Assessing the utility of an anti-malarial pharmacokinetic-pharmacodynamic model for aiding drug clinical development

The area under the effect curve as an efficacy determinant for anti‐infectives

Pharmacokinetic/pharmacodynamic (PK/PD) indices making use of area under the curve, maximum concentration, and the duration that in vivo drug concentration is maintained above a critical level are commonly applied to clinical dose prediction from animal efficacy experiments in the infectious disease arena. These indices make suboptimal use of the nonclinical data, and the prediction depends on the shape of the PK profiles in the animals, determined by the species‐specific absorption, distribution, metabolism, and elimination properties, and the dosing regimen used in the efficacy experiments. Motivated by the principle that efficacy is driven by pharmacology, we conducted simulations using a generalized pathogen dynamic model, to assess the properties of an alternative efficacy predictor: the area under the effect curve (AUEC), computed using in vitro PD and in vivo PK. Across a wide range of hypothetical scenarios, the AUEC consistently showed regimen‐independent strong correlation (R² 0.76–0.98) with in vivo efficacy, superior to all other indices. These findings serve as proof of concept that AUEC should be considered in practice as a translation tool for cross‐species dose prediction. Using AUEC for clinical dose prediction could also potentially cut down animal use by reducing or avoiding dose fractionation experiments.

Suitability of methods for Plasmodium falciparum cultivation in atmospheric air

BACKGROUND

One of the most controversial factors about malaria parasite culture is the gaseous composition used. The most commonly used one consists of a mixture poor in O₂ and rich in CO₂.

OBJECTIVES

The present study aimed to share standard methods from our research group simplifying Plasmodium falciparum cultures by employing atmospheric air (ATM) and reusable glass bottles under agitation.

METHODS

Here, it was compared the parasite viability, free oxygen in media, and drug sensitivity between different strains and isolates maintained for long periods under ATM or classic conditions.

FINDINGS

The oxygen concentration in media under ATM was slightly superior to that observed in human blood and the media under the classic gaseous mixture. However, ATM or the use of glass bottles did not affect parasitic proliferation after several years of culture. Noticeably, the introduction of ATM altered reversibly the efficacy of several antimalarials. This influence was different between the strains and isolate.

CONCLUSIONS

ATM conditions and shaken flasks could be used as a standard method condition for culture manutention since they do not differ greatly from classical 5% O₂ gas mixtures in terms of parasite proliferation and do not impose non-reversible changes to P. falciparum physiology.

Parasite Viability as a Measure of In Vivo Drug Activity in Preclinical and Early Clinical Antimalarial Drug Assessment

The rate at which parasitemia declines in a host after treatment with an antimalarial drug is a major metric for assessment of antimalarial drug activity in preclinical models and in early clinical trials. However, this metric does not distinguish between viable and nonviable parasites. Thus, enumeration of parasites may result in underestimation of drug activity for some compounds, potentially confounding its use as a metric for assessing antimalarial activity in vivo. Here, we report a study of the effect of artesunate on Plasmodium falciparum viability in humans and in mice. We first measured the drug effect in mice by estimating the decrease in parasite viability after treatment using two independent approaches to estimate viability. We demonstrate that, as previously reported in humans, parasite viability declines much faster after artesunate treatment than does the decline in parasitemia (termed parasite clearance). We also observed that artesunate kills parasites faster at higher concentrations, which is not discernible from the traditional parasite clearance curve and that each subsequent dose of artesunate maintains its killing effect. Furthermore, based on measures of parasite viability, we could accurately predict the in vivo recrudescence of infection. Finally, using pharmacometrics modeling, we show that the apparent differences in the antimalarial activity of artesunate in mice and humans are partly explained by differences in host removal of dead parasites in the two hosts. However, these differences, along with different pharmacokinetic profiles, do not fully account for the differences in activity. (This study has been registered with the Australian New Zealand Clinical Trials Registry under identifier ACTRN12617001394336.)

Efficient simulation of clinical target response surfaces

Simulation of combination therapies is challenging due to computational complexity. Either a simple model is used to simulate the response for many combinations of concentration to generate a response surface but parameter variability and uncertainty are neglected and the concentrations are constant—the link to the doses to be administered is difficult to make—or a population pharmacokinetic/pharmacodynamic model is used to predict the response to combination therapy in a clinical trial taking into account the time‐varying concentration profile, interindividual variability (IIV), and parameter uncertainty but simulations are limited to only a few selected doses. We devised new algorithms to efficiently search for the combination doses that achieve a predefined efficacy target while taking into account the IIV and parameter uncertainty. The result of this method is a response surface of confidence levels, indicating for all dose combinations the likelihood of reaching the specified efficacy target. We highlight the importance to simulate across a population rather than focus on an individual. Finally, we provide examples of potential applications, such as informing experimental design.

