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Sun M, Manson ML, Guo T, de Lange ECM. CNS Viral Infections-What to Consider for Improving Drug Treatment: A Plea for Using Mathematical Modeling Approaches. CNS Drugs 2024; 38:349-373. [PMID: 38580795 PMCID: PMC11026214 DOI: 10.1007/s40263-024-01082-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/10/2024] [Indexed: 04/07/2024]
Abstract
Neurotropic viruses may cause meningitis, myelitis, encephalitis, or meningoencephalitis. These inflammatory conditions of the central nervous system (CNS) may have serious and devastating consequences if not treated adequately. In this review, we first summarize how neurotropic viruses can enter the CNS by (1) crossing the blood-brain barrier or blood-cerebrospinal fluid barrier; (2) invading the nose via the olfactory route; or (3) invading the peripheral nervous system. Neurotropic viruses may then enter the intracellular space of brain cells via endocytosis and/or membrane fusion. Antiviral drugs are currently used for different viral CNS infections, even though their use and dosing regimens within the CNS, with the exception of acyclovir, are minimally supported by clinical evidence. We therefore provide considerations to optimize drug treatment(s) for these neurotropic viruses. Antiviral drugs should cross the blood-brain barrier/blood cerebrospinal fluid barrier and pass the brain cellular membrane to inhibit these viruses inside the brain cells. Some antiviral drugs may also require intracellular conversion into their active metabolite(s). This illustrates the need to better understand these mechanisms because these processes dictate drug exposure within the CNS that ultimately determine the success of antiviral drugs for CNS infections. Finally, we discuss mathematical model-based approaches for optimizing antiviral treatments. Thereby emphasizing the potential of CNS physiologically based pharmacokinetic models because direct measurement of brain intracellular exposure in living humans faces ethical restrictions. Existing physiologically based pharmacokinetic models combined with in vitro pharmacokinetic/pharmacodynamic information can be used to predict drug exposure and evaluate efficacy of antiviral drugs within the CNS, to ultimately optimize the treatments of CNS viral infections.
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Affiliation(s)
- Ming Sun
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Martijn L Manson
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Tingjie Guo
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Elizabeth C M de Lange
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.
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Mehta P, Soliman A, Rodriguez-Vera L, Schmidt S, Muniz P, Rodriguez M, Forcadell M, Gonzalez-Perez E, Vozmediano V. Interspecies Brain PBPK Modeling Platform to Predict Passive Transport through the Blood-Brain Barrier and Assess Target Site Disposition. Pharmaceutics 2024; 16:226. [PMID: 38399280 PMCID: PMC10892872 DOI: 10.3390/pharmaceutics16020226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 02/25/2024] Open
Abstract
The high failure rate of central nervous system (CNS) drugs is partly associated with an insufficient understanding of target site exposure. Blood-brain barrier (BBB) permeability evaluation tools are needed to explore drugs' ability to access the CNS. An outstanding aspect of physiologically based pharmacokinetic (PBPK) models is the integration of knowledge on drug-specific and system-specific characteristics, allowing the identification of the relevant factors involved in target site distribution. We aimed to qualify a PBPK platform model to be used as a tool to predict CNS concentrations when significant transporter activity is absent and human data are sparse or unavailable. Data from the literature on the plasma and CNS of rats and humans regarding acetaminophen, oxycodone, lacosamide, ibuprofen, and levetiracetam were collected. Human BBB permeability values were extrapolated from rats using inter-species differences in BBB surface area. The percentage of predicted AUC and Cmax within the 1.25-fold criterion was 85% and 100% for rats and humans, respectively, with an overall GMFE of <1.25 in all cases. This work demonstrated the successful application of the PBPK platform for predicting human CNS concentrations of drugs passively crossing the BBB. Future applications include the selection of promising CNS drug candidates and the evaluation of new posologies for existing drugs.
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Affiliation(s)
- Parsshava Mehta
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (P.M.); (A.S.); (S.S.)
| | - Amira Soliman
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (P.M.); (A.S.); (S.S.)
