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Kulesh V, Vasyutin I, Volkova A, Peskov K, Kimko H, Sokolov V, Alluri R. A tutorial for model-based evaluation and translation of cardiovascular safety in preclinical trials. CPT Pharmacometrics Syst Pharmacol 2024; 13:5-22. [PMID: 37950388 PMCID: PMC10787214 DOI: 10.1002/psp4.13082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/25/2023] [Accepted: 10/31/2023] [Indexed: 11/12/2023] Open
Abstract
Assessment of drug-induced effects on the cardiovascular (CV) system remains a critical component of the drug discovery process enabling refinement of the therapeutic index. Predicting potential drug-related unintended CV effects in the preclinical stage is necessary for first-in-human dose selection and preclusion of adverse CV effects in the clinical stage. According to the current guidelines for small molecules, nonclinical CV safety assessment conducted via telemetry analyses should be included in the safety pharmacology core battery studies. However, the manual for quantitative evaluation of the CV safety signals in animals is available only for electrocardiogram parameters (i.e., QT interval assessment), not for hemodynamic parameters (i.e., heart rate, blood pressure, etc.). Various model-based approaches, including empirical pharmacokinetic-toxicodynamic analyses and systems pharmacology modeling could be used in the framework of telemetry data evaluation. In this tutorial, we provide a comprehensive workflow for the analysis of nonclinical CV safety on hemodynamic parameters with a sequential approach, highlight the challenges associated with the data, and propose respective solutions, complemented with a reproducible example. The work is aimed at helping researchers conduct model-based analyses of the CV safety in animals with subsequent translation of the effect to humans seamlessly and efficiently.
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Affiliation(s)
- Victoria Kulesh
- Modeling & Simulation Decisions FZ‐LLCDubaiUnited Arab Emirates
- Research Center of Model‐Informed Drug DevelopmentSechenov First Moscow State Medical UniversityMoscowRussia
| | - Igor Vasyutin
- Modeling & Simulation Decisions FZ‐LLCDubaiUnited Arab Emirates
| | - Alina Volkova
- Modeling & Simulation Decisions FZ‐LLCDubaiUnited Arab Emirates
- Sirius University of Science and TechnologySiriusRussia
| | - Kirill Peskov
- Modeling & Simulation Decisions FZ‐LLCDubaiUnited Arab Emirates
- Research Center of Model‐Informed Drug DevelopmentSechenov First Moscow State Medical UniversityMoscowRussia
- Sirius University of Science and TechnologySiriusRussia
| | - Holly Kimko
- CPQP, CPSS, BioPharmaceuticals R&DAstraZenecaGaithersburgMarylandUSA
| | - Victor Sokolov
- Modeling & Simulation Decisions FZ‐LLCDubaiUnited Arab Emirates
- Sirius University of Science and TechnologySiriusRussia
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Tosca EM, Bartolucci R, Magni P, Poggesi I. Modeling approaches for reducing safety-related attrition in drug discovery and development: a review on myelotoxicity, immunotoxicity, cardiovascular toxicity, and liver toxicity. Expert Opin Drug Discov 2021; 16:1365-1390. [PMID: 34181496 DOI: 10.1080/17460441.2021.1931114] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Introduction:Safety and tolerability is a critical area where improvements are needed to decrease the attrition rates during development of new drug candidates. Modeling approaches, when smartly implemented, can contribute to this aim.Areas covered:The focus of this review was on modeling approaches applied to four kinds of drug-induced toxicities: hematological, immunological, cardiovascular (CV) and liver toxicity. Papers, mainly published in the last 10 years, reporting models in three main methodological categories - computational models (e.g., quantitative structure-property relationships, machine learning approaches, neural networks, etc.), pharmacokinetic-pharmacodynamic (PK-PD) models, and quantitative system pharmacology (QSP) models - have been considered.Expert opinion:The picture observed in the four examined toxicity areas appears heterogeneous. Computational models are typically used in all areas as screening tools in the early stages of development for hematological, cardiovascular and liver toxicity, with accuracies in the range of 70-90%. A limited number of computational models, based on the analysis of drug protein sequence, was instead proposed for immunotoxicity. In the later stages of development, toxicities are quantitatively predicted with reasonably good accuracy using either semi-mechanistic PK-PD models (hematological and cardiovascular toxicity), or fully exploited QSP models (immuno-toxicity and liver toxicity).