Understanding dynamics of Plasmodium falciparum gametocytes production: Insights from an age-structured model

Many models of within-host malaria infection dynamics have been formulated since the pioneering work of Anderson et al. in 1989. Biologically, the goal of these models is to understand what governs the severity of infections, the patterns of infectiousness, and the variation thereof across individual hosts. Mathematically, these models are based on dynamical systems, with standard approaches ranging from K-compartments ordinary differential equations (ODEs) to delay differential equations (DDEs), to capture the relatively constant duration of replication and bursting once a parasite infects a host red blood cell. Using malariatherapy data, which offers fine-scale resolution on the dynamics of infection across a number of individual hosts, we compare the fit and robustness of one of these standard approaches (K-compartments ODE) with a partial differential equations (PDEs) model, which explicitly tracks the "age" of an infected cell. While both models perform quite similarly in terms of goodness-of-fit for suitably chosen K, the K-compartments ODE model particularly overestimates parasite densities early on in infections when the number of repeated compartments is not large enough. Finally, the K-compartments ODE model (for suitably chosen K) and the PDE model highlight a strong qualitative connection between the density of transmissible parasite stages (i.e., gametocytes) and the density of host-damaging (and asexually-replicating) parasite stages. This finding provides a simple tool for predicting which hosts are most infectious to mosquitoes -vectors of Plasmodium parasites- which is a crucial component of global efforts to control and eliminate malaria.

Seeking an optimal dosing regimen for OZ439/DSM265 combination therapy for treating uncomplicated falciparum malaria

BACKGROUND

The efficacy of artemisinin-based combination therapies (ACTs), the first-line treatments for uncomplicated falciparum malaria, has been declining in malaria-endemic countries due to the emergence of malaria parasites resistant to these compounds. Novel alternative therapies are needed urgently to prevent the likely surge in morbidity and mortality due to failing ACTs.

OBJECTIVES

This study investigates the efficacy of the combination of two novel drugs, OZ439 and DSM265, using a biologically informed within-host mathematical model.

METHODS

A within-host model was developed, which accounts for the differential killing of these compounds against different stages of the parasite's life cycle and accommodates the pharmacodynamic interaction between the drugs. Data of healthy volunteers infected with falciparum malaria collected from four trials (three that administered OZ439 and DSM265 alone, and the fourth a combination of OZ439 and DSM265) were analysed. Model parameters were estimated in a hierarchical Bayesian framework.

RESULTS

The posterior predictive simulations of our model predicted that 800 mg of OZ439 combined with 450 mg of DSM265, which are within the safe and tolerable dose range, can provide above 90% cure rates 42 days after drug administration.

CONCLUSIONS

Our results show that the combination of OZ439 and DSM265 can be a promising alternative to replace ACTs. Our model can be used to inform future Phase 2 and 3 clinical trials of OZ439/DSM265, fast-tracking the deployment of this combination therapy in the regions where ACTs are failing. The dosing regimens that are shown to be efficacious and within safe and tolerable limits are suggested for future investigations.

Development and Validation of an In Silico Decision Tool To Guide Optimization of Intravenous Artesunate Dosing Regimens for Severe Falciparum Malaria Patients

