Quantification of cure for pharmacodynamic models of antimalarial drugs: Deterministic versus stochastic approaches

In silico pharmacokinetic-pharmacodynamic (PK-PD) models are used to inform dose optimisation in antimalarial drug development. Here the PK-PD models capture the change in parasite count over time because of exposure to antimalarial drug(s). For current deterministic PD models, simulated parasite numbers decline proportionally during treatment asymptotically approaching zero, requiring a cure threshold to be selected. We implemented an alternative stochastic model, where parasite-time profiles were simulated using a binomial function with an hourly parasite survival probability. This probabilistic model enables a time of exact cure to be calculated, when zero parasites remain. The 28-day cure rates predicted by the deterministic and stochastic models for multiple antimalarial treatment strategies were equivalent, with an absolute difference ranging from -0.8% to 3.1% (mean of 0.48%, positive values indicate higher stochastic model cure rates). This confirms that the standard deterministic method is an adequate proxy for the underlying stochastic process of parasite death during antimalarial treatment.

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Publication Details

Journal
British Journal of Clinical Pharmacology
Published
2025-11-08
DOI
https://doi.org/10.1002/bcp.70340
Primary Topic
Malaria Research and Control
Type
article
Field-Weighted Citation Impact
0.00

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article

Quantification of cure for pharmacodynamic models of antimalarial drugs: Deterministic versus stochastic approaches

Julie Anne Simpson, Robert J. Commons, David J. Price, Meg K. Tully
British Journal of Clinical Pharmacology
Malaria Research and Control
article

Quantification of cure for pharmacodynamic models of antimalarial drugs: Deterministic versus stochastic approaches

Julie Anne Simpson, Robert J. Commons, David J. Price, Meg K. Tully
article en

Abstract

In silico pharmacokinetic-pharmacodynamic (PK-PD) models are used to inform dose optimisation in antimalarial drug development. Here the PK-PD models capture the change in parasite count over time because of exposure to antimalarial drug(s). For current deterministic PD models, simulated parasite numbers decline proportionally during treatment asymptotically approaching zero, requiring a cure threshold to be selected. We implemented an alternative stochastic model, where parasite-time profiles were simulated using a binomial function with an hourly parasite survival probability. This probabilistic model enables a time of exact cure to be calculated, when zero parasites remain. The 28-day cure rates predicted by the deterministic and stochastic models for multiple antimalarial treatment strategies were equivalent, with an absolute difference ranging from -0.8% to 3.1% (mean of 0.48%, positive values indicate higher stochastic model cure rates). This confirms that the standard deterministic method is an adequate proxy for the underlying stochastic process of parasite death during antimalarial treatment.

British Journal of Clinical PharmacologyVol. 92(1)
The University of Melbourne (AU), Charles Darwin University (AU), University of Oxford (GB), Menzies School of Health Research (AU), Peter Doherty Institute (AU), Ballarat Health Services (AU)
Australian Government, National Health and Medical Research Council
Openalex Percentile: Top 56%
Malaria Research and Control
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