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Affiliation(s)
- Elena M Tosca
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Roberta Bartolucci
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Paolo Magni
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Italo Poggesi
- Clinical Pharmacology & Pharmacometrics, Janssen Research & Development, Beerse, Belgium
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Wong H, Bohnert T, Damian-Iordache V, Gibson C, Hsu CP, Krishnatry AS, Liederer BM, Lin J, Lu Q, Mettetal JT, Mudra DR, Nijsen MJ, Schroeder P, Schuck E, Suryawanshi S, Trapa P, Tsai A, Wang H, Wu F. Translational pharmacokinetic-pharmacodynamic analysis in the pharmaceutical industry: an IQ Consortium PK-PD Discussion Group perspective. Drug Discov Today 2017; 22:1447-1459. [DOI: 10.1016/j.drudis.2017.04.015] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Revised: 04/03/2017] [Accepted: 04/25/2017] [Indexed: 02/06/2023]
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France NP, Della Pasqua O. The role of concentration-effect relationships in the assessment of QTc interval prolongation. Br J Clin Pharmacol 2015; 79:117-31. [PMID: 24938719 DOI: 10.1111/bcp.12443] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Accepted: 06/10/2014] [Indexed: 01/27/2023] Open
Abstract
Population pharmacokinetic and pharmacokinetic-pharmacodynamic (PKPD) modelling has been widely used in clinical research. Yet, its application in the evaluation of cardiovascular safety remains limited, particularly in the evaluation of pro-arrhythmic effects. Here we discuss the advantages of disadvantages of population PKPD modelling and simulation, a paradigm built around the knowledge of the concentration-effect relationship as the basis for decision making in drug development and its utility as a guide to drug safety. A wide-ranging review of the literature was performed on the experimental protocols currently used to characterize the potential for QT interval prolongation, both pre-clinically and clinically. Focus was given to the role of modelling and simulation for design optimization and subsequent analysis and interpretation of the data, discriminating drug from system specific properties. Cardiovascular safety remains one of the major sources of attrition in drug development with stringent regulatory requirements. However, despite the myriad of tests, data are not integrated systematically to ensure accurate translation of the observed drug effects in clinically relevant conditions. The thorough QT study addresses a critical regulatory question but does not necessarily reflect knowledge of the underlying pharmacology and has limitations in its ability to address fundamental clinical questions. It is also prone to issues of multiplicity. Population approaches offer a paradigm for the evaluation of drug safety built around the knowledge of the concentration-effect relationship. It enables quantitative assessment of the probability of QTc interval prolongation in patients, providing better guidance to regulatory labelling and understanding of benefit/risk in specific populations.
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Benson N. Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is. DRUG DISCOVERY TODAY. TECHNOLOGIES 2015; 15:41-8. [PMID: 26464089 DOI: 10.1016/j.ddtec.2015.07.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2014] [Revised: 06/30/2015] [Accepted: 07/14/2015] [Indexed: 01/10/2023]
Abstract
Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way.
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Affiliation(s)
- Neil Benson
- Xenologiq Ltd., Unit 43, Canterbury Innovation Centre, University Road, Canterbury CT2 7FG, UK.
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Collins TA, Bergenholm L, Abdulla T, Yates J, Evans N, Chappell MJ, Mettetal JT. Modeling and Simulation Approaches for Cardiovascular Function and Their Role in Safety Assessment. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2015. [PMID: 26225237 PMCID: PMC4394617 DOI: 10.1002/psp4.18] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Systems pharmacology modeling and pharmacokinetic-pharmacodynamic (PK/PD) analysis of drug-induced effects on cardiovascular (CV) function plays a crucial role in understanding the safety risk of new drugs. The aim of this review is to outline the current modeling and simulation (M&S) approaches to describe and translate drug-induced CV effects, with an emphasis on how this impacts drug safety assessment. Current limitations are highlighted and recommendations are made for future effort in this vital area of drug research.