Most deaths from severe falciparum malaria occur within 24 h of presentation to a hospital. Intravenous (i.v.) artesunate is the first-line treatment for severe falciparum malaria, but its efficacy may be compromised by delayed parasitological responses. In patients with severe malaria, the life-saving benefit of the artemisinin derivatives is their ability to clear circulating parasites rapidly, before they can sequester and obstruct the microcirculation. To evaluate the dosing of i.v. artesunate for the treatment of artemisinin-sensitive and reduced ring stage sensitivity to artemisinin severe falciparum malaria infections, Bayesian pharmacokinetic-pharmacodynamic modeling of data from 94 patients with severe malaria (80 children from Africa and 14 adults from Southeast Asia) was performed. Assuming that delayed parasite clearance reflects a loss of ring stage sensitivity to artemisinin derivatives, the median (95% credible interval) percentage of patients clearing ≥99% of parasites within 24 h (PC24≥99%) for standard (2.4 mg/kg body weight i.v. artesunate at 0 and 12 h) and simplified (4 mg/kg i.v. artesunate at 0 h) regimens was 65% (52.5% to 74.5%) versus 44% (25% to 61.5%) for adults, 62% (51.5% to 74.5%) versus 39% (20.5% to 58.5%) for larger children (≥20 kg), and 60% (48.5% to 70%) versus 36% (20% to 53.5%) for smaller children (<20 kg). The upper limit of the credible intervals for all regimens was below a PC24≥99% of 80%, a threshold achieved on average in clinical studies of severe falciparum malaria infections. In severe falciparum malaria caused by parasites with reduced ring stage susceptibility to artemisinin, parasite clearance is predicted to be slower with both the currently recommended and proposed simplified i.v. artesunate dosing regimens.

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.

Global Analysis of a Reaction-Diffusion Within-Host Malaria Infection Model with Adaptive Immune Response

Malaria is one of the most dangerous global diseases. This paper studies a reaction-diffusion model for the within-host dynamics of malaria infection with both antibody and cell-mediated immune responses. The model explores the interactions between uninfected red blood cells (erythrocytes), three types of infected red blood cells, free merozoites, CTLs and antibodies. It contains some parameters to measure the effect of antimalarial drugs and isoleucine starvation on the blood cycle of malaria infection. The basic properties of the model are discussed. All possible equilibrium points and the threshold conditions required for their existence are addressed. The global stability of all equilibria are proved by selecting suitable Lyapunov functionals and using LaSalle’s invariance principle. The characteristic equations are used to study the local instability conditions of the equilibria. Some numerical simulations are conducted to support the theoretical results. The results indicate that antimalarial drugs with high efficacy can clear the infection and take the system towards the disease-free state. Increasing the efficacy of isoleucine starvation has a similar effect as antimalarial drugs and can eliminate the disease. The presence of immune responses with low efficacy of treatments does not provide a complete protection against the disease. However, the immune responses reduce the concentrations of all types of infected cells and limit the production of malaria parasites.

Modeling the dynamics of Plasmodium falciparum gametocytes in humans during malaria infection

Renewed efforts to eliminate malaria have highlighted the potential to interrupt human-to-mosquito transmission — a process mediated by gametocyte kinetics in human hosts. Here we study the in vivo dynamics of Plasmodium falciparum gametocytes by establishing a framework which incorporates improved measurements of parasitemia, a novel gametocyte dynamics model and model fitting using Bayesian hierarchical inference. We found that the model provides an excellent fit to the clinical data from 17 volunteers infected with P. falciparum (3D7 strain) and reliably predicts observed gametocytemia. We estimated the sexual commitment rate and gametocyte sequestration time to be 0.54% (95% credible interval: 0.30–1.00%) per asexual replication cycle and 8.39 (6.54–10.59) days respectively. We used the data-calibrated model to investigate human-to-mosquito transmissibility, providing a method to link within-human host infection kinetics to epidemiological-scale infection and transmission patterns.

Within-host modeling of blood-stage malaria

Malaria infection continues to be a major health problem worldwide and drug resistance in the major human parasite species, Plasmodium falciparum, is increasing in South East Asia. Control measures including novel drugs and vaccines are in development, and contributions to the rational design and optimal usage of these interventions are urgently needed. Infection involves the complex interaction of parasite dynamics, host immunity, and drug effects. The long life cycle (48 hours in the common human species) and synchronized replication cycle of the parasite population present significant challenges to modeling the dynamics of Plasmodium infection. Coupled with these, variation in immune recognition and drug action at different life cycle stages leads to further complexity. We review the development and progress of "within-host" models of Plasmodium infection, and how these have been applied to understanding and interpreting human infection and animal models of infection.