- Department of Pharmacy Practice, Faculty of Pharmacy, Helwan University, Helwan 11795, Egypt
| | - Leyanis Rodriguez-Vera
- Model Informed Development, CTI Laboratories, Covington, KY 41011, USA; (L.R.-V.); (P.M.); (M.R.)
| | - Stephan Schmidt
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (P.M.); (A.S.); (S.S.)
| | - Paula Muniz
- Model Informed Development, CTI Laboratories, Covington, KY 41011, USA; (L.R.-V.); (P.M.); (M.R.)
| | - Monica Rodriguez
- Model Informed Development, CTI Laboratories, Covington, KY 41011, USA; (L.R.-V.); (P.M.); (M.R.)
| | - Marta Forcadell
- Neuraxpharm Pharmaceuticals SL, Clinical Research and Evidence-Generation Science, 08970 Barcelona, Spain; (M.F.); (E.G.-P.)
| | - Emili Gonzalez-Perez
- Neuraxpharm Pharmaceuticals SL, Clinical Research and Evidence-Generation Science, 08970 Barcelona, Spain; (M.F.); (E.G.-P.)
| | - Valvanera Vozmediano
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (P.M.); (A.S.); (S.S.)
- Model Informed Development, CTI Laboratories, Covington, KY 41011, USA; (L.R.-V.); (P.M.); (M.R.)
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Deepika D, Kumar V. The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3473. [PMID: 36834167 PMCID: PMC9966583 DOI: 10.3390/ijerph20043473] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/10/2023] [Accepted: 02/14/2023] [Indexed: 06/18/2023]
Abstract
Physiologically Based Pharmacokinetic (PBPK) models are mechanistic tools generally employed in the pharmaceutical industry and environmental health risk assessment. These models are recognized by regulatory authorities for predicting organ concentration-time profiles, pharmacokinetics and daily intake dose of xenobiotics. The extension of PBPK models to capture sensitive populations such as pediatric, geriatric, pregnant females, fetus, etc., and diseased populations such as those with renal impairment, liver cirrhosis, etc., is a must. However, the current modelling practices and existing models are not mature enough to confidently predict the risk in these populations. A multidisciplinary collaboration between clinicians, experimental and modeler scientist is vital to improve the physiology and calculation of biochemical parameters for integrating knowledge and refining existing PBPK models. Specific PBPK covering compartments such as cerebrospinal fluid and the hippocampus are required to gain mechanistic understanding about xenobiotic disposition in these sub-parts. The PBPK model assists in building quantitative adverse outcome pathways (qAOPs) for several endpoints such as developmental neurotoxicity (DNT), hepatotoxicity and cardiotoxicity. Machine learning algorithms can predict physicochemical parameters required to develop in silico models where experimental data are unavailable. Integrating machine learning with PBPK carries the potential to revolutionize the field of drug discovery and development and environmental risk. Overall, this review tried to summarize the recent developments in the in-silico models, building of qAOPs and use of machine learning for improving existing models, along with a regulatory perspective. This review can act as a guide for toxicologists who wish to build their careers in kinetic modeling.
