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Original Paper

Modeling of dose–response–time data: four examples of estimating the turnover parameters and generating kinetic functions from response profiles

Johan Gabrielsson

Corresponding Author

E-mail address: [email protected]

PK/PD Section, Preclinical Development, AstraZeneca R&D Södertälje, S‐151 85 Södertälje, Sweden

PK/PD Section, Preclinical Development, AstraZeneca R&D Södertälje, S‐151 85 Södertälje, Sweden
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William J. Jusko

Department of Pharmaceutics, School of Pharmacy, 565 Hochstetter Hall, Buffalo, NY 14260, USA

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Liisi Alari

General Pharmacology, Preclinical Development, AstraZeneca R&D Södertälje, S‐151 85 Södertälje, Sweden

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First published: 01 November 2000
Cited by: 36

Abstract

The most common approach to in vivo pharmacokinetic and pharmacodynamic modeling involves sequential analysis of the plasma concentration versus time and then response versus time data, such that the plasma kinetic model provides an independent function, driving the dynamics. However, response versus time data, even in the absence of measured drug concentrations, inherently contain useful information about the turnover characteristics of response (turnover rate, half‐life of response), the drug's biophase kinetics (F, half‐life) as well as the pharmacodynamic characteristics (potency, intrinsic activity). Previous analyses have assumed linear kinetics, linear dynamics, no time lag between kinetics and dynamics (single‐valued response), and time constant parameters. However, this report demonstrates that the drug effect can be indirect (antinociception, cortisol/adrenocorticotropin (ACTH), body temperature), display nonlinear kinetics, display back mechanisms (nonstationarity, cortisol/ACTH) and exhibit hysteresis with the drug levels in the biophase (antinociception, body temperature). It is also demonstrated that crucial determinants of the success of modeling dose–response–time data are the dose selection, multiple dosing, and to some extent different input rates and routes. This report exemplifies the possibility of assigning kinetic forcing functions in pharmacodynamic modeling in both preclinical and clinical studies for the purpose of characterizing (discrimination between turnover and drug‐specific parameters) response data and optimizing subsequent clinical protocols, and for identification of inter‐individual differences. Copyright © 2000 John Wiley & Sons, Ltd.

Number of times cited according to CrossRef: 36

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  • , Modelling the dose–response relationship: the fair share of pharmacokinetic and pharmacodynamic information, British Journal of Clinical Pharmacology, 83, 6, (1240-1251), (2017).
  • , Nonclassical Pharmacodynamics, Modeling in Biopharmaceutics, Pharmacokinetics and Pharmacodynamics, 10.1007/978-3-319-27598-7_13, (361-403), (2016).
  • , Dose–response-time modelling: Second-generation turnover model with integral back control, European Journal of Pharmaceutical Sciences, 81, (189), (2016).
  • , Analysis of clinical trials with biologics using dose–time‐response models, Statistics in Medicine, 34, 22, (3017-3028), (2015).
  • , Challenges in Pharmacology Modelling, Journal of Dynamics and Differential Equations, 27, 3-4, (941), (2015).
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  • , Optimal design of clinical trials with biologics using dose‐time‐response models, Statistics in Medicine, 33, 30, (5249-5264), (2014).
  • , Dose–response–time data analysis involving nonlinear dynamics, back and delay, European Journal of Pharmaceutical Sciences, 59, (36), (2014).
  • , Romiplostim dose–response in patients with myelodysplastic syndromes, British Journal of Clinical Pharmacology, 75, 6, (1445-1454), (2013).
  • , Use of Pharmacokinetic Data Below Lower Limit of Quantitation Values, Pharmaceutical Research, 29, 9, (2628), (2012).
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  • , Romiplostim Dose Response in Patients With Immune Thrombocytopenia, The Journal of Clinical Pharmacology, 52, 10, (1540), (2012).
  • , Modeling and Simulation in the Development of Cardiovascular Agents, Clinical Trial Simulations, 10.1007/978-1-4419-7415-0_10, (199-226), (2010).
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  • , Early integration of pharmacokinetic and dynamic reasoning is essential for optimal development of lead compounds: strategic considerations, Drug Discovery Today, 14, 7-8, (358), (2009).
  • , Pharmacokinetic and Pharmacodynamic Modeling of a Monoclonal Antibody Antagonist of Glucagon Receptor in Male ob/ob Mice, The AAPS Journal, 10.1208/s12248-009-9150-z, 11, 4, (700-709), (2009).
  • , PHARMACODYNAMICS, Pharmacology and Therapeutics, 10.1016/B978-1-4160-3291-5.50018-4, (203-218), (2009).
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  • , Evaluation of drugs in pediatrics using K‐PD models: perspectives, Fundamental & Clinical Pharmacology, 22, 6, (589-594), (2008).
  • , Pharmacokinetic‐pharmacodynamic modelling of S(−)‐atenolol in rats: reduction of isoprenaline‐induced tachycardia as a continuous pharmacodynamic endpoint, British Journal of Pharmacology, 151, 3, (356-366), (2009).
  • , Modelling Response Time Profiles in the Absence of Drug Concentrations: Definition and Performance Evaluation of the K–PD Model, Journal of Pharmacokinetics and Pharmacodynamics, 10.1007/s10928-006-9035-z, 34, 1, (57-85), (2006).
  • , Integrated??Pharmacokinetics??and Pharmacodynamics in??Drug??Development, Clinical Pharmacokinetics, 10.2165/00003088-200746090-00001, 46, 9, (713-737), (2007).
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