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

Antimalarial treatment currently relies on an artemisinin derivative and a longer-acting partner drug. With the emergence of resistance to the artemisinin derivatives and the potential pressure this exerts on the partner drugs, the impact of resistance to each drug on efficacy needs to be investigated. An in silico exploration of dihydroartemisinin-piperaquine and mefloquine-artesunate, two artemisinin-based combination therapies that are commonly used in Southeast Asia, was performed. The percentage of treatment failures was simulated from a within-host pharmacokinetic-pharmacodynamic (PKPD) model, assuming that parasites developed increasing levels of (i) artemisinin derivative resistance or (ii) concomitant resistance to both the artemisinin derivative and the partner drug. Because the exact nature of how resistant Plasmodium falciparum parasites respond to treatment is unknown, we examined the impact on treatment failure rates of artemisinin resistance that (i) reduced the maximal killing rate, (ii) increased the concentration of drug required for 50% killing, or (iii) shortened the window of parasite stages that were susceptible to artemisinin derivatives until the drugs had no effect on the ring stages. The loss of the ring-stage activity of the artemisinin derivative caused the greatest increase in the treatment failure rate, and this result held irrespective of whether partner drug resistance was assumed to be present or not. To capture the uncertainty regarding how artemisinin derivative and partner drug resistance affects the assumed concentration-killing effect relationship, a variety of changes to this relationship should be considered when using within-host PKPD models to simulate clinical outcomes to guide treatment strategies for resistant infections.

Investigating the Efficacy of Triple Artemisinin-Based Combination Therapies for Treating Plasmodium falciparum Malaria Patients Using Mathematical Modeling

The first line treatment for uncomplicated falciparum malaria is artemisinin-based combination therapy (ACT), which consists of an artemisinin derivative coadministered with a longer-acting partner drug. However, the spread of Plasmodium falciparum resistant to both artemisinin and its partner drugs poses a major global threat to malaria control activities. Novel strategies are needed to retard and reverse the spread of these resistant parasites. One such strategy is triple artemisinin-based combination therapy (TACT). We developed a mechanistic within-host mathematical model to investigate the efficacy of a TACT (dihydroartemisinin-piperaquine-mefloquine [DHA-PPQ-MQ]) for use in South-East Asia, where DHA and PPQ resistance are now increasingly prevalent. Comprehensive model simulations were used to explore the degree to which the underlying resistance influences the parasitological outcomes. The effect of MQ dosing on the efficacy of TACT was quantified at various degrees of DHA and PPQ resistance. To incorporate interactions between drugs, a novel model is presented for the combined effect of DHA-PPQ-MQ, which illustrates how the interactions can influence treatment efficacy. When combined with a standard regimen of DHA and PPQ, the administration of three 6.7-mg/kg doses of MQ was sufficient to achieve parasitological efficacy greater than that currently recommended by World Health Organization (WHO) guidelines. As a result, three 8.3-mg/kg doses of MQ, the current WHO-recommended dosing regimen for MQ, combined with DHA-PPQ, has the potential to produce high cure rates in regions where resistance to DHA-PPQ has emerged.

A Dynamic Stress Model Explains the Delayed Drug Effect in Artemisinin Treatment of Plasmodium falciparum

Artemisinin resistance constitutes a major threat to the continued success of control programs for malaria, particularly in light of developing resistance to partner drugs. Improving our understanding of how artemisinin-based drugs act and how resistance manifests is essential for the optimization of dosing regimens and the development of strategies to prolong the life span of current first-line treatment options. Recent short-drug-pulse in vitro experiments have shown that the parasite killing rate depends not only on drug concentration but also the exposure time, challenging the standard pharmacokinetic-pharmacodynamic (PK-PD) paradigm in which the killing rate depends only on drug concentration. Here, we introduce a dynamic stress model of parasite killing and show through application to 3D7 laboratory strain viability data that the inclusion of a time-dependent parasite stress response dramatically improves the model's explanatory power compared to that of a traditional PK-PD model. Our model demonstrates that the previously reported hypersensitivity of early-ring-stage parasites of the 3D7 strain to dihydroartemisinin compared to other parasite stages is due primarily to a faster development of stress rather than a higher maximum achievable killing rate. We also perform in vivo simulations using the dynamic stress model and demonstrate that the complex temporal features of artemisinin action observed in vitro have a significant impact on predictions for in vivo parasite clearance. Given the important role that PK-PD models play in the design of clinical trials for the evaluation of alternative drug dosing regimens, our novel model will contribute to the further development and improvement of antimalarial therapies.

