In Silico Investigation of the Decline in Clinical Efficacy of Artemisinin Combination Therapies Due to Increasing Artemisinin and Partner Drug Resistance

Characterisation of Plasmodium vivax lactate dehydrogenase dynamics in P. vivax infections

Plasmodium vivax lactate dehydrogenase (PvLDH) is an essential enzyme in the glycolytic pathway of P. vivax. It is widely used as a diagnostic biomarker and a measure of total-body parasite biomass in vivax malaria. However, the dynamics of PvLDH remains poorly understood. Here, we developed mathematical models that capture parasite and matrix PvLDH dynamics in ex vivo culture and the human host. We estimated key biological parameters characterising in vivo PvLDH dynamics based on longitudinal data of parasitemia and PvLDH concentration collected from P. vivax-infected humans, with the estimates informed by the ex vivo data as prior knowledge in a Bayesian hierarchical framework. We found that the in vivo accumulation rate of intraerythrocytic PvLDH peaks at 10-20 h post-invasion (late ring stage) with a median estimate of intraerythrocytic PvLDH mass at the end of the life cycle to be 9.4 × 10-3ng. We also found that the median estimate of in vivo PvLDH half-life was approximately 21.9 h. Our findings provide a foundation with which to advance our quantitative understanding of P. vivax biology and will facilitate the improvement of PvLDH-based diagnostic tools.

Malaria PK/PD and the Role Pharmacometrics Can Play in the Global Health Arena: Malaria Treatment Regimens for Vulnerable Populations

Malaria is an infectious disease which disproportionately effects children and pregnant women. These vulnerable populations are often excluded from clinical trials resulting in one‐size‐fits‐all treatment regimens based on those established for a nonpregnant adult population. Pharmacokinetic/pharmacodynamic (PK/PD) models can be used to optimize dose selection as they define the drug exposure‐response relationship. Additionally, these models are able to identify patient characteristics that cause alterations in the expected PK/PD profiles and through simulations can recommend changes to dosing which compensate for the differences. In this review, we examine how PK/PD models have been applied to optimize antimalarial dosing recommendations for young children, including those who are malnourished, pregnant women, and individuals receiving concomitant therapies such as those for HIV treatment. The malaria field has had great success in utilizing PK/PD models as a foundation to update treatment guidelines and propose the next generation of dosing regimens to investigate in clinical trials. We propose how the malaria field can continue to use modeling to improve therapies by further integrating PK data into clinical studies and including data on drug resistance and host immunity in PK/PD models. Finally, we suggest that other disease areas can achieve similar success in applying pharmacometrics to improve outcomes by implementing three key principals.

Parasite-Host Dynamics throughout Antimalarial Drug Development Stages Complicate the Translation of Parasite Clearance

Ensuring continued success against malaria depends on a pipeline of new antimalarials. Antimalarial drug development utilizes preclinical murine and experimental human malaria infection studies to evaluate drug efficacy.

Ensuring continued success against malaria depends on a pipeline of new antimalarials. Antimalarial drug development utilizes preclinical murine and experimental human malaria infection studies to evaluate drug efficacy. A sequential approach is typically adapted, with results from each stage informing the design of the next stage of development. The validity of this approach depends on confidence that results from murine malarial studies predict the outcome of clinical trials in humans. Parasite clearance rates following treatment are key parameters of drug efficacy. To investigate the validity of forward predictions, we developed a suite of mathematical models to capture parasite growth and drug clearance along the drug development pathway and estimated parasite clearance rates. When comparing the three infection experiments, we identified different relationships of parasite clearance with dose and different maximum parasite clearance rates. In Plasmodium berghei-NMRI mouse infections, we estimated a maximum parasite clearance rate of 0.2 (1/h); in Plasmodium falciparum-SCID mouse infections, 0.05 (1/h); and in human volunteer infection studies with P. falciparum, we found a maximum parasite clearance rate of 0.12 (1/h) and 0.18 (1/h) after treatment with OZ439 and MMV048, respectively. Sensitivity analysis revealed that host-parasite driven processes account for up to 25% of variance in parasite clearance for medium-high doses of antimalarials. Although there are limitations in translating parasite clearance rates across these experiments, they provide insight into characterizing key parameters of drug action and dose response and assist in decision-making regarding dosage for further drug development.