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D’Ambrosio A, Altomare A, Boscarino T, Gori M, Balestrieri P, Putignani L, Del Chierico F, Carotti S, Cicala M, Guarino MPL, Piemonte V. Mathematical Modeling of Vedolizumab Treatment's Effect on Microbiota and Intestinal Permeability in Inflammatory Bowel Disease Patients. Bioengineering (Basel) 2024; 11:710. [PMID: 39061792 PMCID: PMC11274165 DOI: 10.3390/bioengineering11070710] [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: 06/01/2024] [Revised: 07/04/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Growing evidence suggests that impaired gut permeability and gut microbiota alterations are involved in the pathogenesis of Inflammatory Bowel Diseases (IBDs), which include Ulcerative Colitis (UC) and Crohn's Disease (CD). Vedolizumab is an anti-α4β7 antibody approved for IBD treatment, used as the first treatment or second-line therapy when the first line results in inadequate effectiveness. The aim of this study is to develop a mathematical model capable of describing the pathophysiological mechanisms of Vedolizumab treatment in IBD patients. In particular, the relationship between drug concentration in the blood, colonic mucosal permeability and fecal microbiota composition was investigated and modeled to detect and predict trends in order to support and tailor Vedolizumab therapies. To pursue this aim, clinical data from a pilot study on a cluster of 11 IBD patients were analyzed. Enrolled patients underwent colonoscopy in three phases (before (t0), after 24 weeks of (t1) and after 52 weeks of (t2 ) Vedolizumab treatment) to collect mucosal biopsies for transepithelial electrical resistance (TEER) evaluation (permeability to ions), intestinal permeability measurement and histological analysis. Moreover, fecal samples were collected for the intestinal microbiota analysis at the three time points. The collected data were compared to those of 11 healthy subjects at t0, who underwent colonoscopy for screening surveillance, and used to implement a three-compartmental mathematical model (comprising central blood, peripheral blood and the intestine). The latter extends previous evidence from the literature, based on the regression of experimental data, to link drug concentration in the peripheral blood compartment with Roseburia abundance and intestinal permeability. The clinical data showed that Vedolizumab treatment leads to an increase in TEER and a reduction in intestinal permeability to a paracellular probe, improving tissue inflammation status. Microbiota analysis showed increasing values of Roseburia, albeit not statistically significant. This trend was adequately reproduced by the mathematical model, which offers a useful tool to describe the pathophysiological effects of Vedolizumab therapy on colonic mucosal permeability and fecal microbiota composition. The model's satisfactory predictive capabilities and simplicity shed light on the relationship between the drug, the microbiota and permeability and allow for its straightforward extension to diverse therapeutic conditions.
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Affiliation(s)
- Antonio D’Ambrosio
- Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Science and Technology for Sustainable Development and One Health, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy; (T.B.); (V.P.)
| | - Annamaria Altomare
- Department of Sciences and Technology of Sustainable Development and Human Health, Università Campus Biomedico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy;
- Gastroenterology Research Unit, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy; (M.G.); (M.C.); (M.P.L.G.)
| | - Tamara Boscarino
- Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Science and Technology for Sustainable Development and One Health, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy; (T.B.); (V.P.)
| | - Manuele Gori
- Gastroenterology Research Unit, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy; (M.G.); (M.C.); (M.P.L.G.)
- Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR), International Campus “A. Buzzati-Traverso”, Via E. Ramarini 32, Monterotondo Scalo, 00015 Rome, Italy
| | - Paola Balestrieri
- Gastroenterology Unit, Fondazione Policlinico Campus Bio-Medico di Roma, Via Alvaro del Portillo 200, 00128 Rome, Italy;
| | - Lorenza Putignani
- Units of Microbiomics and Human Microbiome, Bambino Gesù Children’s Hospital, IRCCS, Piazza Sant’Onofrio 4, 00165 Rome, Italy;
| | - Federica Del Chierico
- Unit of Human Microbiome, Bambino Gesù Children’s Hospital, IRCCS, Piazza Sant’Onofrio 4, 00165 Rome, Italy;
| | - Simone Carotti
- Microscopic and Ultrastructural Anatomy Research Unit, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
| | - Michele Cicala
- Gastroenterology Research Unit, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy; (M.G.); (M.C.); (M.P.L.G.)
- Microscopic and Ultrastructural Anatomy Research Unit, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
| | - Michele Pier Luca Guarino
- Gastroenterology Research Unit, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy; (M.G.); (M.C.); (M.P.L.G.)
- Gastroenterology Unit, Fondazione Policlinico Campus Bio-Medico di Roma, Via Alvaro del Portillo 200, 00128 Rome, Italy;
| | - Vincenzo Piemonte
- Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Science and Technology for Sustainable Development and One Health, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy; (T.B.); (V.P.)
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Huang H, Zhao W, Qin N, Duan X. Recent Progress on Physiologically Based Pharmacokinetic (PBPK) Model: A Review Based on Bibliometrics. TOXICS 2024; 12:433. [PMID: 38922113 PMCID: PMC11209072 DOI: 10.3390/toxics12060433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 06/04/2024] [Accepted: 06/13/2024] [Indexed: 06/27/2024]
Abstract
Physiologically based pharmacokinetic/toxicokinetic (PBPK/PBTK) models are designed to elucidate the mechanism of chemical compound action in organisms based on the physiological, biochemical, anatomical, and thermodynamic properties of organisms. After nearly a century of research and practice, good results have been achieved in the fields of medicine, environmental science, and ecology. However, there is currently a lack of a more systematic review of progress in the main research directions of PBPK models, especially a more comprehensive understanding of the application in aquatic environmental research. In this review, a total of 3974 articles related to PBPK models from 1996 to 24 March 2024 were collected. Then, the main research areas of the PBPK model were categorized based on the keyword co-occurrence maps and cluster maps obtained by CiteSpace. The results showed that research related to medicine is the main application area of PBPK. Four major research directions included in the medical field were "drug assessment", "cross-species prediction", "drug-drug interactions", and "pediatrics and pregnancy drug development", in which "drug assessment" accounted for 55% of the total publication volume. In addition, bibliometric analyses indicated a rapid growth trend in the application in the field of environmental research, especially in predicting the residual levels in organisms and revealing the relationship between internal and external exposure. Despite facing the limitation of insufficient species-specific parameters, the PBPK model is still an effective tool for improving the understanding of chemical-biological effectiveness and will provide a theoretical basis for accurately assessing potential risks to ecosystems and human health. The combination with the quantitative structure-activity relationship model, Bayesian method, and machine learning technology are potential solutions to the previous research gaps.