Assessing the impact of imperfect adherence to artemether-lumefantrine on malaria treatment outcomes using within-host modelling

Artemether-lumefantrine (AL) is the most widely-recommended treatment for uncomplicated Plasmodium falciparum malaria worldwide. Its safety and efficacy have been extensively demonstrated in clinical trials; however, its performance in routine health care settings, where adherence to drug treatment is unsupervised and therefore may be suboptimal, is less well characterised. Here we develop a within-host modelling framework for estimating the effects of sub-optimal adherence to AL treatment on clinical outcomes in malaria patients. Our model incorporates the data on the human immune response to the parasite, and AL's pharmacokinetic and pharmacodynamic properties. Utilising individual-level data of adherence to AL in 482 Tanzanian patients as input for our model predicted higher rates of treatment failure than were obtained when adherence was optimal (9% compared to 4%). Our model estimates that the impact of imperfect adherence was worst in children, highlighting the importance of advice to caregivers.

A mechanistic model quantifies artemisinin-induced parasite growth retardation in blood-stage Plasmodium falciparum infection

Falciparum malaria is a major parasitic disease causing widespread morbidity and mortality globally. Artemisinin derivatives-the most effective and widely-used antimalarials that have helped reduce the burden of malaria by 60% in some areas over the past decade-have recently been found to induce growth retardation of blood-stage Plasmodium falciparum when applied at clinically relevant concentrations. To date, no model has been designed to quantify the growth retardation effect and to predict the influence of this property on in vivo parasite killing. Here we introduce a mechanistic model of parasite growth from the ring to trophozoite stage of the parasite's life cycle, and by modelling the level of staining with an RNA-binding dye, we demonstrate that the model is able to reproduce fluorescence distribution data from in vitro experiments using the laboratory 3D7 strain. We quantify the dependence of growth retardation on drug concentration and identify the concentration threshold above which growth retardation is evident. We estimate that the parasite life cycle is prolonged by up to 10 hours. We illustrate that even such a relatively short delay in growth may significantly influence in vivo parasite dynamics, demonstrating the importance of considering growth retardation in the design of optimal artemisinin-based dosing regimens.

Development of a paediatric physiologically based pharmacokinetic model to assess the impact of drug-drug interactions in tuberculosis co-infected malaria subjects: A case study with artemether-lumefantrine and the CYP3A4-inducer rifampicin

The fixed dosed combination of artemether and lumefantrine (AL) is widely used for the treatment of malaria in adults and children in sub-Sahara Africa, with lumefantrine day 7 concentrations being widely used as a marker for clinical efficacy. Both are substrates for CYP3A4 and susceptible to drug-drug interactions (DDIs); indeed, knowledge of the impact of these factors is currently sparse in paediatric population groups. Confounding malaria treatment is the co-infection of patients with tuberculosis. The concomitant treatment of AL with tuberculosis chemotherapy, which includes the CYP3A4 inducer rifampicin, increases the risk of parasite recrudescence and malaria treatment failure. This study developed a population-based PBPK model for AL in adults capable of predicting the pharmacokinetics of AL under non-DDI and DDI conditions, as well as predicting AL pharmacokinetics in paediatrics of 2-12years of age. The validated model was utilised to assess the concomitant treatment of rifampicin and lumefantrine under standard body-weight based treatment regimens for 2-5year olds, and demonstrated that no subjects attained the target day 7 concentration (C_d7) of 280ng/mL, highlighting the importance of this DDI and the potential risk of malaria-TB based DDIs. An adapted 7-day treatment regimen was simulated and resulted in 63% and 74.5% of subjects attaining the target C_d7 for 1-tablet and 2-tablet regimens respectively.

Mathematical Modelling to Guide Drug Development for Malaria Elimination

Mathematical models of the dynamics of a drug within the host are now frequently used to guide drug development. These generally focus on assessing the efficacy and duration of response to guide patient therapy. Increasingly, antimalarial drugs are used at the population level, to clear infections, provide chemoprevention, and to reduce onward transmission of infection. However, there is less clarity on the extent to which different drug properties are important for these different uses. In addition, the emergence of drug resistance poses new threats to longer-term use and highlights the need for rational drug development. Here, we argue that integrating within-host pharmacokinetic and pharmacodynamic (PK/PD) models with mathematical models for the population-level transmission of malaria is key to guiding optimal drug design to aid malaria elimination.

Population Pharmacokinetic Properties of Piperaquine in Falciparum Malaria: An Individual Participant Data Meta-Analysis

BACKGROUND

Artemisinin-based combination therapies (ACTs) are the mainstay of the current treatment of uncomplicated Plasmodium falciparum malaria, but ACT resistance is spreading across Southeast Asia. Dihydroartemisinin-piperaquine is one of the five ACTs currently recommended by the World Health Organization. Previous studies suggest that young children (<5 y) with malaria are under-dosed. This study utilised a population-based pharmacokinetic approach to optimise the antimalarial treatment regimen for piperaquine.