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Affiliation(s)
- Deepika Deepika
- Environmental Engineering Laboratory, Departament d’Enginyeria Quimica, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Catalonia, Spain
- Pere Virgili Health Research Institute (IISPV), Hospital Universitari Sant Joan de Reus, Universitat Rovira i Virgili, 43204 Reus, Catalonia, Spain
| | - Vikas Kumar
- Environmental Engineering Laboratory, Departament d’Enginyeria Quimica, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Catalonia, Spain
- Pere Virgili Health Research Institute (IISPV), Hospital Universitari Sant Joan de Reus, Universitat Rovira i Virgili, 43204 Reus, Catalonia, Spain
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Heitman AM, Bies RR, Schwartz SL. A Physiologically-Based Pharmacokinetic Model of the Brain Considering Regional Lipid Variance. J Pharmacol Exp Ther 2022; 383:217-226. [PMID: 36167416 DOI: 10.1124/jpet.122.001256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/08/2022] [Accepted: 08/25/2022] [Indexed: 01/07/2023] Open
Abstract
Modeling and simulation of the central nervous system provides a tool for understanding and predicting the distribution of small molecules throughout the brain tissue and cerebral spinal fluid (CSF), and these efforts often rely on empirical data to make predictions of distributions to move toward a better mechanistic understanding. A physiologically based pharmacokinetic model presented here incorporates multiple means of drug distribution to assemble a model for understanding potential factors that may determine the distribution of drugs across various regions of the brain, including both intra- and extracellular regions. Two classes of parameters are presented. The first concerns regional gross anatomic variability of the brain; the second concerns estimation of unbound fractions of drugs using know membrane phospholipid heterogeneity derived from regional lipid content. The model was then tested by comparing its outcomes to data from published human pharmacokinetic studies of acetaminophen, morphine, and phenytoin. The alignment of model predictions in the plasma, CSF, and tissue concentrations with the published data from studies of those three drugs suggests that the model can be a template for identifying drug localization in the brain. Clearly, knowledge of differentiated drug distribution in the brain is a requisite step in postulating pharmacodynamic and certain disease mechanisms. SIGNIFICANCE STATEMENT: This study concerns the application of heterogenous lipid distribution in brain tissue to predict regional variations in drug distribution in the brain via a mathematical model, thus expanding upon the current understanding of mechanisms of drug distribution in the central nervous system.
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Affiliation(s)
- Andrew McPherson Heitman
- Department of Pharmacology and Physiology, Georgetown University Medical Center, Washington, DC (A.M.H., S.L.S.) and Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, New York (R.B.)
| | - Robert R Bies
- Department of Pharmacology and Physiology, Georgetown University Medical Center, Washington, DC (A.M.H., S.L.S.) and Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, New York (R.B.)
| | - Sorell L Schwartz
- Department of Pharmacology and Physiology, Georgetown University Medical Center, Washington, DC (A.M.H., S.L.S.) and Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, New York (R.B.)
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5
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Revisiting Cerebrospinal Fluid Flow Direction and Rate in Physiologically Based Pharmacokinetic Model. Pharmaceutics 2022; 14:pharmaceutics14091764. [PMID: 36145511 PMCID: PMC9504371 DOI: 10.3390/pharmaceutics14091764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/17/2022] [Accepted: 08/21/2022] [Indexed: 11/28/2022] Open
Abstract
The bidirectional pulsatile movement of cerebrospinal fluid (CSF), instead of the traditionally believed unidirectional and constant CSF circulation, has been demonstrated. In the present study, the structure and parameters of the CSF compartments were revisited in our comprehensive and validated central nervous system (CNS)-specific, physiologically based pharmacokinetic (PBPK) model of healthy rats (LeiCNS-PK3.0). The bidirectional and site-dependent CSF movement was incorporated into LeiCNS-PK3.0 to create the new LeiCNS-PK“3.1” model. The physiological CSF movement rates in healthy rats that are unavailable from the literature were estimated by fitting the PK data of sucrose, a CSF flow marker, after intra-CSF administration. The capability of LeiCNS-PK3.1 to describe the PK profiles of other molecules was compared with that of the original LeiCNS-PK3.0 model. LeiCNS-PK3.1 demonstrated superior description of the CSF PK profiles of a range of small molecules after intra-CSF administration over LeiCNS-PK3.0. LeiCNS-PK3.1 also retained the same level of predictability of CSF PK profiles in cisterna magna after intravenous administration. These results support the theory of bidirectional and site-dependent CSF movement across the entire CSF space over unidirectional and constant CSF circulation in healthy rats, pointing out the need to revisit the structures and parameters of CSF compartments in CNS-PBPK models.
