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Chen W, Boras B, Sung T, Hu W, Spilker ME, D’Argenio DZ. A whole-body circulatory neutrophil model with application to predicting clinical neutropenia from in vitro studies. CPT Pharmacometrics Syst Pharmacol 2021; 10:671-683. [PMID: 33793091 PMCID: PMC8302245 DOI: 10.1002/psp4.12620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 02/16/2021] [Accepted: 03/03/2021] [Indexed: 11/23/2022] Open
Abstract
A circulatory model of granulopoiesis and its regulation is presented that includes neutrophil trafficking in the lungs, liver, spleen, bone marrow, lymph nodes, and blood. In each organ, neutrophils undergo transendothelial migration from vascular to interstitial space, clearance due to apoptosis, and recycling via the lymphatic flow. The model includes cell cycling of progenitor cells in the bone marrow, granulocyte colony-stimulating factor (G-CSF) kinetics and its neutrophil regulatory action, as well as neutrophil margination in the blood. From previously reported studies, 111 In-labeled neutrophil kinetic data in the blood and sampled organs were used to estimate the organ trafficking parameters in the model. The model was further developed and evaluated using absolute neutrophil count (ANC), band cell, and segmented neutrophil time course data from healthy volunteers following four dose levels of pegfilgrastim (r2 = 0.77-0.99), along with ANC time course responses following filgrastim (r2 = 0.96). The baseline values of various cell types in bone marrow and blood, as well as G-CSF concentration in the blood, predicted by the model are consistent with available literature reports. After incorporating the mechanism of action of both paclitaxel and carboplatin, as determined from an in vitro bone marrow studies, the model reliably predicted the observed ANC time course following paclitaxel plus carboplatin observed in a phase I trial of 46 patients (r2 = 0.70). The circulatory neutrophil model may provide a mechanistic framework for predicting multi-organ neutrophil homeostasis and dynamics in response to therapeutic agents that target neutrophil dynamics and trafficking in different organs.
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Affiliation(s)
- Wenbo Chen
- Department of Biomedical EngineeringUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Britton Boras
- Pfizer Worldwide Research, Development and MedicineSan DiegoCaliforniaUSA
| | - Tae Sung
- Pfizer Worldwide Research, Development and MedicineSan DiegoCaliforniaUSA
| | - Wenyue Hu
- Pfizer Worldwide Research, Development and MedicineSan DiegoCaliforniaUSA
| | - Mary E. Spilker
- Pfizer Worldwide Research, Development and MedicineSan DiegoCaliforniaUSA
| | - David Z. D’Argenio
- Department of Biomedical EngineeringUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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Ayyar VS, Jusko WJ. Transitioning from Basic toward Systems Pharmacodynamic Models: Lessons from Corticosteroids. Pharmacol Rev 2020; 72:414-438. [PMID: 32123034 DOI: 10.1124/pr.119.018101] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Technology in bioanalysis, -omics, and computation have evolved over the past half century to allow for comprehensive assessments of the molecular to whole body pharmacology of diverse corticosteroids. Such studies have advanced pharmacokinetic and pharmacodynamic (PK/PD) concepts and models that often generalize across various classes of drugs. These models encompass the "pillars" of pharmacology, namely PK and target drug exposure, the mass-law interactions of drugs with receptors/targets, and the consequent turnover and homeostatic control of genes, biomarkers, physiologic responses, and disease symptoms. Pharmacokinetic methodology utilizes noncompartmental, compartmental, reversible, physiologic [full physiologically based pharmacokinetic (PBPK) and minimal PBPK], and target-mediated drug disposition models using a growing array of pharmacometric considerations and software. Basic PK/PD models have emerged (simple direct, biophase, slow receptor binding, indirect response, irreversible, turnover with inactivation, and transduction models) that place emphasis on parsimony, are mechanistic in nature, and serve as highly useful "top-down" methods of quantitating the actions of diverse drugs. These are often components of more complex quantitative systems pharmacology (QSP) models that explain the array of responses to various drugs, including corticosteroids. Progressively deeper mechanistic appreciation of PBPK, drug-target interactions, and systems physiology from the molecular (genomic, proteomic, metabolomic) to cellular to whole body levels provides the foundation for enhanced PK/PD to comprehensive QSP models. Our research based on cell, animal, clinical, and theoretical studies with corticosteroids have provided ideas and quantitative methods that have broadly advanced the fields of PK/PD and QSP modeling and illustrates the transition toward a global, systems understanding of actions of diverse drugs. SIGNIFICANCE STATEMENT: Over the past half century, pharmacokinetics (PK) and pharmacokinetics/pharmacodynamics (PK/PD) have evolved to provide an array of mechanism-based models that help quantitate the disposition and actions of most drugs. We describe how many basic PK and PK/PD model components were identified and often applied to the diverse properties of corticosteroids (CS). The CS have complications in disposition and a wide array of simple receptor-to complex gene-mediated actions in multiple organs. Continued assessments of such complexities have offered opportunities to develop models ranging from simple PK to enhanced PK/PD to quantitative systems pharmacology (QSP) that help explain therapeutic and adverse CS effects. Concurrent development of state-of-the-art PK, PK/PD, and QSP models are described alongside experimental studies that revealed diverse CS actions.