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Affiliation(s)
- T A Collins
- Drug Safety and Metabolism, AstraZeneca Alderley Park, Macclesfield, UK
| | | | - T Abdulla
- School of Engineering, University of Warwick UK
| | - Jwt Yates
- Oncology, AstraZeneca Alderley Park, Macclesfield, UK
| | - N Evans
- School of Engineering, University of Warwick UK
| | | | - J T Mettetal
- Drug Safety and Metabolism, AstraZeneca Waltham, Massachusetts, USA
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Gotta V, Cools F, van Ammel K, Gallacher DJ, Visser SAG, Sannajust F, Morissette P, Danhof M, van der Graaf PH. Sensitivity of pharmacokinetic-pharmacodynamic analysis for detecting small magnitudes of QTc prolongation in preclinical safety testing. J Pharmacol Toxicol Methods 2014; 72:1-10. [PMID: 25556117 DOI: 10.1016/j.vascn.2014.12.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2014] [Revised: 12/17/2014] [Accepted: 12/22/2014] [Indexed: 10/24/2022]
Abstract
INTRODUCTION Preclinical concentration-effect (pharmacokinetic-pharmacodynamic, PKPD) modeling has successfully quantified QT effects of several drugs known for significant QT prolongation. This study investigated its sensitivity for detecting small magnitudes of QT-prolongation in a typical preclinical cardiovascular (CV) safety study in the conscious telemetered dog (crossover study in 4-8 animals receiving a vehicle and three dose levels). Results were compared with conventional statistical analysis (analysis of covariance, ANCOVA). METHODS A PKPD model predicting individual QTc was first developed from vehicle arms of 28 typical CV studies and one positive control study (sotalol). The model quantified between-animal, inter-occasion and within-animal variability and described QTc over 24h as a function of circadian variation and drug concentration. This "true" model was used to repeatedly (n = 500) simulate studies with typical drug-induced QTc prolongation (∆QTc) of 1 to 12 ms at high-dose peak concentrations. Simulated studies were re-analyzed by both PKPD analysis (with varying complexity) and ANCOVA. Sensitivity (power) was calculated as the percentage of studies in which a significant (α = 0.05) drug effect was found. One simulation scenario did not include a concentration-effect relationship and served to investigate false-positive rates. Exposure-effect relationships were derived from both PKPD analysis (linear concentration-effect) and ANCOVA (linear trend test for dose) and compared. RESULTS PKPD analysis/ANCOVA had a sensitivity of 80% to detect the effects of 7/13 ms (n = 4), 5/10 ms (n = 6) and 4.5/8 ms (n = 8), respectively. The false-positive rate was much higher using ANCOVA (40%) compared to PKPD analysis (1%). Typical drug effects were more precisely predicted using estimated concentration-effect slopes (± 1.5-2.8 ms) than dose-effect slopes (± 3.3-3.7 ms). DISCUSSION Preclinical PKPD analysis can increase the confidence in the quantification of small QTc effects and potentially allow reducing the number of animals while maintaining the required study sensitivity. This underscores the value of PKPD modeling in preclinical safety testing.
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Affiliation(s)
- Verena Gotta
- Systems Pharmacology, Leiden Academic Center of Drug Research (LACDR), Leiden University, Leiden, The Netherlands.
| | - Frank Cools
- Global Safety Pharmacology, Janssen Research & Development, Janssen Pharmaceutica NV, Beerse, Belgium.
| | - Karel van Ammel
- Global Safety Pharmacology, Janssen Research & Development, Janssen Pharmaceutica NV, Beerse, Belgium.
| | - David J Gallacher
- Global Safety Pharmacology, Janssen Research & Development, Janssen Pharmaceutica NV, Beerse, Belgium.
| | - Sandra A G Visser
- Quantitative Pharmacology and Pharmacometrics, Merck Research Laboratories, Merck & Co., Inc., Upper Gwynedd, PA, USA.
| | - Frederick Sannajust
- SALAR, Safety and Exploratory Pharmacology Department, Merck Research Laboratories, Merck & Co., Inc., West Point, PA, USA.
| | - Pierre Morissette
- SALAR, Safety and Exploratory Pharmacology Department, Merck Research Laboratories, Merck & Co., Inc., West Point, PA, USA.
| | - Meindert Danhof
- Systems Pharmacology, Leiden Academic Center of Drug Research (LACDR), Leiden University, Leiden, The Netherlands.
| | - Piet H van der Graaf
- Systems Pharmacology, Leiden Academic Center of Drug Research (LACDR), Leiden University, Leiden, The Netherlands.
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Caruso A, Frances N, Meille C, Greiter-Wilke A, Hillebrecht A, Lavé T. Translational PK/PD modeling for cardiovascular safety assessment of drug candidates: Methods and examples in drug development. J Pharmacol Toxicol Methods 2014; 70:73-85. [DOI: 10.1016/j.vascn.2014.05.004] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2013] [Revised: 04/12/2014] [Accepted: 05/15/2014] [Indexed: 12/20/2022]
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Chain ASY, Sturkenboom MCJM, Danhof M, Della Pasqua OE. Establishing in vitro to clinical correlations in the evaluation of cardiovascular safety pharmacology. DRUG DISCOVERY TODAY. TECHNOLOGIES 2013; 10:e373-e383. [PMID: 24050134 DOI: 10.1016/j.ddtec.2012.07.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Preclinical studies are vital in establishing the efficacy and safety of a new chemical entity (NCE) in humans. To deliver meaningful information, experiments have to be well defined and provide outcome that is relevant and translatable to humans. This review briefly surveys the various preclinical experiments that are frequently conducted to assess drug effects on cardiac conductivity in early drug development. We examine the different approaches used to establish correlations between non-clinical and clinical settings and discuss their value in the evaluation of cardiovascular risk.
