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A quantitative systems pharmacology model for simulating OFF-Time in augmentation trials for Parkinson’s disease: application to preladenant

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Abstract

The clinical impact of therapeutic interventions in Parkinson’s disease is often measured as a reduction in OFF-time when the beneficial effects of the standard-of-care L-DOPA formulations wanes off. We investigated the pharmacodynamic interactions of augmentation therapy to standard-of-care using a quantitative systems pharmacology (QSP) model of the basal ganglia motor circuit, essentially a computer model of neuronal firing in the different subregions with anatomically informed connectivity, cell-specific expression of 17 different G-protein coupled receptors and corresponding coupling to voltage-gated ion channel effector proteins based on experimentally observed intracellular signaling. The calculated beta/gamma (b/g) power spectrum of the local field potentials in the subthalamic nucleus was previously calibrated on the clinically relevant Unified Parkinson’s Disease Rating Scale (UPDRS). When combining this QSP model with PK modeling of different formulations of L-DOPA, we calculated the b/g fluctuations over a 16 h awake period and used a weighted distance from a specific threshold to determine the cumulative liability of OFF-Time. Prediction of OFF-time with clinical observations of different L-DOPA formulations showed a significant correlation. Simulations show that augmentation with the adenosine A2A antagonist preladenant reduces OFF-time with 6 min for carbidopa/levodopa 950 mg 5-times daily to 37 min for 100 mg L-DOPA – 3 or 5 times daily. Exploring delays between preladenant and L-DOPA intake did not improve the outcome. Hypothetical A2A antagonists with an ideal PK and pharmacology profile can achieve OFF-Time reductions ranging from 9.5 min with DuoDopa to 55 min with low dose L-DOPA formulations. Combination of the QSP model with PK modeling can predict the anticipated OFF-Time reduction of novel A2A antagonists with standard of care. With the large number of GPCR in the model, this combination can support both the design of clinical trials with new therapeutic agents and the optimization of combination therapy in clinical practice.

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Abbreviations

A1:

Adenosine 1 receptor

A2A:

Adenosine 2A receptor

AUC:

Area-under-the-curve (for PK profile)

cAMP:

Cyclic adenosine-mono-phosphate (intracellular second messenger)

GPe:

Globus Pallidus pars externa

GPe:

Globus Pallidus pars interna

MSN:

Medium spiny neurons (majority of striatal GABAergic neurons)

PD:

Parkinson’s disease

PET:

Positron emission tomography

PK:

Pharmacokinetics

Pyr:

Pyramidal neurons (located in the motor cortex)

QSP:

Quantitative systems pharmacology

Re:

Reticular neurons

STN:

Subthalamic nucleus

TC:

Thalamocortical neurons

UPDRS:

Unified Parkinson’s disease rating scale

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Authors and Affiliations

  1. Certara QSP-UK, Canterbury Innovation Centre, University Road, Canterbury, CT2 7FG, UK

    Rachel Rose, Emma Mitchell & Piet Van Der Graaf

  2. Kyowa-Kirin, 1-9-2 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan

    Daisuke Takaichi & Jun Hosogi

  3. Certara QSP-US, Westwind Dr 686, Berwyn, PA, 19312, USA

    Hugo Geerts

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  1. Rachel Rose
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Contributions

RR developed the PK model and RR and EM ran the simulations; EM developed the interface between the PK model and the QSP model; DT and JH provided key insights into defining the relation between the QSP biomarkers and the clinical presentation. PvdG and HG conceived and led the project and wrote the manuscript. All authors reviewed the manuscript.

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Correspondence to Hugo Geerts.

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Rose, R., Mitchell, E., Van Der Graaf, P. et al. A quantitative systems pharmacology model for simulating OFF-Time in augmentation trials for Parkinson’s disease: application to preladenant. J Pharmacokinet Pharmacodyn 49, 593–606 (2022). https://doi.org/10.1007/s10928-022-09825-9

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