METHODS AND FINDINGS

Published pharmacokinetic studies on piperaquine were identified through a systematic literature review of articles published between 1 January 1960 and 15 February 2013. Individual plasma piperaquine concentration-time data from 11 clinical studies (8,776 samples from 728 individuals) in adults and children with uncomplicated malaria and healthy volunteers were collated and standardised by the WorldWide Antimalarial Resistance Network. Data were pooled and analysed using nonlinear mixed-effects modelling. Piperaquine pharmacokinetics were described successfully by a three-compartment disposition model with flexible absorption. Body weight influenced clearance and volume parameters significantly, resulting in lower piperaquine exposures in small children (<25 kg) compared to larger children and adults (≥25 kg) after administration of the manufacturers' currently recommended dose regimens. Simulated median (interquartile range) day 7 plasma concentration was 29.4 (19.3-44.3) ng/ml in small children compared to 38.1 (25.8-56.3) ng/ml in larger children and adults, with the recommended dose regimen. The final model identified a mean (95% confidence interval) increase of 23.7% (15.8%-32.5%) in piperaquine bioavailability between each piperaquine dose occasion. The model also described an enzyme maturation function in very young children, resulting in 50% maturation at 0.575 (0.413-0.711) y of age. An evidence-based optimised dose regimen was constructed that would provide piperaquine exposures across all ages comparable to the exposure currently seen in a typical adult with standard treatment, without exceeding the concentration range observed with the manufacturers' recommended regimen. Limited data were available in infants and pregnant women with malaria as well as in healthy individuals.

CONCLUSIONS

The derived population pharmacokinetic model was used to develop a revised dose regimen of dihydroartemisinin-piperaquine that is expected to provide equivalent piperaquine exposures safely in all patients, including in small children with malaria. Use of this dose regimen is expected to prolong the useful therapeutic life of dihydroartemisinin-piperaquine by increasing cure rates and thereby slowing resistance development. This work was part of the evidence that informed the World Health Organization technical guidelines development group in the development of the recently published treatment guidelines (2015).

Quantifying the pharmacology of antimalarial drug combination therapy

Most current antimalarial drugs are combinations of an artemisinin plus a ‘partner’ drug from another class, and are known as artemisinin-based combination therapies (ACTs). They are the frontline drugs in treating human malaria infections. They also have a public-health role as an essential component of recent, comprehensive scale-ups of malaria interventions and containment efforts conceived as part of longer term malaria elimination efforts. Recent reports that resistance has arisen to artemisinins has caused considerable concern. We investigate the likely impact of artemisinin resistance by quantifying the contribution artemisinins make to the overall therapeutic capacity of ACTs. We achieve this using a simple, easily understood, algebraic approach and by more sophisticated pharmacokinetic/pharmacodynamic analyses of drug action; the two approaches gave consistent results. Surprisingly, the artemisinin component typically makes a negligible contribution (≪0.0001%) to the therapeutic capacity of the most widely used ACTs and only starts to make a significant contribution to therapeutic outcome once resistance has started to evolve to the partner drugs. The main threat to antimalarial drug effectiveness and control comes from resistance evolving to the partner drugs. We therefore argue that public health policies be re-focussed to maximise the likely long-term effectiveness of the partner drugs.

OptiMal-PK: an internet-based, user-friendly interface for the mathematical-based design of optimized anti-malarial treatment regimens

Background

The search for highly effective anti-malarial therapies has gathered pace and recent years have seen a number of promising single and combined therapies reach the late stages of development. A key drug development challenge is the need for early assessment of the clinical utility of new drug leads as it is often unclear for developers whether efforts should be focused on efficacy or metabolic stability/exposure or indeed whether the continuation of iterative QSAR (quantitative structure–activity and relationships) cycles of medicinal chemistry and biological testing will translate to improved clinical efficacy. Pharmacokinetic and pharmacodynamic (PK/PD)-based measurements available from in vitro studies can be used for such clinical predictions. However, these predictions often require bespoke mathematical PK/PD modelling expertise and are normally performed after candidate development and, therefore, not during the pre-clinical development phase when such decisions need to be made.

