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Liang F, Zhang Y, Xue Q, Yao N. Exploring inter-ethnic and inter-patient variability and optimal dosing of osimertinib: a physiologically based pharmacokinetic modeling approach. Front Pharmacol 2024; 15:1363259. [PMID: 38500771 PMCID: PMC10946252 DOI: 10.3389/fphar.2024.1363259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 02/22/2024] [Indexed: 03/20/2024] Open
Abstract
Purpose: This study aimed to develop and validate a physiologically based pharmacokinetic (PBPK) model for osimertinib (OSI) to predict plasma trough concentration (Ctrough) and pulmonary EGFRm+ (T790M and L858R mutants) inhibition in Caucasian, Japanese, and Chinese populations. The PBPK model was also utilized to investigate inter-ethnic and inter-patient differences in OSI pharmacokinetics (PK) and determine optimal dosing regimens. Methods: Population PBPK models of OSI for healthy and disease populations were developed using physicochemical and biochemical properties of OSI and physiological parameters of different groups. And then the PBPK models were validated using the multiple clinical PK and drug-drug interaction (DDI) study data. Results: The model demonstrated good consistency with the observed data, with most of prediction-to-observation ratios of 0.8-1.25 for AUC, Cmax, and Ctrough. The PBPK model revealed that plasma exposure of OSI was approximately 2-fold higher in patients compared to healthy individuals, and higher exposure observed in Caucasians compared to other ethnic groups. This was primarily attributed to a lower CL/F of OSI in patients and Caucasian. The PBPK model displayed that key factors influencing PK and EGFRm+ inhibition differences included genetic polymorphism of CYP3A4, CYP1A2 expression, plasma free concentration (fup), albumin level, and auto-inhibition/induction on CYP3A4. Inter-patient PK variability was most influenced by CYP3A4 variants, fup, and albumin level. The PBPK simulations indicated that the optimal dosing regimen for patients across the three populations of European, Japanese, and Chinese ancestry was OSI 80 mg once daily (OD) to achieve the desired range of plasma Ctrough (328-677 nmol/L), as well as 80 mg and 160 mg OD for desirable pulmonary EGFRm+ inhibition (>80%). Conclusion: In conclusion, this study's PBPK simulations highlighted potential ethnic and inter-patient variability in OSI PK and EGFRm+ inhibition between Caucasian, Japanese, and Chinese populations, while also providing insights into optimal dosing regimens of OSI.
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Affiliation(s)
| | | | | | - Na Yao
- Bethune International Peace Hospital, Shijiazhuang, China
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Wang Z, Liu W, Li X, Chen H, Qi D, Pan F, Liu H, Yu S, Yi B, Wang G, Liu Y. Physiologically based pharmacokinetic combined JAK2 occupancy modelling to simulate PK and PD of baricitinib with kidney transporter inhibitors and in patients with hepatic/renal impairment. Regul Toxicol Pharmacol 2022; 133:105210. [PMID: 35700864 DOI: 10.1016/j.yrtph.2022.105210] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 04/05/2022] [Accepted: 06/08/2022] [Indexed: 11/19/2022]
Abstract
PURPOSE Our aim is to build a physiologically based pharmacokinetic and JAK2 occupancy model (PBPK-JO) to simultaneously predict pharmacokinetic (PK) and pharmacodynamic (PD) changes of baricitinib (BAR) in healthy humans when co-administrated with kidney transporters OAT3 and MATE2-K inhibitors, and in patients with hepatic and renal impairment. METHODS Probenecid and vandetanib were selected as OAT3 and MATE2-K competitive inhibitors, respectively. The PBPK-JO model was built using physicochemical and biochemical properties of BAR, and then verified by observed clinical PK. Finally, the model was applied to determine optimal dosing regimens in various clinical situations. RESULTS Here, we have successfully simulated PK and JAK2 occupancy profiles in humans by PBPK-JO model. Moreover, this modelling reproduced every observed PK data, and every mean relative deviation (MRD) was below 2. The simulation suggested that PK of BAR had a significant change (2.22-fold increase), however PD only had a slight increase of 1.14-fold. Additionally, the simulation also suggested that vandetanib was almost unlikely to affect the PK and PD of BAR. In simulations of hepatic and renal impairment patients, the predictions suggested that significant changes in the PK and PD of BAR occurred. However, there was a lower fold increase in JAK2 occupancy than in PK in patients relative to healthy individuals. CONCLUSION Administration dose adjustment of BAR when co-administrated with OAT3 inhibitors or in patients with hepatic or renal impairment should combine PK and PD changes of BAR, instead of only considering PK alteration.
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Affiliation(s)
- Zhongjian Wang
- Pharnexcloud Digital Technology Co., Ltd., Chengdu, Sichuan, 610093, China
| | - Wei Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Xueyan Li
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Hongjiao Chen
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Dongying Qi
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Fulu Pan
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Huining Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Shuang Yu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100102, China
| | - Bowen Yi
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, China.
| | - Guopeng Wang
- Zhongcai Health (Beijing) Biological Technology Development Co., Ltd., Beijing, 101500, China.
| | - Yang Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100102, China.