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Affiliation(s)
- Vivaswath S Ayyar
- Department of Pharmaceutical Sciences University at Buffalo, School of Pharmacy and Pharmaceutical Sciences, Buffalo, New York
| | - William J Jusko
- Department of Pharmaceutical Sciences University at Buffalo, School of Pharmacy and Pharmaceutical Sciences, Buffalo, New York
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Michalaki LI, Goussis DA. Asymptotic analysis of a TMDD model: when a reaction contributes to the destruction of its product. J Math Biol 2018; 77:821-855. [DOI: 10.1007/s00285-018-1234-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Revised: 01/28/2018] [Indexed: 02/04/2023]
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Delayed logistic indirect response models: realization of oscillating behavior. J Pharmacokinet Pharmacodyn 2018; 45:49-58. [PMID: 29313194 DOI: 10.1007/s10928-017-9563-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Accepted: 12/18/2017] [Indexed: 12/18/2022]
Abstract
Indirect response (IDR) models are probably the most frequently applied tools relating the effect of a signal to a baseline response. A response modeled by such a classical IDR model will always return monotonously to its baseline after drug administration. We extend IDR models with a delay process, i.e. a retarded response state, that leads to oscillating response behavior. First, IDR models with a first-order production and second-order loss term based on the famous logistic equation are constructed. Second, a delay process similar to the delayed logistic equation is included. Relations of the classical IDR model with our extended IDR model concerning response and model parameters are revealed. Simulations of typical response profiles are presented and data fitting of a model for leptin and cholesterol dynamics after administration of methylprednisolone is performed. The influence of the delay parameter on the other model parameters is discussed.
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Shoji S, Suzuki A, Conrado DJ, Peterson MC, Hey-Hadavi J, McCabe D, Rojo R, Tammara BK. Dissociated Agonist of Glucocorticoid Receptor or Prednisone for Active Rheumatoid Arthritis: Effects on P1NP and Osteocalcin Pharmacodynamics. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2017; 6:439-448. [PMID: 28556506 PMCID: PMC5529777 DOI: 10.1002/psp4.12201] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2016] [Revised: 04/05/2017] [Accepted: 04/10/2017] [Indexed: 11/29/2022]
Abstract
Fosdagrocorat (PF‐04171327), a dissociated agonist of the glucocorticoid receptor, has potent anti‐inflammatory activity in patients with rheumatoid arthritis with reduced adverse effects on bone health. To identify fosdagrocorat doses with bone formation marker changes similar to prednisone 5 mg, we characterized treatment‐related changes in amino‐terminal propeptide of type I collagen (P1NP) and osteocalcin (OC) with fosdagrocorat (1, 5, 10, or 15 mg) and prednisone (5 or 10 mg) in a phase II randomized trial (N = 323). The time course of markers utilized a mixed‐effects longitudinal kinetic‐pharmacodynamic model. Median predicted changes from baseline at week 8 with fosdagrocorat 5, 10, and 15 mg were −18, −22, and −22% (P1NP), and −7, −13, and −17% (OC), respectively. Changes with prednisone 5 and 10 mg were −15% and −18% (P1NP) and −10% and −17% (OC). The probability of fosdagrocorat doses up to 15 mg being noninferior to prednisone 5 mg for P1NP and OC changes was >90%.