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Affiliation(s)
| | | | - Ning Qin
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China; (H.H.); (W.Z.)
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China; (H.H.); (W.Z.)
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Talha Zahid M, Zamir A, Majeed A, Imran I, Alsanea S, Ahmad T, Alqahtani F, Fawad Rasool M. A physiologically based pharmacokinetic model of cefepime to predict its pharmacokinetics in healthy, pediatric and disease populations. Saudi Pharm J 2023; 31:101675. [PMID: 37576858 PMCID: PMC10415223 DOI: 10.1016/j.jsps.2023.06.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 06/12/2023] [Indexed: 08/15/2023] Open
Abstract
The physiologically based pharmacokinetic modeling (PBPK) approach can predict drug pharmacokinetics (PK) by combining changes in blood flow and pathophysiological alterations for developing drug-disease models. Cefepime hydrochloride is a parenteral cephalosporin that is used to treat pneumonia, sepsis, and febrile neutropenia, among other things. The current study sought to identify the factors that impact cefepime pharmacokinetics (PK) following dosing in healthy, diseased (CKD and obese), and pediatric populations. For model construction and simulation, the modeling tool PK-SIM was utilized. Estimating cefepime PK following intravenous (IV) application in healthy subjects served as the primary step in the model-building procedure. The prediction of cefepime PK in chronic kidney disease (CKD) and obese populations were performed after the integration of the relevant pathophysiological changes. Visual predictive checks and a comparison of the observed and predicted values of the PK parameters were used to verify the developed model. The results of the PK parameters were consistent with the reported clinical data in healthy subjects. The developed PBPK model successfully predicted cefepime PK as observed from the ratio of the observed and predicted PK parameters as they were within a two-fold error range.
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Affiliation(s)
- Muhammad Talha Zahid
- Department of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, 60800, Multan, Pakistan
| | - Ammara Zamir
- Department of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, 60800, Multan, Pakistan
| | - Abdul Majeed
- Department of Pharmaceutics, Faculty of Pharmacy, Bahauddin Zakariya University, 60800, Multan, Pakistan
| | - Imran Imran
- Department of Pharmacology, Faculty of Pharmacy, Bahauddin Zakariya University, 60800, Multan, Pakistan
| | - Sary Alsanea
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia
| | - Tanveer Ahmad
- Institute for Advanced Biosciences (IAB), CNRS UMR5309, INSERM U1209, Grenoble Alpes University, La Tronche 38700, France
| | - Faleh Alqahtani
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia
| | - Muhammad Fawad Rasool
- Department of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, 60800, Multan, Pakistan
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Ojara FW, Kawuma AN, Waitt C. A systematic review on maternal-to-infant transfer of drugs through breast milk during the treatment of malaria, tuberculosis, and neglected tropical diseases. PLoS Negl Trop Dis 2023; 17:e0011449. [PMID: 37440491 DOI: 10.1371/journal.pntd.0011449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND Exclusive breastfeeding of infants under 6 months of age is recommended by the World Health Organization. In 2021, over 300 million combined incident cases of malaria, tuberculosis, and neglected tropical diseases (NTDs) were reported, predominantly in low-income countries. For many of the drugs used as first-line treatments for these conditions, there is limited knowledge on infant exposure through breastfeeding with poorly understood consequences. This review summarized available knowledge on mother-to-infant transfer of these drugs to inform future lactation pharmacokinetic studies. METHODOLOGY A list of first-line drugs was generated from the latest WHO treatment guidelines. Using standard online databases, 2 independent reviewers searched for eligible articles reporting lactation pharmacokinetics studies and extracted information on study design, participant characteristics, and the mathematical approach used for parameter estimation. A third reviewer settled any disagreements between the 2 reviewers. All studies were scored against the standardized "ClinPK" checklist for conformity to best practices for reporting clinical pharmacokinetic studies. Simple proportions were used to summarize different study characteristics. FINDINGS The most remarkable finding was the scarcity of lactation pharmacokinetic data. Only 15 of the 69 drugs we listed had lactation pharmacokinetics fully characterized. Most studies enrolled few mothers, and only one evaluated infant drug concentrations. Up to 66% of the studies used non-compartmental analysis to estimate pharmacokinetic parameters rather than model-based compartmental analysis. Unlike non-compartmental approaches, model-based compartmental analysis provides for dynamic characterization of individual plasma and breast milk concentration-time profiles and adequately characterizes variability within and between individuals, using sparsely sampled data. The "ClinPK" checklist inadequately appraised the studies with variability in the number of relevant criteria across different studies. CONCLUSIONS/SIGNIFICANCE A consensus is required on best practices for conducting and reporting lactation pharmacokinetic studies, especially in neglected diseases such as malaria, tuberculosis, and NTDs, to optimize treatment of mother-infant pairs.
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Affiliation(s)
- Francis Williams Ojara
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
- Department of Pharmacology and Therapeutics, Gulu University, Gulu, Uganda
| | - Aida N Kawuma
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Catriona Waitt
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, United Kingdom
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Corpstein CD, Li T. A Perspective on Model-Informed IVIVC for Development of Subcutaneous Injectables. Pharm Res 2023; 40:1633-1639. [PMID: 37523013 DOI: 10.1007/s11095-023-03572-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 07/19/2023] [Indexed: 08/01/2023]
Abstract
Subcutaneously administered drugs are growing in popularity for both large and small molecule drugs. However, development of these systems - particularly generics - is slowed due to a lack of formal guidance regarding preclinical testing and in vitro - in vivo correlations (IVIVC). Many of these methods, while appropriate for oral drugs, may not be optimized for the complex injection site physiologies, and release rate and absorption mechanisms of subcutaneous drugs. Current limitations for formulation design and IVIVC can be supported by implementing mechanistic, computational methods. These methods can help to inform drug development by identifying key drug and formulation attributes, and their effects on drug release rates. This perspective, therefore, addresses current guidelines in place for oral IVIVC development, how they may differ for subcutaneously administered compounds, and how modeling and simulation can be implemented to inform design of these products. As such, integration of modeling and simulation with current IVIVC systems can help in driving the development of subcutaneous injectables.
