Translational pharmacokinetic-pharmacodynamic analysis in the pharmaceutical industry: an IQ Consortium PK-PD Discussion Group perspective

Wong, Harvey; Bohnert, Tonika; Damian-Iordache, Valeriu; Gibson, Christopher R; Hsu, Cheng‐Pang; Krishnatry, Anu Shilpa; Liederer, Bianca M.; Jing, Lin; Lu, Qiang; Mettetal, Jerome; Mudra, Daniel R.; Nijsen, Marjoleen; Schroeder, Patricia; Schuck, Edgar; Suryawanshi, Satyendra; Trapa, Patrick; Tsai, Alice; Wang, Haiqing; Wu, Fan

doi:10.1016/j.drudis.2017.04.015

Cited by 20 publications

(23 citation statements)

References 78 publications

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“…There is consensus among the pharmaceutical industry that improved understanding of exposure-response relationships at an early stage in the drug hunting process will be important to inform lead optimization strategies and reduce attrition rates in the clinic (1,2). A retrospective analysis of Phase II trial data highlighted the importance of pharmacokinetic (PK) and pharmacodynamic (PD) principles underlying the "three pillars of survival" (3).…”

Section: Introductionmentioning

confidence: 99%

Application of Pharmacokinetic-Pharmacodynamic Modeling to Inform Translation of In Vitro NaV1.7 Inhibition to In Vivo Pharmacological Response in Non-human Primate

Ballard¹,

Pall

Vardigan

et al. 2020

Pharm Res

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Purpose This work describes a staged approach to the application of pharmacokinetic-pharmacodynamic (PK-PD) modeling in the voltage-gated sodium ion channel (NaV1.7) inhibitor drug discovery effort to address strategic questions regarding in vitro to in vivo translation of target modulation. Methods PK-PD analysis was applied to data from a functional magnetic resonance imaging (fMRI) technique to non-invasively measure treatment mediated inhibition of olfaction signaling in non-human primates (NHPs). Initial exposure-response was evaluated using single time point data pooled across 27 compounds to inform on in vitro to in vivo correlation (IVIVC). More robust effect compartment PK-PD modeling was conducted for a subset of 10 compounds with additional PD and PK data to characterize hysteresis. Results The pooled compound exposure-response facilitated an early exploration of IVIVC with a limited dataset for each individual compound, and it suggested a 2.4-fold in vitro to in vivo scaling factor for the NaV1.7 target. Accounting for hysteresis with an effect compartment PK-PD model as compounds advanced towards preclinical development provided a more robust determination of in vivo potency values, which resulted in a statistically significant positive IVIVC with a slope of 1.057 ± 0.210, R-squared of 0.7831, and p value of 0.006. Subsequent simulations with the PK-PD model informed the design of anti-nociception efficacy studies in NHPs. Conclusions A staged approach to PK-PD modeling and simulation enabled integration of in vitro NaV1.7 potency, plasma protein binding, and pharmacokinetics to describe the exposure-response profile and inform future study design as the NaV1.7 inhibitor effort progressed through drug discovery.

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Section: Introductionmentioning

confidence: 99%

Application of Pharmacokinetic-Pharmacodynamic Modeling to Inform Translation of In Vitro NaV1.7 Inhibition to In Vivo Pharmacological Response in Non-human Primate

Ballard¹,

Pall

Vardigan

et al. 2020

Pharm Res

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“…The complex CNS biology, in combination with the lack of suitable animal models and clinically relevant biomarkers in these models, results in the less frequent use of translational PK/PD in neuroscience. 16,17 Noninvasive imaging techniques, such as PET, can generate useful and objective data on CNS drug effects in both preclinical species and human. It is thereby considered an ideal translational tool.…”

Section: Discussionmentioning

confidence: 99%

Translational Model‐Informed Dose Selection for a Human Positron Emission Tomography Imaging Study of JNJ‐54175446, a P2X7 Receptor Antagonist