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Murata Y, Neuhoff S, Rostami-Hodjegan A, Takita H, Al-Majdoub ZM, Ogungbenro K. In Vitro to In Vivo Extrapolation Linked to Physiologically Based Pharmacokinetic Models for Assessing the Brain Drug Disposition. AAPS J 2022; 24:28. [PMID: 35028763 PMCID: PMC8817058 DOI: 10.1208/s12248-021-00675-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 12/09/2021] [Indexed: 11/30/2022] Open
Abstract
Drug development for the central nervous system (CNS) is a complex endeavour with low success rates, as the structural complexity of the brain and specifically the blood-brain barrier (BBB) poses tremendous challenges. Several in vitro brain systems have been evaluated, but the ultimate use of these data in terms of translation to human brain concentration profiles remains to be fully developed. Thus, linking up in vitro-to-in vivo extrapolation (IVIVE) strategies to physiologically based pharmacokinetic (PBPK) models of brain is a useful effort that allows better prediction of drug concentrations in CNS components. Such models may overcome some known aspects of inter-species differences in CNS drug disposition. Required physiological (i.e. systems) parameters in the model are derived from quantitative values in each organ. However, due to the inability to directly measure brain concentrations in humans, compound-specific (drug) parameters are often obtained from in silico or in vitro studies. Such data are translated through IVIVE which could be also applied to preclinical in vivo observations. In such exercises, the limitations of the assays and inter-species differences should be adequately understood in order to verify these predictions with the observed concentration data. This report summarizes the state of IVIVE-PBPK-linked models and discusses shortcomings and areas of further research for better prediction of CNS drug disposition. Graphical abstract ![]()
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Affiliation(s)
- Yukiko Murata
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK.,Sohyaku.Innovative Research Division, Mitsubishi Tanabe Pharma Corporation, 1000, Kamoshida-cho, Aoba-ku, Yokohama, Kanagawa, 227-0033, Japan
| | - Sibylle Neuhoff
- Certara UK Ltd, Simcyp Division, 1 Concourse Way, Level 2-Acero, Sheffield, S1 2BJ, UK
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK.,Certara UK Ltd, Simcyp Division, 1 Concourse Way, Level 2-Acero, Sheffield, S1 2BJ, UK
| | - Hiroyuki Takita
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK.,Development Planning, Clinical Development Center, Asahi Kasei Pharma Corporation, Hibiya Mitsui Tower, 1-1-2 Yurakucho, Chiyoda-ku, Tokyo, 100-0006, Japan
| | - Zubida M Al-Majdoub
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK
| | - Kayode Ogungbenro
- Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK.
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7
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Kim D, Bae GH, Kim HY, Jeon H, Kim K, Shin J, Lee S, Hong S, Kim I, Kim Y. Orally Administered Benzofuran Derivative Disaggregated Aβ Plaques and Oligomers in the Brain of 5XFAD Alzheimer Transgenic Mouse. ACS Chem Neurosci 2021; 12:99-108. [PMID: 33332107 DOI: 10.1021/acschemneuro.0c00606] [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] [Indexed: 02/06/2023] Open
Abstract
Amyloid-β (Aβ) aggregated forms are highly associated with the onset of Alzheimer's disease (AD). Aβ abnormally accumulates in the brain and induces neuronal damages and symptoms of AD such as cognitive impairment and memory loss. Since an antibody drug, aducanumab, reduces Aβ aggregates and delays clinical decline, clearance of accumulated Aβ in the brain is accounted as a therapeutic approach to treat AD. In this study, we synthesized 17 benzofuran derivatives that may disaggregate Aβ oligomers and plaques into inert monomers. By a series of Aβ aggregation inhibition and aggregates' disaggregation assays utilizing thioflavin T assays and gel electrophoresis, YB-9, 2-((5-methoxy-3-(4-methoxyphenyl)benzofuran-6-yl)oxy)acetic acid, was selected as the final Aβ-disaggregator candidate. When it was orally administered to the 8-month-old male transgenic mouse model with five familial AD mutations (5XFAD) via drinking water daily for two months, Aβ oligomers and plaques in hippocampus were reduced. Consequently, decreased astrogliosis and rescued synaptic dysfunction were observed in the hippocampus of YB-9-treated 5XFAD mice compared with the untreated transgenic control group.