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Affiliation(s)
- Clairissa D Corpstein
- Department of Industrial and Physical Pharmacy, Purdue University, West Lafayette, Indiana, USA
| | - Tonglei Li
- Department of Industrial and Physical Pharmacy, Purdue University, West Lafayette, Indiana, USA.
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Khan D, Badhan R, Kirby DJ, Bryson S, Shah M, Mohammed AR. Virtual Clinical Trials Guided Design of an Age-Appropriate Formulation and Dosing Strategy of Nifedipine for Paediatric Use. Pharmaceutics 2023; 15:pharmaceutics15020556. [PMID: 36839878 PMCID: PMC9961156 DOI: 10.3390/pharmaceutics15020556] [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: 11/29/2022] [Revised: 01/13/2023] [Accepted: 01/28/2023] [Indexed: 02/11/2023] Open
Abstract
The rapid onset of action of nifedipine causes a precipitous reduction in blood pressure leading to adverse effects associated with reflex sympathetic nervous system (SNS) activation, including tachycardia and worsening myocardial and cerebrovascular ischemia. As a result, short acting nifedipine preparations are not recommended. However, importantly, there are no modified release preparations of nifedipine authorised for paediatric use, and hence a paucity of clinical studies reporting pharmacokinetics data in paediatrics. Pharmacokinetic parameters may differ significantly between children and adults due to anatomical and physiological differences, often resulting in sub therapeutic and/or toxic plasma concentrations of medication. However, in the field of paediatric pharmacokinetics, the use of pharmacokinetic modelling, particularly physiological-based pharmacokinetics (PBPK), has revolutionised the ability to extrapolate drug pharmacokinetics across age groups, allowing for pragmatic determination of paediatric plasma concentrations to support drug licensing and clinical dosing. In order to pragmatically assess the translation of resultant dissolution profiles to the paediatric populations, virtual clinical trials simulations were conducted. In the context of formulation development, the use of PBPK modelling allowed the determination of optimised formulations that achieved plasma concentrations within the target therapeutic window throughout the dosing strategy. A 5 mg sustained release mini-tablet was successfully developed with the duration of release extending over 24 h and an informed optimised dosing strategy of 450 µg/kg twice daily. The resulting formulation provides flexible dosing opportunities, improves patient adherence by reducing frequent administration burden and enhances patient safety profiles by maintaining efficacious levels of consistent drug plasma levels over a sustained period of time.
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Affiliation(s)
- Dilawar Khan
- Aston Pharmacy School, College of Health and Life Sciences, Aston University, Birmingham B4 7ET, UK
| | - Raj Badhan
- Aston Pharmacy School, College of Health and Life Sciences, Aston University, Birmingham B4 7ET, UK
| | - Daniel J. Kirby
- Aston Pharmacy School, College of Health and Life Sciences, Aston University, Birmingham B4 7ET, UK
| | - Simon Bryson
- Proveca Ltd., No. 1 Spinningfields, Quay Street, Manchester M3 3JE, UK
| | - Maryam Shah
- Proveca Ltd., No. 1 Spinningfields, Quay Street, Manchester M3 3JE, UK
| | - Afzal Rahman Mohammed
- Aston Pharmacy School, College of Health and Life Sciences, Aston University, Birmingham B4 7ET, UK
- Correspondence:
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Jayanti RP, Long NP, Phat NK, Cho YS, Shin JG. Semi-Automated Therapeutic Drug Monitoring as a Pillar toward Personalized Medicine for Tuberculosis Management. Pharmaceutics 2022; 14:pharmaceutics14050990. [PMID: 35631576 PMCID: PMC9147223 DOI: 10.3390/pharmaceutics14050990] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 04/26/2022] [Accepted: 05/02/2022] [Indexed: 12/10/2022] Open
Abstract
Standard tuberculosis (TB) management has failed to control the growing number of drug-resistant TB cases worldwide. Therefore, innovative approaches are required to eradicate TB. Model-informed precision dosing and therapeutic drug monitoring (TDM) have become promising tools for adjusting anti-TB drug doses corresponding with individual pharmacokinetic profiles. These are crucial to improving the treatment outcome of the patients, particularly for those with complex comorbidity and a high risk of treatment failure. Despite the actual benefits of TDM at the bedside, conventional TDM encounters several hurdles related to laborious, time-consuming, and costly processes. Herein, we review the current practice of TDM and discuss the main obstacles that impede it from successful clinical implementation. Moreover, we propose a semi-automated TDM approach to further enhance precision medicine for TB management.
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Affiliation(s)
- Rannissa Puspita Jayanti
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Nguyen Phuoc Long
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Nguyen Ky Phat
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Yong-Soon Cho
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Jae-Gook Shin
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
- Department of Clinical Pharmacology, Inje University Busan Paik Hospital, Busan 47392, Korea
- Correspondence: ; Tel.: +82-51-890-6709; Fax: +82-51-893-1232
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Bahrami F, Rossi RM, Defraeye T. Predicting transdermal fentanyl delivery using physics-based simulations for tailored therapy based on the age. Drug Deliv 2022; 29:950-969. [PMID: 35319323 PMCID: PMC8956318 DOI: 10.1080/10717544.2022.2050846] [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] [Indexed: 12/19/2022] Open
Abstract
Transdermal fentanyl patches are an effective alternative to the sustained release of oral morphine for chronic pain management. Due to the narrow therapeutic range of fentanyl, the concentration of fentanyl in the blood needs to be carefully monitored. Only then can effective pain relief be achieved while avoiding adverse effects such as respiratory depression. This study developed a physics-based digital twin of a patient by implementing drug uptake, pharmacokinetics, and pharmacodynamics models. The twin was employed to predict the in-silico effect of conventional fentanyl transdermal in a 20–80-year-old virtual patient. The results show that, with increasing age, the maximum transdermal fentanyl flux and maximum concentration of fentanyl in the blood decreased by 11.4% and 7.0%, respectively. However, the results also show that as the patient's age increases, the pain relief increases by 45.2%. Furthermore, the digital twin was used to propose a tailored therapy based on the patient's age. This predesigned therapy customized the duration of applying the commercialized fentanyl patches. According to this therapy, a 20-year-old patient needs to change the patch 2.1 times more frequently than conventional therapy, which leads to 30% more pain relief and 315% more time without pain. In addition, the digital twin was updated by the patient's pain intensity feedback. Such therapy increased the patient's breathing rate while providing effective pain relief, so a safer treatment. We quantified the added value of a patient's physics-based digital twin and sketched the future roadmap for implementing such twin-assisted treatment into the clinics.