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Davies MR, Mistry HB, Hussein L, Pollard CE, Valentin JP, Swinton J, Abi-Gerges N. An in silico canine cardiac midmyocardial action potential duration model as a tool for early drug safety assessment. Am J Physiol Heart Circ Physiol 2012; 302:H1466-80. [DOI: 10.1152/ajpheart.00808.2011] [Citation(s) in RCA: 63] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Cell lines expressing ion channels (IC) and the advent of plate-based electrophysiology device have enabled a molecular understanding of the action potential (AP) as a means of early QT assessment. We sought to develop an in silico AP (isAP) model that provides an assessment of the effect of a compound on the myocyte AP duration (APD) using concentration-effect curve data from a panel of five ICs (hNav1.5, hCav1.2, hKv4.3/hKChIP2.2, hKv7.1/hminK, hKv11.1). A test set of 53 compounds was selected to cover a range of selective and mixed IC modulators that were tested for their effects on optically measured APD. A threshold of >10% change in APD at 90% repolarization (APD90) was used to signify an effect at the top test concentration. To capture the variations observed in left ventricular midmyocardial myocyte APD data from 19 different dogs, the isAP model was calibrated to produce an ensemble of 19 model variants that could capture the shape and form of the APs and also quantitatively replicate dofetilide- and diltiazem-induced APD90 changes. Provided with IC panel data only, the isAP model was then used, blinded, to predict APD90 changes greater than 10%. At a simulated concentration of 30 μM and based on a criterion that six of the variants had to agree, isAP prediction was scored as showing greater than 80% predictivity of compound activity. Thus, early in drug discovery, the isAP model allows integrating separate IC data and is amenable to the throughput required for use as a virtual screen.
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Affiliation(s)
| | | | - L. Hussein
- Safety Pharmacology, Safety Assessment United Kingdom, AstraZeneca R&D, Macclesfield, United Kingdom
| | - C. E. Pollard
- Safety Pharmacology, Safety Assessment United Kingdom, AstraZeneca R&D, Macclesfield, United Kingdom
| | - J.-P. Valentin
- Safety Pharmacology, Safety Assessment United Kingdom, AstraZeneca R&D, Macclesfield, United Kingdom
| | - J. Swinton
- Computational Biology, Discovery Sciences and
| | - N. Abi-Gerges
- Safety Pharmacology, Safety Assessment United Kingdom, AstraZeneca R&D, Macclesfield, United Kingdom
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van der Graaf PH, Benson N. Systems Pharmacology: Bridging Systems Biology and Pharmacokinetics-Pharmacodynamics (PKPD) in Drug Discovery and Development. Pharm Res 2011; 28:1460-4. [DOI: 10.1007/s11095-011-0467-9] [Citation(s) in RCA: 194] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2011] [Accepted: 04/28/2011] [Indexed: 11/30/2022]
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Current awareness: Pharmacoepidemiology and drug safety. Pharmacoepidemiol Drug Saf 2010. [DOI: 10.1002/pds.1854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Pharmacokinetic-pharmacodynamic modeling of alpha interferon response induced by a Toll-like 7 receptor agonist in mice. Antimicrob Agents Chemother 2009; 54:1179-85. [PMID: 20028817 DOI: 10.1128/aac.00551-09] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Recombinant alpha interferon (IFN-alpha) is used in the treatment of hepatitis C virus (HCV)-infected patients but is not optimal in terms of efficacy or tolerability. Toll-like 7 receptor (TLR-7) agonists stimulate the innate immune system to produce, among other cytokines, IFN-alpha and are being evaluated as alternative drugs to treat HCV infection. This paper describes the application of pharmacokinetic-pharmacodynamic (PK-PD) modeling to understanding the behavior of a TLR-7 agonist [9-benzyl-8-hydroxy-2-(2-methoxyethoxy) adenine (BHMA)] in mice, using IFN-alpha as a biomarker. This is the first report of such a PK-PD model, and the conclusions may be of utility in the clinical development of TLR-7 agonists for HCV infection.
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