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Affiliation(s)
- S Shoji
- Pfizer Japan Inc, Tokyo, Japan
| | | | | | | | | | - D McCabe
- Pfizer Inc, New York, New York, USA
| | - R Rojo
- Pfizer Inc, Groton, Connecticut, USA
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Cirincione B, LaCreta F, Sager P, Mager DE. Model-Based Evaluation of Exenatide Effects on the QT Interval in Healthy Subjects Following Continuous IV Infusion. J Clin Pharmacol 2017; 57:956-965. [PMID: 28543393 PMCID: PMC5518197 DOI: 10.1002/jcph.882] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Accepted: 01/19/2017] [Indexed: 12/20/2022]
Abstract
Investigation of the cardiovascular proarrhythmic potential of a new chemical entity is now an integral part of drug development. Studies suggest that meals and glycemic changes can influence QT intervals, and a semimechanistic model has been developed that incorporates the effects of changes in glucose concentrations on heart rate (HR) and QT intervals. This analysis aimed to adapt the glucose-HR-QT model to incorporate the effects of exenatide, a drug that reduces postprandial increases in glucose concentrations. The final model includes stimulatory drug effects on glucose elimination and HR perturbations. The targeted and constant exenatide plasma concentrations (>200 pg/mL), via intravenous infusions at multiple dose levels, resulted in significant inhibition of glucose concentrations. The exenatide concentration associated with 50% of the stimulation of HR production was 584 pg/mL. After accounting for exenatide effects on glucose and HR, no additional drug effects were required to explain observed changes in the QT interval. Resulting glucose, HR, and QT profiles at all exenatide concentrations were adequately described. For therapeutic agents that alter glycemic conditions, particularly those that alter postprandial glucose, the QT interval cannot be directly compared to that with placebo without first accounting for confounding factors (eg, glucose) either through mathematical modeling or careful consideration of mealtime placement in the study design.
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Affiliation(s)
- Brenda Cirincione
- Research and Development, Bristol-Myers Squibb, Princeton, NJ, USA.,Department of Pharmaceutical Sciences, University at Buffalo, SUNY, Buffalo, NY, USA
| | - Frank LaCreta
- Research and Development, Bristol-Myers Squibb, Princeton, NJ, USA
| | - Philip Sager
- Sager Consulting Experts and Stanford University School of Medicine, San Francisco, CA, USA
| | - Donald E Mager
- Department of Pharmaceutical Sciences, University at Buffalo, SUNY, Buffalo, NY, USA
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Wilbaux M, Wölnerhanssen BK, Meyer-Gerspach AC, Beglinger C, Pfister M. Characterizing the dynamic interaction among gastric emptying, glucose absorption, and glycemic control in nondiabetic obese adults. Am J Physiol Regul Integr Comp Physiol 2016; 312:R314-R323. [PMID: 27974316 DOI: 10.1152/ajpregu.00369.2016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Revised: 12/12/2016] [Accepted: 12/12/2016] [Indexed: 01/21/2023]
Abstract
The effects of altered gastric emptying on glucose absorption and kinetics are not well understood in nondiabetic obese adults. The aim of this work was to develop a physiology-based model that can characterize and compare interactions among gastric emptying, glucose absorption, and glycemic control in nondiabetic obese and lean healthy adults. Dynamic glucose, insulin, and gastric emptying (measured with breath test) data from 12 nondiabetic obese and 12 lean healthy adults were available until 180 min after an oral glucose tolerance test (OGTT) with 10, 25, and 75 g of glucose. A physiology-based model was developed to characterize glucose kinetics applying nonlinear mixed-effects modeling with NONMEM7.3. Glucose kinetics after OGTT was described by a one-compartment model with an effect compartment to describe delayed insulin effects on glucose clearance. After the interactions between individual gastric emptying and glucose absorption profiles were accounted for, the glucose absorption rate was found to be similar in nondiabetic obese and lean controls. Baseline glucose concentration was estimated to be only marginally higher in nondiabetic obese subjects (4.9 vs. 5.2 mmol/l), whereas insulin-dependent glucose clearance in nondiabetic obese subjects was found to be cut in half compared with lean controls (0.052 vs. 0.029 l/min) and the insulin concentration associated with 50% of insulin-dependent glucose elimination rate was approximately twofold higher in nondiabetic obese subjects compared with lean controls (7.1 vs. 15.3 μU/ml). Physiology-based models can characterize and compare the dynamic interaction among gastric emptying, glucose absorption and glycemic control in populations of interest such as lean healthy and nondiabetic obese adults.
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Affiliation(s)
- Mélanie Wilbaux
- Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland;
| | - Bettina K Wölnerhanssen
- Department of Biomedicine, Division of Gastroenterology and Hepatology, University Hospital of Basel, Basel, Switzerland; and
| | - Anne Christin Meyer-Gerspach
- Department of Biomedicine, Division of Gastroenterology and Hepatology, University Hospital of Basel, Basel, Switzerland; and
| | - Christoph Beglinger
- Department of Biomedicine, Division of Gastroenterology and Hepatology, University Hospital of Basel, Basel, Switzerland; and
| | - Marc Pfister
- Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland.,Quantitative Solutions LP, Menlo Park, Calfornia
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