Miao

Ravenstijn

et al. 2019

Clinical Translational Sci

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Positron emission tomography (PET) provides useful information in target engagement or receptor occupancy in the brain for central nervous system (CNS) drug development, however, dose selection for human PET studies is challenging and largely empirical. Here, we describe a translational pharmacokinetic/pharmacodynamic (PK/PD) modeling work to inform dose selection for a human PET study of JNJ‐54175446, a CNS‐penetrating P2X7 receptor antagonist. Models were developed using data on monkey brain occupancy and plasma drug exposures from a monkey PET study and early human clinical studies that provided data on drug exposures and human ex vivo‐stimulated peripheral interleukin (IL)‐1β release. The observed plasma PK of JNJ‐54175446 in human was adequately described by a one‐compartment model with parallel zero‐order and first‐order absorption and first‐order elimination. An exposure‐occupancy model was extrapolated from monkey to human assuming a similar unbound potency (all other model parameters remained unchanged). This model was then used to simulate human brain occupancy to guide human PET study dose selection, together with the human population PK model. The corroboration of model predicted occupancy by the observed occupancy data from the human PET study supports the use of a monkey as a predictive model for human PET target engagement. Potency estimate for brain occupancy was generally comparable to that for the suppression of the provoked peripheral IL‐1β release ex vivo, indicating that blood IL‐1β release may be used as a surrogate of central occupancy for JNJ‐54175446. Translational PK/PD modeling approach could be used for selecting optimal doses for human PET and other clinical studies.

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“…Through years of implementation in drug development, PKPD modeling has demonstrated tremendous value in elucidating the relationship between the pharmacokinetics (PK) of a therapeutic intervention and the resulting pharmacodynamic (PD) effect . This is especially true in the translational space, where estimated PKPD parameters, derived from relevant preclinical studies and appropriately adjusted for the clinical scenario, enabled prospective simulations to evaluate key drug development questions such as clinical dose level and frequency . Over the years, translational PKPD modeling has evolved beyond empirical models to incorporate more mechanistic components to establish mechanism‐based PKPD models, which facilitate biologic driven translations across species and/or between different patient populations.…”

Section: Definition and Terminologymentioning

confidence: 99%

“…14,15 This is especially true in the translational space, where estimated PKPD parameters, derived from relevant preclinical studies and appropriately adjusted for the clinical scenario, enabled prospective simulations to evaluate key drug development questions such as clinical dose level and frequency. 15,16 Over the years, translational PKPD modeling has evolved beyond empirical models to incorporate more mechanistic components to establish mechanism-based PKPD models, which facilitate biologic driven translations across species and/or between different patient populations. Although the value of PKPD modeling has been widely recognized, its main focus is to establish relationship between drug PK and selected elements of the biological system that are perturbed by a particular drug treatment.…”

Section: Definition and Terminologymentioning

confidence: 99%

Applications of Quantitative Systems Pharmacology in Model‐Informed Drug Discovery: Perspective on Impact and Opportunities

Bradshaw

Spilker

Zang³

et al. 2019

CPT Pharmacom & Syst Pharma

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Quantitative systems pharmacology (QSP) approaches have been increasingly applied in the pharmaceutical since the landmark white paper published in 2011 by a National Institutes of Health working group brought attention to the discipline. In this perspective, we discuss QSP in the context of other modeling approaches and highlight the impact of QSP across various stages of drug development and therapeutic areas. We discuss challenges to the field as well as future opportunities.

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Translational pharmacokinetic-pharmacodynamic analysis in the pharmaceutical industry: an IQ Consortium PK-PD Discussion Group perspective

Cited by 20 publications

References 78 publications

Application of Pharmacokinetic-Pharmacodynamic Modeling to Inform Translation of In Vitro NaV1.7 Inhibition to In Vivo Pharmacological Response in Non-human Primate

Application of Pharmacokinetic-Pharmacodynamic Modeling to Inform Translation of In Vitro NaV1.7 Inhibition to In Vivo Pharmacological Response in Non-human Primate

Translational Model‐Informed Dose Selection for a Human Positron Emission Tomography Imaging Study of JNJ‐54175446, a P2X7 Receptor Antagonist

Applications of Quantitative Systems Pharmacology in Model‐Informed Drug Discovery: Perspective on Impact and Opportunities

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