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Affiliation(s)
- Flora Bahrami
- Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Biomimetic Membranes and Textiles, St. Gallen, Switzerland.,ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - René Michel Rossi
- Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Biomimetic Membranes and Textiles, St. Gallen, Switzerland
| | - Thijs Defraeye
- Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Biomimetic Membranes and Textiles, St. Gallen, Switzerland
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Thompson CV, Firman JW, Goldsmith MR, Grulke CM, Tan YM, Paini A, Penson PE, Sayre RR, Webb S, Madden JC. A Systematic Review of Published Physiologically-based Kinetic Models and an Assessment of their Chemical Space Coverage. Altern Lab Anim 2021; 49:197-208. [PMID: 34836462 DOI: 10.1177/02611929211060264] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Across multiple sectors, including food, cosmetics and pharmaceutical industries, there is a need to predict the potential effects of xenobiotics. These effects are determined by the intrinsic ability of the substance, or its derivatives, to interact with the biological system, and its concentration-time profile at the target site. Physiologically-based kinetic (PBK) models can predict organ-level concentration-time profiles, however, the models are time and resource intensive to generate de novo. Read-across is an approach used to reduce or replace animal testing, wherein information from a data-rich chemical is used to make predictions for a data-poor chemical. The recent increase in published PBK models presents the opportunity to use a read-across approach for PBK modelling, that is, to use PBK model information from one chemical to inform the development or evaluation of a PBK model for a similar chemical. Essential to this process, is identifying the chemicals for which a PBK model already exists. Herein, the results of a systematic review of existing PBK models, compliant with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format, are presented. Model information, including species, sex, life-stage, route of administration, software platform used and the availability of model equations, was captured for 7541 PBK models. Chemical information (identifiers and physico-chemical properties) has also been recorded for 1150 unique chemicals associated with these models. This PBK model data set has been made readily accessible, as a Microsoft Excel® spreadsheet, providing a valuable resource for those developing, using or evaluating PBK models in industry, academia and the regulatory sectors.
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Affiliation(s)
- Courtney V Thompson
- School of Pharmacy and Biomolecular Sciences, 4589Liverpool John Moores University, Liverpool, UK
| | - James W Firman
- School of Pharmacy and Biomolecular Sciences, 4589Liverpool John Moores University, Liverpool, UK
| | - Michael R Goldsmith
- Office of Research and Development, Center for Computational Toxicology and Exposure, Chemical Characterization and Exposure Division, 427887US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Christopher M Grulke
- Office of Research and Development, Center for Computational Toxicology and Exposure, Chemical Characterization and Exposure Division, 427887US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Yu-Mei Tan
- Office of Pesticide Programs, Health Effects Division, 138030US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Alicia Paini
- 99013European Commission Joint Research Centre (JRC), Ispra, Italy
| | - Peter E Penson
- School of Pharmacy and Biomolecular Sciences, 4589Liverpool John Moores University, Liverpool, UK
| | - Risa R Sayre
- Office of Research and Development, Center for Computational Toxicology and Exposure, Chemical Characterization and Exposure Division, 427887US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Steven Webb
- Syngenta, Product Safety, Early Stage Research, 101825Jealott's Hill International Research Centre, Bracknell, UK
| | - Judith C Madden
- School of Pharmacy and Biomolecular Sciences, 4589Liverpool John Moores University, Liverpool, UK
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10
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PBPK Modeling and Simulation and Therapeutic Drug Monitoring: Possible Ways for Antibiotic Dose Adjustment. Processes (Basel) 2021. [DOI: 10.3390/pr9112087] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Pharmacokinetics (PK) is a branch of pharmacology present and of vital importance for the research and development (R&D) of new drugs, post-market monitoring, and continued optimizations in clinical contexts. Ultimately, pharmacokinetics can contribute to improving patients’ clinical outcomes, helping enhance the efficacy of treatments, and reducing possible adverse side effects while also contributing to precision medicine. This article discusses the methods used to predict and study human pharmacokinetics and their evolution to the current physiologically based pharmacokinetic (PBPK) modeling and simulation methods. The importance of therapeutic drug monitoring (TDM) and PBPK as valuable tools for Model-Informed Precision Dosing (MIPD) are highlighted, with particular emphasis on antibiotic therapy since dosage adjustment of antibiotics can be vital to ensure successful clinical outcomes and to prevent the spread of resistant bacterial strains.
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Jeong HC, Chae YJ, Lee S, Kang W, Yun HY, Shin KH. Prediction of Fluoxetine and Norfluoxetine Pharmacokinetic Profiles Using Physiologically Based Pharmacokinetic Modeling. J Clin Pharmacol 2021; 61:1505-1513. [PMID: 34118174 DOI: 10.1002/jcph.1927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 06/10/2021] [Indexed: 11/06/2022]
Abstract
Fluoxetine is a selective serotonin reuptake inhibitor that is metabolized to norfluoxetine by cytochrome P450 (CYP) 2D6, CYP2C19, and CYP3A4. A physiologically based pharmacokinetic model for fluoxetine and norfluoxetine metabolism was developed to predict and investigate changes in concentration-time profiles according to fluoxetine dosage in the Korean population. The model was developed based on the Certara repository model and information gleaned from the literature. Digitally extracted clinical study data were used to develop and verify the model. Simulations for plasma concentrations of fluoxetine and norfluoxetine after a single dose of 60 or 80 mg fluoxetine were made based on 1000 virtual healthy Korean individuals using the SimCYP version 19 simulator. The mean ratios (simulated/observed) after a single administration of 80 mg fluoxetine for maximum plasma concentration, area under the plasma concentration-time curve, and apparent clearance were 1.12, 1.08, and 0.93 for fluoxetine; the ratios of maximum plasma concentration and area under the plasma concentration-time curve were 1.08 and 1.08, respectively, for norfluoxetine, indicating that the simulated concentration-time profiles of fluoxetine and norfluoxetine fitted the observed profiles well. The developed model was used to predict plasma fluoxetine and norfluoxetine concentration-time profiles after repeated administrations of fluoxetine in Korean volunteers. This physiologically based pharmacokinetic model could provide basic understanding of the pharmacokinetic profiles of fluoxetine and its metabolite under various situations.