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Affiliation(s)
- DaWon Kim
- Pharmaceutical Sciences Division and Wisconsin Center for NanoBioSystems, University of Wisconsin, Madison, Wisconsin 53705, United States
| | | | | | | | | | | | | | - Seungpyo Hong
- Pharmaceutical Sciences Division and Wisconsin Center for NanoBioSystems, University of Wisconsin, Madison, Wisconsin 53705, United States
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8
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Nam MH, Won W, Han KS, Lee CJ. Signaling mechanisms of μ-opioid receptor (MOR) in the hippocampus: disinhibition versus astrocytic glutamate regulation. Cell Mol Life Sci 2021; 78:415-426. [PMID: 32671427 PMCID: PMC11073310 DOI: 10.1007/s00018-020-03595-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 07/02/2020] [Accepted: 07/09/2020] [Indexed: 02/07/2023]
Abstract
μ-opioid receptor (MOR) is a class of opioid receptors that is critical for analgesia, reward, and euphoria. MOR is distributed in various brain regions, including the hippocampus, where traditionally, it is believed to be localized mainly at the presynaptic terminals of the GABAergic inhibitory interneurons to exert a strong disinhibitory effect on excitatory pyramidal neurons. However, recent intensive research has uncovered the existence of MOR in hippocampal astrocytes, shedding light on how astrocytic MOR participates in opioid signaling via glia-neuron interaction in the hippocampus. Activation of astrocytic MOR has shown to cause glutamate release from hippocampal astrocytes and increase the excitability of presynaptic axon fibers to enhance the release of glutamate at the Schaffer Collateral-CA1 synapses, thereby, intensifying the synaptic strength and plasticity. This novel mechanism involving astrocytic MOR has been shown to participate in hippocampus-dependent conditioned place preference. Furthermore, the signaling of hippocampal MOR, whose action is sexually dimorphic, is engaged in adult neurogenesis, seizure, and stress-induced memory impairment. In this review, we focus on the two profoundly different hippocampal opioid signaling pathways through either GABAergic interneuronal or astrocytic MOR. We further compare and contrast their molecular and cellular mechanisms and their possible roles in opioid-associated conditioned place preference and other hippocampus-dependent behaviors.
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Affiliation(s)
- Min-Ho Nam
- Center for Neuroscience, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
| | - Woojin Won
- KU-KIST Graduate School of Converging Science and Technology, Korea University, 145 Anam-ro, Seogbuk-gu, Seoul, 02841, Republic of Korea
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Kyung-Seok Han
- Department of Medical Biotechnology, Dongguk University-Gyeongju, 123 Dongdae-ro, Gyeongju, Gyeongbuk, Republic of Korea
| | - C Justin Lee
- KU-KIST Graduate School of Converging Science and Technology, Korea University, 145 Anam-ro, Seogbuk-gu, Seoul, 02841, Republic of Korea.
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea.
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9
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Computational framework for predictive PBPK-PD-Tox simulations of opioids and antidotes. J Pharmacokinet Pharmacodyn 2019; 46:513-529. [PMID: 31396799 DOI: 10.1007/s10928-019-09648-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Accepted: 07/29/2019] [Indexed: 10/26/2022]
Abstract
The primary goal of this work was to develop a computational tool to enable personalized prediction of pharmacological disposition and associated responses for opioids and antidotes. Here we present a computational framework for physiologically-based pharmacokinetic (PBPK) modeling of an opioid (morphine) and an antidote (naloxone). At present, the model is solely personalized according to an individual's mass. These PK models are integrated with a minimal pharmacodynamic model of respiratory depression induction (associated with opioid administration) and reversal (associated with antidote administration). The model was developed and validated on human data for IV administration of morphine and naloxone. The model can be further extended to consider different routes of administration, as well as to study different combinations of opioid receptor agonists and antagonists. This work provides the framework for a tool that could be used in model-based management of pain, pharmacological treatment of opioid addiction, appropriate use of antidotes for opioid overdose and evaluation of abuse deterrent formulations.
