 Goldenseal (dpeaa)DE-He213 Berberine (dpeaa)DE-He213 Interactions (dpeaa)DE-He213 Physiologically based pharmacokinetic (dpeaa)DE-He213 Boddy, Alan V. (orcid)0000-0002-8920-9286 aut McLachlan, Andrew J. (orcid)0000-0003-4674-0242 aut Enthalten in European journal of clinical pharmacology Berlin : Springer, 1968 78(2022), 4 vom: 20. Jan., Seite 597-611 (DE-627)253722829 (DE-600)1459058-X 1432-1041 nnns volume:78 year:2022 number:4 day:20 month:01 pages:597-611 https://dx.doi.org/10.1007/s00228-021-03266-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 78 2022 4 20 01 597-611 |
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10.1007/s00228-021-03266-y doi (DE-627)SPR046498729 (SPR)s00228-021-03266-y-e DE-627 ger DE-627 rakwb eng Adiwidjaja, Jeffry verfasserin (orcid)0000-0002-6781-2113 aut Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies. Imatinib (dpeaa)DE-He213 Bosutinib (dpeaa)DE-He213 Goldenseal (dpeaa)DE-He213 Berberine (dpeaa)DE-He213 Interactions (dpeaa)DE-He213 Physiologically based pharmacokinetic (dpeaa)DE-He213 Boddy, Alan V. (orcid)0000-0002-8920-9286 aut McLachlan, Andrew J. (orcid)0000-0003-4674-0242 aut Enthalten in European journal of clinical pharmacology Berlin : Springer, 1968 78(2022), 4 vom: 20. Jan., Seite 597-611 (DE-627)253722829 (DE-600)1459058-X 1432-1041 nnns volume:78 year:2022 number:4 day:20 month:01 pages:597-611 https://dx.doi.org/10.1007/s00228-021-03266-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 78 2022 4 20 01 597-611 |
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10.1007/s00228-021-03266-y doi (DE-627)SPR046498729 (SPR)s00228-021-03266-y-e DE-627 ger DE-627 rakwb eng Adiwidjaja, Jeffry verfasserin (orcid)0000-0002-6781-2113 aut Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies. Imatinib (dpeaa)DE-He213 Bosutinib (dpeaa)DE-He213 Goldenseal (dpeaa)DE-He213 Berberine (dpeaa)DE-He213 Interactions (dpeaa)DE-He213 Physiologically based pharmacokinetic (dpeaa)DE-He213 Boddy, Alan V. (orcid)0000-0002-8920-9286 aut McLachlan, Andrew J. (orcid)0000-0003-4674-0242 aut Enthalten in European journal of clinical pharmacology Berlin : Springer, 1968 78(2022), 4 vom: 20. Jan., Seite 597-611 (DE-627)253722829 (DE-600)1459058-X 1432-1041 nnns volume:78 year:2022 number:4 day:20 month:01 pages:597-611 https://dx.doi.org/10.1007/s00228-021-03266-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 78 2022 4 20 01 597-611 |
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Enthalten in European journal of clinical pharmacology 78(2022), 4 vom: 20. Jan., Seite 597-611 volume:78 year:2022 number:4 day:20 month:01 pages:597-611 |
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Adiwidjaja, Jeffry @@aut@@ Boddy, Alan V. @@aut@@ McLachlan, Andrew J. @@aut@@ |
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Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. 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|
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Adiwidjaja, Jeffry |
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Adiwidjaja, Jeffry misc Imatinib misc Bosutinib misc Goldenseal misc Berberine misc Interactions misc Physiologically based pharmacokinetic Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib |
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Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib Imatinib (dpeaa)DE-He213 Bosutinib (dpeaa)DE-He213 Goldenseal (dpeaa)DE-He213 Berberine (dpeaa)DE-He213 Interactions (dpeaa)DE-He213 Physiologically based pharmacokinetic (dpeaa)DE-He213 |
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misc Imatinib misc Bosutinib misc Goldenseal misc Berberine misc Interactions misc Physiologically based pharmacokinetic |
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misc Imatinib misc Bosutinib misc Goldenseal misc Berberine misc Interactions misc Physiologically based pharmacokinetic |
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Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib |
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Adiwidjaja, Jeffry Boddy, Alan V. McLachlan, Andrew J. |
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physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib |
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Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib |
| abstract |
Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
| abstractGer |
Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
| abstract_unstemmed |
Purpose This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. Methods PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. Results The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase ($ 5^{th} $ to $ 95^{th} $ percentiles of prediction of 1.4–3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, $ 5^{th} $ to $ 95^{th} $ percentile: 1.1–1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0–1.2). Conclusion PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib |
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Boddy, Alan V. McLachlan, Andrew J. |
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10.1007/s00228-021-03266-y |
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| score |
7.400692 |