Physiologically based Pharmacokinetic Model Validated to Enable Predictions Of Multiple Drugs in a Long-acting Drug-combination Nano-Particles (DcNP) : Confirmation with 3 HIV Drugs, Lopinavir, Ritonavir, and Tenofovir in DcNP Products
Copyright © 2024. Published by Elsevier Inc..
Drug-Combination Nanoparticles (DcNP) are a novel drug delivery system designed for synchronized delivery of multiple drugs in a single, long-acting, and targeted dose. Unlike depot formulations, slowly releasing drug at the injection site into the blood, DcNP allows multiple-drug-in-combination to collectively distribute from the injection site into the lymphatic system. Two distinct classes of long-acting injectables products are proposed based on pharmacokinetic mechanisms. Class I involves sustained release at the injection site. Class II involves a drug-carrier complex composed of lopinavir, ritonavir, and tenofovir uptake and retention in the lymphatic system before systemic access as a part of the PBPK model validation. For clinical development, Class II long-acting drug-combination products, we leverage data from 3 nonhuman primate studies consisting of nine PK datasets: Study 1, varying fixed-dose ratios; Study 2, short multiple dosing with kinetic tails; Study 3, long multiple dosing (chronic). PBPK validation criteria were established to validate each scenario for all drugs. The models passed validation in 8 of 9 cases, specifically to predict Study 1 and 2, including PK tails, with ritonavir and tenofovir, fully passing Study 3 as well. PBPK model for lopinavir in Study 3 did not pass the validation due to an observable time-varying and delayed drug accumulation, which likely was due to ritonavir's CYP3A inhibitory effect building up during multiple dosing that triggered a mechanism-based drug-drug interaction (DDI). Subsequently, the final model enables us to account for this DDI scenario.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
Journal of pharmaceutical sciences - (2024) vom: 20. Feb. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Perazzolo, Simone [VerfasserIn] |
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| Links: |
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| Themen: |
HIV |
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| Anmerkungen: |
Date Revised 05.03.2024 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.1016/j.xphs.2024.02.018 |
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| 245 | 1 | 0 | |a Physiologically based Pharmacokinetic Model Validated to Enable Predictions Of Multiple Drugs in a Long-acting Drug-combination Nano-Particles (DcNP) |b Confirmation with 3 HIV Drugs, Lopinavir, Ritonavir, and Tenofovir in DcNP Products |
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| 520 | |a Copyright © 2024. Published by Elsevier Inc. | ||
| 520 | |a Drug-Combination Nanoparticles (DcNP) are a novel drug delivery system designed for synchronized delivery of multiple drugs in a single, long-acting, and targeted dose. Unlike depot formulations, slowly releasing drug at the injection site into the blood, DcNP allows multiple-drug-in-combination to collectively distribute from the injection site into the lymphatic system. Two distinct classes of long-acting injectables products are proposed based on pharmacokinetic mechanisms. Class I involves sustained release at the injection site. Class II involves a drug-carrier complex composed of lopinavir, ritonavir, and tenofovir uptake and retention in the lymphatic system before systemic access as a part of the PBPK model validation. For clinical development, Class II long-acting drug-combination products, we leverage data from 3 nonhuman primate studies consisting of nine PK datasets: Study 1, varying fixed-dose ratios; Study 2, short multiple dosing with kinetic tails; Study 3, long multiple dosing (chronic). PBPK validation criteria were established to validate each scenario for all drugs. The models passed validation in 8 of 9 cases, specifically to predict Study 1 and 2, including PK tails, with ritonavir and tenofovir, fully passing Study 3 as well. PBPK model for lopinavir in Study 3 did not pass the validation due to an observable time-varying and delayed drug accumulation, which likely was due to ritonavir's CYP3A inhibitory effect building up during multiple dosing that triggered a mechanism-based drug-drug interaction (DDI). Subsequently, the final model enables us to account for this DDI scenario | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a HIV | |
| 650 | 4 | |a Long-acting | |
| 650 | 4 | |a Lopinavir | |
| 650 | 4 | |a Mechanism-based inhibition | |
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| 650 | 4 | |a Ritonavir | |
| 650 | 4 | |a Tenofovir | |
| 650 | 4 | |a Validation | |
| 700 | 1 | |a Shen, Danny D |e verfasserin |4 aut | |
| 700 | 1 | |a Scott, Ariel M |e verfasserin |4 aut | |
| 700 | 1 | |a Ho, Rodney J Y |e verfasserin |4 aut | |
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