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Affiliation(s)
- Hyeon-Cheol Jeong
- College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu, Republic of Korea
| | - Yoon-Jee Chae
- College of Pharmacy, Woosuk University, Jeonbuk, Republic of Korea
| | - Sooyeun Lee
- College of Pharmacy, Keimyung University, Daegu, Republic of Korea
| | - Wonku Kang
- College of Pharmacy, Chung-Ang University, Seoul, Republic of Korea
| | - Hwi-Yeol Yun
- College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea
| | - Kwang-Hee Shin
- College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu, Republic of Korea
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12
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Zhou K, Mi K, Ma W, Xu X, Huo M, Algharib SA, Pan Y, Xie S, Huang L. Application of physiologically based pharmacokinetic models to promote the development of veterinary drugs with high efficacy and safety. J Vet Pharmacol Ther 2021; 44:663-678. [PMID: 34009661 DOI: 10.1111/jvp.12976] [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: 03/01/2021] [Revised: 10/27/2020] [Accepted: 04/18/2021] [Indexed: 12/12/2022]
Abstract
Physiologically based pharmacokinetic (PBPK) models have become important tools for the development of novel human drugs. Food-producing animals and pets comprise an important part of human life, and the development of veterinary drugs (VDs) has greatly impacted human health. Owing to increased affordability of and demand for drug development, VD manufacturing companies should have more PBPK models required to reduce drug production costs. So far, little attention has been paid on applying PBPK models for the development of VDs. This review begins with the development processes of VDs; then summarizes case studies of PBPK models in human or VD development; and analyzes the application, potential, and advantages of PBPK in VD development, including candidate screening, formulation optimization, food effects, target-species safety, and dosing optimization. Then, the challenges of applying the PBPK model to VD development are discussed. Finally, future opportunities of PBPK models in designing dosing regimens for intracellular pathogenic infections and for efficient oral absorption of VDs are further forecasted. This review will be relevant to readers who are interested in using a PBPK model to develop new VDs.
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Affiliation(s)
- Kaixiang Zhou
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China
| | - Kun Mi
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China
| | - Wenjin Ma
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China
| | - Xiangyue Xu
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China
| | - Meixia Huo
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China
| | - Samah Attia Algharib
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China.,Department of Clinical Pathology, Faculty of Veterinary Medicine, Benha University, Moshtohor, Toukh, Egypt
| | - Yuanhu Pan
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China.,MOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Huazhong Agricultural University, Wuhan, China
| | - Shuyu Xie
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China.,MOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Huazhong Agricultural University, Wuhan, China
| | - Lingli Huang
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Wuhan, China.,MOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Huazhong Agricultural University, Wuhan, China
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13
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Li L, He H, Jiang S, Qi J, Lu Y, Ding N, Lin HS, Wu W, Xiang X. Simulation of the In Vivo Fate of Polymeric Nanoparticles Traced by Environment-Responsive Near-Infrared Dye: A Physiologically Based Pharmacokinetic Modelling Approach. Molecules 2021; 26:molecules26051271. [PMID: 33652827 PMCID: PMC7956253 DOI: 10.3390/molecules26051271] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 02/21/2021] [Accepted: 02/22/2021] [Indexed: 12/18/2022] Open
Abstract
The application of physiologically based pharmacokinetic models to nanoparticles is still very restricted and challenging, owing to the complicated in vivo transport mechanisms involving nanoparticles, including phagocytosis, enhanced permeability and retention effects, cellular recognition, and internalisation, enzymatic degradation, lymphatic transport, and changes in physical properties. In our study, five nanoparticle formulations were synthesised using polycaprolactone as a framework material and methoxy poly (ethylene glycol)-poly(ε-caprolactone) as a long-circulating decorating material, as well as types of environmentally responsive near-infrared aza-boron-dipyrromethene dyes. According to quantification data and direct visualisation involving specific organs, a phagocytosis physiologically based pharmacokinetic model was developed to describe the dynamics of nanoparticles within and between organs in mice, considering cellular mechanisms involving phagocytosis and enhanced permeability and retention effects. Our results offer a better understanding of the in vivo fate of polymeric nanoparticles.
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Affiliation(s)
- Lei Li
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai 201203, China;
| | - Haisheng He
- Key Laboratory of Smart Drug Delivery of MOE and PLA, School of Pharmacy, Fudan University, Shanghai 201203, China; (H.H.); (J.Q.); (Y.L.)
| | - Sifang Jiang
- West China School of Pharmacy, Sichuan University, Chengdu 610041, China;
| | - Jianping Qi
- Key Laboratory of Smart Drug Delivery of MOE and PLA, School of Pharmacy, Fudan University, Shanghai 201203, China; (H.H.); (J.Q.); (Y.L.)
| | - Yi Lu
- Key Laboratory of Smart Drug Delivery of MOE and PLA, School of Pharmacy, Fudan University, Shanghai 201203, China; (H.H.); (J.Q.); (Y.L.)
| | - Ning Ding
- Department of Medicinal Chemistry, School of Pharmacy, Fudan University, Shanghai 201203, China;
| | - Hai-Shu Lin
- College of Pharmacy, Shenzhen Technology University, Shenzhen 518118, China;
| | - Wei Wu
- Key Laboratory of Smart Drug Delivery of MOE and PLA, School of Pharmacy, Fudan University, Shanghai 201203, China; (H.H.); (J.Q.); (Y.L.)
- Correspondence: (W.W.); (X.X.); Tel.: +86-021-5198-0084 (W.W.); +86-021-5198-0024 (X.X.)
| | - Xiaoqiang Xiang
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai 201203, China;
- Correspondence: (W.W.); (X.X.); Tel.: +86-021-5198-0084 (W.W.); +86-021-5198-0024 (X.X.)