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10
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Madden JC, Pawar G, Cronin MT, Webb S, Tan YM, Paini A. In silico resources to assist in the development and evaluation of physiologically-based kinetic models. ACTA ACUST UNITED AC 2019. [DOI: 10.1016/j.comtox.2019.03.001] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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11
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Gerhart JG, Watt KM, Edginton A, Wade KC, Salerno SN, Benjamin DK, Smith PB, Hornik CP, Cohen-Wolkowiez M, Duara S, Ross A, Shattuck K, Stewart DL, Neu N, Gonzalez D. Physiologically-Based Pharmacokinetic Modeling of Fluconazole Using Plasma and Cerebrospinal Fluid Samples From Preterm and Term Infants. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2019; 8:500-510. [PMID: 31087536 PMCID: PMC6656941 DOI: 10.1002/psp4.12414] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 04/02/2019] [Indexed: 12/16/2022]
Abstract
Fluconazole is used to treat hematogenous Candida meningoencephalitis in preterm and term infants. To characterize plasma and central nervous system exposure, an adult fluconazole physiologically‐based pharmacokinetic (PBPK) model was scaled to infants, accounting for age dependencies in glomerular filtration and metabolism. The model was optimized using 760 plasma samples from 166 infants (median postmenstrual age (range) 28 weeks (24–50)) and 27 cerebrospinal fluid (CSF) samples from 22 infants (postmenstrual age 28 weeks (24–33)). Simulations evaluated achievement of the surrogate efficacy target of area under the unbound concentration‐time curve ≥ 400 mg • hour/L over the dosing interval in plasma and CSF using dosing guidelines. Average fold error of predicted concentrations was 0.73 and 1.14 for plasma and CSF, respectively. Target attainment in plasma and CSF was reached faster after incorporating a loading dose of 25 mg/kg. PBPK modeling can be useful in exploring CNS kinetics of drugs in children.
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Affiliation(s)
- Jacqueline G Gerhart
- Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Kevin M Watt
- Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Andrea Edginton
- School of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada
| | - Kelly C Wade
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Sara N Salerno
- Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Daniel K Benjamin
- Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - P Brian Smith
- Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Christoph P Hornik
- Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Michael Cohen-Wolkowiez
- Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Shahnaz Duara
- Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Ashley Ross
- University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Karen Shattuck
- Department of Pediatrics, University of Texas Medical Branch, Galveston, Texas, USA
| | - Dan L Stewart
- Department of Pediatrics, University of Louisville, Louisville, Kentucky, USA
| | - Natalie Neu
- Department of Pediatrics, Columbia University Medical Center, New York, New York, USA
| | - Daniel Gonzalez
- Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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12
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Tan C, Dong Y, Wang J, Yang X. Vanadyl acetylacetonate attenuates Aβ pathogenesis in APP/PS1 transgenic mice depending on the intervention stage. NEW J CHEM 2019. [DOI: 10.1039/c9nj00820a] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
VAC treatment caused different Grp75 responses before and after Aβ plaque formation.
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Affiliation(s)
- Chang Tan
- The State Key Laboratories of Natural and Biomimetic Drugs and Department of Chemical Biology
- School of Pharmaceutical Science
- Peking University Health Science Center
- Beijing 100191
- China
| | - Yaqiong Dong
- The State Key Laboratories of Natural and Biomimetic Drugs and Department of Chemical Biology
- School of Pharmaceutical Science
- Peking University Health Science Center
- Beijing 100191
- China
| | - Jing Wang
- The State Key Laboratories of Natural and Biomimetic Drugs and Department of Chemical Biology
- School of Pharmaceutical Science
- Peking University Health Science Center
- Beijing 100191
- China
| | - Xiaoda Yang
- The State Key Laboratories of Natural and Biomimetic Drugs and Department of Chemical Biology
- School of Pharmaceutical Science
- Peking University Health Science Center
- Beijing 100191
- China
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