Methods

An internet-based tool has been developed using STELLA^® software. The tool simulates multiple differential equations that describe anti-malarial PK/PD relationships where the user can easily input PK/PD parameters. The tool utilizes a simple stop-light system to indicate the efficacy of each combination of parameters. This tool, called OptiMal-PK, additionally allows for the investigation of the effect of drug combinations with known or custom compounds.

Results

The results of simulations obtained from OptiMal-PK were compared to a previously published and validated mathematical model on which this tool is based. The tool has also been used to simulate the PK/PD relationship for a number of existing anti-malarial drugs in single or combined treatment. Simulations were predictive of the published clinical parasitological clearance activities for these existing therapies.

Conclusions

OptiMal-PK is designed to be implemented by medicinal chemists and pharmacologists during the pre-clinical anti-malarial drug development phase to explore the impact of different PK/PD parameters upon the predicted clinical activity of any new compound. It can help investigators to identify which pharmacological features of a compound are most important to the clinical performance of a new chemical entity and how partner drugs could potentially improve the activity of existing therapies.

Rethinking Dosing Regimen Selection of Piperaquine for Malaria Chemoprevention: A Simulation Study

Background

The combination of short-acting dihydroartemisinin and long-acting piperaquine (DP) is among the first-line therapies for the treatment of uncomplicated Plasmodium falciparum malaria. Population pharmacokinetic models of piperaquine (PQ) based on data from acute treatment of young children can be used to predict exposure profiles of piperaquine under different DP chemoprevention regimens. The purpose of our study was to make such predictions in young children.

Methods

Based on a prior population pharmacokinetic model of PQ in young Ugandan children, we simulated capillary plasma concentration-time profiles (including their variability) of candidate chemoprevention regimens for a reference population of 1–2 year olds weighing at least 11 kg. Candidate regimens that were tested included monthly administration of standard therapeutic doses, bimonthly dosing, and weekly dosing (with and without a loading dose).

Results

Once daily doses of 320 mg for three days (960 mg total) at the beginning of each month are predicted to achieve an average steady-state trough capillary piperaquine concentration of 35 ng/mL, with 60% achieving a level of 30 ng/mL or higher. In contrast, weekly dosing of 320 mg (i.e., 33% higher amount per month) is predicted to approximately double the average steady-state trough concentration, increase the percent of children predicted to achieve 30 ng/mL or higher (94%), while at the same time lowering peak concentrations. Exposure at steady-state, reached at approximately 3 months of multiple dosing, is expected to be approximately 2-fold higher than exposure following initial dosing, due to accumulation. A loading dose improves early exposure, thereby reducing the risk of breakthrough infections at the initiation of chemoprevention.

Conclusions

Once weekly chemoprevention of DP predicts favourable exposures with respect to both trough and peak concentrations. These predictions need to be verified, as well as safety evaluated, in field-based clinical studies of young children. Simulations based on prior knowledge provide a systematic information-driven approach to evaluate candidate DP chemopreventive regimens for future trial designs.

Incorporating Stage-Specific Drug Action into Pharmacological Modeling of Antimalarial Drug Treatment

Pharmacological modeling of antiparasitic treatment based on a drug's pharmacokinetic and pharmacodynamic properties plays an increasingly important role in identifying optimal drug dosing regimens and predicting their potential impact on control and elimination programs. Conventional modeling of treatment relies on methods that do not distinguish between parasites at different developmental stages. This is problematic for malaria parasites, as their sensitivity to drugs varies substantially during their 48-h developmental cycle. We investigated four drug types (short or long half-lives with or without stage-specific killing) to quantify the accuracy of the standard methodology. The treatment dynamics of three drug types were well characterized with standard modeling. The exception were short-half-life drugs with stage-specific killing (i.e., artemisinins) because, depending on time of treatment, parasites might be in highly drug-sensitive stages or in much less sensitive stages. We describe how to bring such drugs into pharmacological modeling by including additional variation into the drug's maximal killing rate. Finally, we show that artemisinin kill rates may have been substantially overestimated in previous modeling studies because (i) the parasite reduction ratio (PRR) (generally estimated to be 10(4)) is based on observed changes in circulating parasite numbers, which generally overestimate the "true" PRR, which should include both circulating and sequestered parasites, and (ii) the third dose of artemisinin at 48 h targets exactly those stages initially hit at time zero, so it is incorrect to extrapolate the PRR measured over 48 h to predict the impact of doses at 48 h and later.

How Robust Are Malaria Parasite Clearance Rates as Indicators of Drug Effectiveness and Resistance?