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Luo Z, Liu Y, Han X, Yang W, Wang G, Wang J, Jiang X, Sen M, Li X, Yu G, Shi Y. Mechanism of Paeoniae Radix Alba in the Treatment of Non-alcoholic Fatty Liver Disease Based on Sequential Metabolites Identification Approach, Network Pharmacology, and Binding Affinity Measurement. Front Nutr 2021; 8:677659. [PMID: 34604271 PMCID: PMC8481579 DOI: 10.3389/fnut.2021.677659] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 08/23/2021] [Indexed: 12/13/2022] Open
Abstract
Screening functional food ingredients (FFI) from medicinal and edible plants (MEP) has still remained a great challenge due to the complexity of MEP and its obscure function mechanisms. Herein, an integrated strategy based on sequential metabolites identification approach, network pharmacology, molecular docking, and surface plasmon resonance (SPR) analysis was proposed for quickly identifying the active constituents in MEP. First, the sequential biotransformation process of MEP, including intestinal absorption and metabolism, and hepatic metabolism, was investigated by oral gavage, and intestinal perfusion with venous sampling method. Then the blood samples were analyzed by UPLC-Q Exactive Orbitrap HRMS. Second, the network pharmacology approach was used to explore the potential targets and possible mechanisms of the in vivo metabolites of MEP. Third, molecular docking and SPR approaches were used to verify the specific interactions between protein targets and representative ingredients. The proposed integrated strategy was successfully used to explore the heptoprotective components and the underlying molecular mechanism of Paeoniae Radix Alba (PRA). A total of 44 compounds were identified in blood samples, including 17 porotypes and 27 metabolites. The associated metabolic pathways were oxidation, methylation, sulfation, and glucuronidation. After further screening, 31 bioactive candidates and 377 related targets were obtained. In addition, the bioactive components contained in PRA may have therapeutic potentials for non-alcoholic fatty liver disease (NAFLD). The above results demonstrated the proposed strategy may provide a feasible tool for screening FFI and elaborating the complex function mechanisms of MEP.
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Affiliation(s)
- Zhiqiang Luo
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China.,School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Yang Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Xing Han
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.,State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Wenning Yang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Guopeng Wang
- Zhongcai Health (Beijing) Biological Technology Development Co., Ltd., Beijing, China
| | - Jing Wang
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China
| | - Xiaoquan Jiang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Muli Sen
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Xueyan Li
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Guohua Yu
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Yuanyuan Shi
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China.,Department of Biomedical Engineering, Shenzhen Research Institute, Beijing University of Chinese Medicine, Shenzhen, China
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Yang H, Li X, Li G, Huang H, Yang W, Jiang X, Sen M, Liu J, Liu Y, Pan Y, Wang G. Accurate quantitative determination of affinity and binding kinetics for tight binding inhibition of xanthine oxidase. Biomed Pharmacother 2021; 139:111664. [PMID: 34243606 DOI: 10.1016/j.biopha.2021.111664] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 04/22/2021] [Accepted: 04/23/2021] [Indexed: 11/28/2022] Open
Abstract
The accurate quantitative determination of affinity and binding kinetics (BK) for tight binding inhibition is extraordinary important from both the continuous optimization of compounds, particularly in developing structure-activity relationships (SAR), and the prediction of in vivo target occupancy (TO). Due to the unique properties for tight binding inhibition that the inhibitors are characterized by the ultrahigh-affinity, relatively fast association to the target enzyme combined with extremely slow dissociation of the inhibitor-enzyme binary complex, the classical steady state equilibrium methods are no longer valid. Here, we made several recommendations of how to design the optimal experiments and apply special mathematical calculation approaches to quantitatively evaluate the accurate affinity and BK as the examples of two tight binding inhibitors against the xanthine oxidase (XO), as well as compared the differences in the results calculated from the different data analytical methods and analyzed the influence of these differences on the XO engagement in human. Analysis of the results displayed that the accurate apparent dissociation constant (Ki*,app) was 0.2 ± 0.06 nM for topiroxotstat and was 0.45 ± 0.2 nM for febuxostat; that on-rate (kon) was (4.3 ± 1.1) × 106 M-1s-1 for topiroxotstat and was(133.3 ± 3.5) × 106 M-1s-1 for febuxostat, and off-rate (koff) was (1.0±0.2) × 10-5 s-1 for topiroxotstat and was ≤ 0.16 × 10-5 s-1for febuxostat. Moreover, there were significant differences in the Ki*,app and koff values estimated using the appropriate specialized methods for tight binding inhibition versus classical steady state equilibrium methods, with the substantial differences of 14-fold and 32-fold reduction for topiroxostat, respectively, and of 9.6-fold and ≥ 213-fold reduction for febuxostat, while the kon values remain the moderate differences for the two inhibitors. The obvious greater AUC of XO engagement time courses and longer durations of above 70% engagement by the appropriate specialized methods for tight binding inhibition were observed that the results display the differences of 70.1% and 88%, respectively for topiroxostat and of 38.1% and 35.0%, respectively for febuxostat in human liver cell than by classical steady state equilibrium methods. Again, our studies provide several valuable recommendations of the optimal experiment protocols and appropriate analytical approaches for accurately quantitatively assessing the affinity and BK parameters as well as demonstrate the ability of our recommended methods to generate reliable data for tight binding inhibitors against XO.
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Affiliation(s)
- Haiyang Yang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Xueyan Li
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Gang Li
- Beijing Adamadle Biotech Co., Ltd., Beijing 100102, China
| | - Huating Huang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Wenning Yang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Xiaoquan Jiang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Muli Sen
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China
| | - Jingjing Liu
- National Institutes for Food and Drug Control, Beijing 100050, China
| | - Yang Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 102488, China.
| | - Yanli Pan
- Institute of Information on Traditional Chinese Medicine China Academy of Chinese Medical Sciences, Beijing 100700, China.
| | - Guopeng Wang
- Zhongcai Health (Beijing) Biological Technology Development Co., Ltd., Beijing 101500, China.
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