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14
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Willmann S, Coboeken K, Kapsa S, Thelen K, Mundhenke M, Fischer K, Hügl B, Mück W. Applications of Physiologically Based Pharmacokinetic Modeling of Rivaroxaban-Renal and Hepatic Impairment and Drug-Drug Interaction Potential. J Clin Pharmacol 2021; 61:656-665. [PMID: 33205449 PMCID: PMC8048900 DOI: 10.1002/jcph.1784] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 11/09/2020] [Indexed: 02/06/2023]
Abstract
The non–vitamin K antagonist oral anticoagulant rivaroxaban is used in several thromboembolic disorders. Rivaroxaban is eliminated via both metabolic degradation and renal elimination as unchanged drug. Therefore, renal and hepatic impairment may reduce rivaroxaban clearance, and medications inhibiting these clearance pathways could lead to drug‐drug interactions. This physiologically based pharmacokinetic (PBPK) study investigated the pharmacokinetic behavior of rivaroxaban in clinical situations where drug clearance is impaired. A PBPK model was developed using mass balance and bioavailability data from adults and qualified using clinically observed data. Renal and hepatic impairment were simulated by adjusting disease‐specific parameters, and concomitant drug use was simulated by varying enzyme activity in virtual populations (n = 1000) and compared with pharmacokinetic predictions in virtual healthy populations and clinical observations. Rivaroxaban doses of 10 mg or 20 mg were used. Mild to moderate renal impairment had a minor effect on area under the concentration‐time curve and maximum plasma concentration of rivaroxaban, whereas severe renal impairment caused a more pronounced increase in these parameters vs normal renal function. Area under the concentration‐time curve and maximum plasma concentration increased with severity of hepatic impairment. These effects were smaller in the simulations compared with clinical observations. AUC and Cmax increased with the strength of cytochrome P450 3A4 and P‐glycoprotein inhibitors in simulations and clinical observations. This PBPK model can be useful for estimating the effects of impaired drug clearance on rivaroxaban pharmacokinetics. Identifying other factors that affect the pharmacokinetics of rivaroxaban could facilitate the development of models that approximate real‐world pharmacokinetics more accurately.
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Affiliation(s)
| | | | - Stefanie Kapsa
- Clinical Pharmacokinetics Cardiovascular, Bayer AG, Wuppertal, Germany
| | - Kirstin Thelen
- Clinical Pharmacokinetics Cardiovascular, Bayer AG, Wuppertal, Germany
| | - Markus Mundhenke
- Medical Affairs Cardiovascular, Bayer Vital GmbH, Leverkusen, Germany
| | | | - Burkhard Hügl
- Clinic for Cardiology and Rhythmology, Marienhaus Klinikum St Elisabeth Neuwied, Neuwied, Germany
| | - Wolfgang Mück
- Clinical Pharmacokinetics Cardiovascular, Bayer AG, Wuppertal, Germany
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15
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Physiologically-based pharmacokinetic models for children: Starting to reach maturation? Pharmacol Ther 2020; 211:107541. [DOI: 10.1016/j.pharmthera.2020.107541] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 03/19/2020] [Indexed: 12/13/2022]
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16
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Chen F, Liu H, Wang B, Yang L, Cai W, Jiao Z, Yang Z, Chen Y, Quan Y, Xiang X, Wang H. Physiologically Based Pharmacokinetic Modeling to Understand the Absorption of Risperidone Orodispersible Film. Front Pharmacol 2020; 10:1692. [PMID: 32116683 PMCID: PMC7008171 DOI: 10.3389/fphar.2019.01692] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 12/26/2019] [Indexed: 11/13/2022] Open
Abstract
Objective The aim of the present study was to investigate the absorption routes as well as the potential application of the oral transmucosal delivery of risperidone orodispersible film (ODF) using physiologically based pharmacokinetic modeling. Methods The pharmacokinetic study after intragastric (i.g.), supralingual, and sublingual administration of risperidone ODF was conducted in Beagle dogs. Then a mechanic absorption model which combined Oral Cavity Compartment Absorption and Transit (OCCAT) model with Advanced Compartment Absorption and Transit (ACAT) model for predicting the absorption routes of risperidone ODF in vivo was constructed using GastroPlus™. A sensitivity analysis was performed to investigate the impact of oral residence time on the in vivo absorption of risperidone ODF. Based on the fraction of intraoral absorption, the potential of the oral transmucosal delivery of risperidone were predicted. Results There were no statistical differences in the AUC0-t (P = 0.4327), AUC0-∞ (P = 0.3278), Cmax (P = 0.0531), and Tmax (P = 0.2775) values among i.g., supralingual, and sublingual administration of risperidone ODF in Beagle dogs. The predicted absorption percentage via oral mucosa at oral residence time of 2 min, 5 min, and 10 min was 7.0%, 11.4%, and 19.5%, respectively. No obvious difference was observed for the bioavailability of risperidone ODF within 10 min of oral residence time. The PBPK absorption model for risperidone could be simplified to include ACAT model solely. Conclusion The main absorption route for risperidone ODF was the gastrointestine. The absorption percentage via oral mucosa was almost negligible due to the physicochemical properties of risperidone although ODF dissolved completely in the oral cavity of Beagle dogs within 2 min.
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Affiliation(s)
- Fang Chen
- National Pharmaceutical Engineering Research Center, China State Institute of Pharmaceutical Industry, Shanghai, China
| | - Hongrui Liu
- National Pharmaceutical Engineering Research Center, China State Institute of Pharmaceutical Industry, Shanghai, China
| | - Bing Wang
- National Pharmaceutical Engineering Research Center, China State Institute of Pharmaceutical Industry, Shanghai, China
| | - Liuliu Yang
- National Pharmaceutical Engineering Research Center, China State Institute of Pharmaceutical Industry, Shanghai, China
| | - Weimin Cai
- Department of Clinical Pharmacy, School of Pharmacy, Fudan University, Shanghai, China
| | - Zheng Jiao
- Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Zhou Yang
- Department of General Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
| | - Yusheng Chen
- Department of General Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
| | - Yingjun Quan
- Department of General Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
| | - Xiaoqiang Xiang
- Department of Clinical Pharmacy, School of Pharmacy, Fudan University, Shanghai, China
| | - Hao Wang
- National Pharmaceutical Engineering Research Center, China State Institute of Pharmaceutical Industry, Shanghai, China
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17
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Price E, Gesquiere AJ. An in vitro assay and artificial intelligence approach to determine rate constants of nanomaterial-cell interactions. Sci Rep 2019; 9:13943. [PMID: 31558741 PMCID: PMC6763461 DOI: 10.1038/s41598-019-50208-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Accepted: 09/05/2019] [Indexed: 12/11/2022] Open
Abstract
In vitro assays and simulation technologies are powerful methodologies that can inform scientists of nanomaterial (NM) distribution and fate in humans or pre-clinical species. For small molecules, less animal data is often needed because there are a multitude of in vitro screening tools and simulation-based approaches to quantify uptake and deliver data that makes extrapolation to in vivo studies feasible. Small molecule simulations work because these materials often diffuse quickly and partition after reaching equilibrium shortly after dosing, but this cannot be applied to NMs. NMs interact with cells through energy dependent pathways, often taking hours or days to become fully internalized within the cellular environment. In vitro screening tools must capture these phenomena so that cell simulations built on mechanism-based models can deliver relationships between exposure dose and mechanistic biology, that is biology representative of fundamental processes involved in NM transport by cells (e.g. membrane adsorption and subsequent internalization). Here, we developed, validated, and applied the FORECAST method, a combination of a calibrated fluorescence assay (CF) with an artificial intelligence-based cell simulation to quantify rates descriptive of the time-dependent mechanistic biological interactions between NMs and individual cells. This work is expected to provide a means of extrapolation to pre-clinical or human biodistribution with cellular level resolution for NMs starting only from in vitro data.
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Affiliation(s)
- Edward Price
- NanoScience Technology Center, University of Central Florida, Orlando, FL, 32826, USA
- Department of Chemistry, University of Central Florida, Orlando, FL, 32816, USA
| | - Andre J Gesquiere
- NanoScience Technology Center, University of Central Florida, Orlando, FL, 32826, USA.
- Department of Chemistry, University of Central Florida, Orlando, FL, 32816, USA.
- Department of Materials Science and Engineering, University of Central Florida, Orlando, FL, 32816, USA.
- The College of Optics and Photonics (CREOL), University of Central Florida, Orlando, FL, 32816, USA.
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18
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Development of a physiologically based pharmacokinetic model for intravenous lenalidomide in mice. Cancer Chemother Pharmacol 2019; 84:1073-1087. [PMID: 31493176 DOI: 10.1007/s00280-019-03941-z] [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: 03/21/2019] [Accepted: 08/23/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE Lenalidomide is used widely in B-cell malignancies for its immunomodulatory activity. It is primarily eliminated via the kidneys, with a significant proportion of renal elimination attributed to active processes. Lenalidomide is a weak substrate of P-glycoprotein (P-gp), though it is unclear whether P-gp is solely responsible for lenalidomide transport. This study aimed to determine whether the current knowledge of lenalidomide was sufficient to describe the pharmacokinetics of lenalidomide in multiple tissues. METHODS A physiologically based pharmacokinetic model was developed using the Open Systems Pharmacology Suite to explore the pharmacokinetics of lenalidomide in a variety of tissues. Data were available for mice dosed intravenously at 0.5, 1.5, 5, and 10 mg/kg, with concentrations measured in plasma, brain, heart, kidney, liver, lung, muscle, and spleen. P-gp expression and activity were sourced from the literature. RESULTS The model predictions in plasma, liver, and lung were representative of the observed data (median prediction error 13%, - 10%, and 30%, respectively, with 90% confidence intervals including zero), while other tissue predictions showed sufficient similarity to the observed data. Contrary to the data, model predictions for the brain showed no drug reaching brain tissue when P-gp was expressed at the blood-brain barrier. The data were better described by basolateral transporters at the intracellular wall. Local sensitivity analysis showed that transporter activity was the most sensitive parameter in these models for exposure. CONCLUSION As P-gp transport at the blood-brain barrier did not explain the observed brain concentrations alone, there may be other transporters involved in lenalidomide disposition.
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Pryor R, Martinez-Martinez D, Quintaneiro L, Cabreiro F. The Role of the Microbiome in Drug Response. Annu Rev Pharmacol Toxicol 2019; 60:417-435. [PMID: 31386593 DOI: 10.1146/annurev-pharmtox-010919-023612] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The microbiome is known to regulate many aspects of host health and disease and is increasingly being recognized as a key mediator of drug action. However, investigating the complex multidirectional relationships between drugs, the microbiota, and the host is a challenging endeavor, and the biological mechanisms that underpin these interactions are often not well understood. In this review, we outline the current evidence that supports a role for the microbiota as a contributor to both the therapeutic benefits and side effects of drugs, with a particular focus on those used to treat mental disorders, type 2 diabetes, and cancer. We also provide a snapshot of the experimental and computational tools that are currently available for the dissection of drug-microbiota-host interactions. The advancement of knowledge in this area may ultimately pave the way for the development of novel microbiota-based strategies that can be used to improve treatment outcomes.
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Affiliation(s)
- Rosina Pryor
- MRC London Institute of Medical Sciences, London W12 0NN, United Kingdom; .,Institute of Clinical Sciences, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
| | - Daniel Martinez-Martinez
- MRC London Institute of Medical Sciences, London W12 0NN, United Kingdom; .,Institute of Clinical Sciences, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
| | - Leonor Quintaneiro
- MRC London Institute of Medical Sciences, London W12 0NN, United Kingdom; .,Institute of Clinical Sciences, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, United Kingdom.,Institute of Structural and Molecular Biology, University College London and Birkbeck, London WC1E 6BT, United Kingdom
| | - Filipe Cabreiro
- MRC London Institute of Medical Sciences, London W12 0NN, United Kingdom; .,Institute of Clinical Sciences, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
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Smits A, De Cock P, Vermeulen A, Allegaert K. Physiologically based pharmacokinetic (PBPK) modeling and simulation in neonatal drug development: how clinicians can contribute. Expert Opin Drug Metab Toxicol 2018; 15:25-34. [PMID: 30554542 DOI: 10.1080/17425255.2019.1558205] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Introduction: Legal initiatives to stimulate neonatal drug development should be accompanied by development of valid research tools. Physiologically based (PB)-pharmacokinetic (PK) modeling and simulation are established tools, accepted by regulatory authorities. Consequently, PBPK holds promise to be a strong research tool to support neonatal drug development. Area covered: The currently available PBPK models still have poor predictive performance in neonates. Using an illustrative approach on distinct PK processes of absorption, distribution, metabolism, excretion, and real-world data in neonates, we provide evidence on the need to further refine available PBPK system parameters through generation and integration of new knowledge. This necessitates cross talk between clinicians and modelers to integrate knowledge (PK datasets, system knowledge, maturational physiology) or test and refine PBPK models. Expert opinion: Besides refining these models for 'small molecules', PBPK model development should also be more widely applied for therapeutic proteins and to determine exposure through breastfeeding. Researchers should also be aware that PBPK modeling in combination with clinical observations can also be used to elucidate age-related changes that are almost impossible to study based on in vivo or in vitro data. This approach has been explored for hepatic biliary excretion, renal tubular activity, and central nervous system exposure.
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Affiliation(s)
- Anne Smits
- a Neonatal Intensive Care Unit , University Hospitals Leuven , Leuven , Belgium.,b Department of Development and Regeneration , KU Leuven , Leuven , Belgium
| | - Pieter De Cock
- c Department of Pharmacy , Ghent University Hospital , Ghent , Belgium.,d Heymans Institute of Pharmacology , Ghent University , Ghent , Belgium.,e Department of Pediatric Intensive Care , Ghent University , Ghent , Belgium
| | - An Vermeulen
- f Laboratory of Medical Biochemistry and Clinical Analysis, Faculty of Pharmaceutical Sciences , Ghent University , Ghent , Belgium
| | - Karel Allegaert
- b Department of Development and Regeneration , KU Leuven , Leuven , Belgium.,g Department of Pediatrics, Division of Neonatology , Erasmus MC Sophia Children's Hospital, University Medical Center Rotterdam , Rotterdam , The Netherlands
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Abstract
Organ-on-a-chip technology provides a novel in vitro platform with a possibility of reproducing physiological functions of in vivo tissue, more accurately than conventional cell-based model systems. Many newly arising diseases result from complex interaction between multiple organs. By realizing different organ functions on a chip, organ-on-a-chip technology is a potentially useful for building models of such complex diseases. Pharmacokinetic (PK) models provide a mathematical framework for understanding the interaction between organs involving transport and reaction of molecules. Here, we discuss various forms of organ-on-a-chip devices reported so far, with a particular emphasis on multi-organ devices for recapitulating multi-organ interactions. Also, we introduce the concept of PK models, and explain how it can be used to design and analyze multi-organ chip devices.
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Affiliation(s)
- Jong Hwan Sung
- Department of Chemical Engineering, Hongik University, Seoul, South Korea.
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22
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Guimarães M, Statelova M, Holm R, Reppas C, Symilllides M, Vertzoni M, Fotaki N. Biopharmaceutical considerations in paediatrics with a view to the evaluation of orally administered drug products - a PEARRL review. ACTA ACUST UNITED AC 2018; 71:603-642. [PMID: 29971768 DOI: 10.1111/jphp.12955] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2018] [Accepted: 05/28/2018] [Indexed: 12/25/2022]
Abstract
OBJECTIVES In this review, the current biopharmaceutical approaches for evaluation of oral formulation performance in paediatrics are discussed. KEY FINDINGS The paediatric gastrointestinal (GI) tract undergoes numerous morphological and physiological changes throughout its development and growth. Some physiological parameters are yet to be investigated, limiting the use of the existing in vitro biopharmaceutical tools to predict the in vivo performance of paediatric formulations. Meals and frequencies of their administration evolve during childhood and affect oral drug absorption. Furthermore, the establishment of a paediatric Biopharmaceutics Classification System (pBCS), based on the adult Biopharmaceutics Classification System (BCS), requires criteria adjustments. The usefulness of computational simulation and modeling for extrapolation of adult data to paediatrics has been confirmed as a tool for predicting drug formulation performance. Despite the great number of successful physiologically based pharmacokinetic models to simulate drug disposition, the simulation of drug absorption from the GI tract is a complicating issue in paediatric populations. SUMMARY The biopharmaceutics tools for investigation of oral drug absorption in paediatrics need further development, refinement and validation. A combination of in vitro and in silico methods could compensate for the uncertainties accompanying each method on its own.
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Affiliation(s)
- Mariana Guimarães
- Department of Pharmacy and Pharmacology, University of Bath, Bath, UK
| | - Marina Statelova
- Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - René Holm
- Drug Product Development, Janssen Research and Development, Johnson & Johnson, Beerse, Belgium
| | - Christos Reppas
- Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - Moira Symilllides
- Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - Maria Vertzoni
- Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - Nikoletta Fotaki
- Department of Pharmacy and Pharmacology, University of Bath, Bath, UK
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23
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Thiele I, Clancy CM, Heinken A, Fleming RM. Quantitative systems pharmacology and the personalized drug-microbiota-diet axis. CURRENT OPINION IN SYSTEMS BIOLOGY 2017; 4:43-52. [PMID: 32984662 PMCID: PMC7493425 DOI: 10.1016/j.coisb.2017.06.001] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Precision medicine is an emerging paradigm that aims at maximizing the benefits and minimizing the adverse effects of drugs. Realistic mechanistic models are needed to understand and limit heterogeneity in drug responses. While pharmacokinetic models describe in detail a drug's absorption and metabolism, they generally do not account for individual variations in response to environmental influences, in addition to genetic variation. For instance, the human gut microbiota metabolizes drugs and is modulated by diet, and it exhibits significant variation among individuals. However, the influence of the gut microbiota on drug failure or drug side effects is under-researched. Here, we review recent advances in computational modeling approaches that could contribute to a better, mechanism-based understanding of drug-microbiota-diet interactions and their contribution to individual drug responses. By integrating systems biology and quantitative systems pharmacology with microbiology and nutrition, the conceptually and technologically demand for novel approaches could be met to enable the study of individual variability, thereby providing breakthrough support for progress in precision medicine.
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Affiliation(s)
- Ines Thiele
- University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Esch-sur-Alzette, Luxembourg
| | - Catherine M. Clancy
- University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Esch-sur-Alzette, Luxembourg
| | - Almut Heinken
- University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Esch-sur-Alzette, Luxembourg
| | - Ronan M.T. Fleming
- University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Esch-sur-Alzette, Luxembourg
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European regulatory perspective on pediatric physiologically based pharmacokinetic models. ACTA ACUST UNITED AC 2017. [DOI: 10.4155/ipk-2016-0025] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Physiologically based pharmacokinetic (PBPK) models offer a mechanistic understanding of the disposition of the drug in the body. When well informed and conducted, this may lead to more efficient clinical studies in the vulnerable pediatric population. A review of pediatric submissions to European regulatory authorities has shown a limited number of recent examples. The use of PBPK models to inform pediatric drug development is encouraged. It is, however, important to consider the confidence in the predictions. A qualification of the PBPK platform for the intended purpose should be performed, and a learn-and-confirm approach is recommended. Further research in this area is encouraged to inform important parameters, and to increase availability of pediatric data for model qualification.
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