Artemisinin-based combination therapies (ACTs) are currently the first-line drugs for treating uncomplicated falciparum malaria, the most deadly of the human malarias. Malaria parasite clearance rates estimated from patients' blood following ACT treatment have been widely adopted as a measure of drug effectiveness and as surveillance tools for detecting the presence of potential artemisinin resistance. This metric has not been investigated in detail, nor have its properties or potential shortcomings been identified. Herein, the pharmacology of drug treatment, parasite biology, and human immunity are combined to investigate the dynamics of parasite clearance following ACT. This approach parsimoniously recovers the principal clinical features and dynamics of clearance. Human immunity is the primary determinant of clearance rates, unless or until artemisinin killing has fallen to near-ineffective levels. Clearance rates are therefore highly insensitive metrics for surveillance that may lead to overconfidence, as even quite substantial reductions in drug sensitivity may not be detected as lower clearance rates. Equally serious is the use of clearance rates to quantify the impact of ACT regimen changes, as this strategy will plausibly miss even very substantial increases in drug effectiveness. In particular, the malaria community may be missing the opportunity to dramatically increase ACT effectiveness through regimen changes, particularly through a switch to twice-daily regimens and/or increases in artemisinin dosing levels. The malaria community therefore appears overreliant on a single metric of drug effectiveness, the parasite clearance rate, that has significant and serious shortcomings.

Predicting the impact of border control on malaria transmission: a simulated focal screen and treat campaign

Background

South Africa is one of many countries committed to malaria elimination with a target of 2018 and all malaria-endemic provinces, including Mpumalanga, are increasing efforts towards this ambitious goal. The reduction of imported infections is a vital element of an elimination strategy, particularly if a country is already experiencing high levels of imported infections. Border control of malaria is one tool that may be considered.

Methods

A metapopulation, non-linear stochastic ordinary differential equation model is used to simulate malaria transmission in Mpumalanga and Maputo province, Mozambique (the source of the majority of imported infections) to predict the impact of a focal screen and treat campaign at the Mpumalanga–Maputo border. This campaign is simulated by nesting an individual-based model for the focal screen and treat campaign within the metapopulation transmission model.

Results

The model predicts that such a campaign, simulated for different levels of resources, coverage and take-up rates with a variety of screening tools, will not eliminate malaria on its own, but will reduce transmission substantially. Making the campaign mandatory decreases transmission further though sub-patent infections are likely to remain undetected if the diagnostic tool is not adequately sensitive. Replacing screening and treating with mass drug administration results in substantially larger decreases as all (including sub-patent) infections are treated before movement into Mpumalanga.

Conclusions

The reduction of imported cases will be vital to any future malaria control or elimination strategy. This simulation predicts that FSAT at the Mpumalanga–Maputo border will be unable to eliminate local malaria on its own, but may still play a key role in detecting and treating imported infections before they enter the country. Thus FSAT may form part of an integrated elimination strategy where a variety of interventions are employed together to achieve malaria elimination.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-015-0776-2) contains supplementary material, which is available to authorized users.

Modelling the time course of antimalarial parasite killing: a tour of animal and human models, translation and challenges

Malaria remains a global public health concern and current treatment options are suboptimal in some clinical settings. For effective chemotherapy, antimalarial drug concentrations must be sufficient to remove completely all of the parasites in the infected host. Optimized dosing therefore requires a detailed understanding of the time course of antimalarial response, whilst simultaneously considering the parasite life cycle and host immune elimination. Recently, the World Health Organization (WHO) has recommended the development of mathematical models for understanding better antimalarial drug resistance and management. Other international groups have also suggested that mechanistic pharmacokinetic (PK) and pharmacodynamic (PD) models can support the rationalization of antimalarial dosing strategies. At present, artemisinin-based combination therapy (ACT) is recommended as first line treatment of falciparum malaria for all patient groups. This review summarizes the PK-PD characterization of artemisinin derivatives and other partner drugs from both preclinical studies and human clinical trials. We outline the continuous and discrete time models that have been proposed to describe antimalarial activity on specific stages of the parasite life cycle. The translation of PK-PD predictions from animals to humans is considered, because preclinical studies can provide rich data for detailed mechanism-based modelling. While similar sampling techniques are limited in clinical studies, PK-PD models can be used to optimize the design of experiments to improve estimation of the parameters of interest. Ultimately, we propose that fully developed mechanistic models can simulate and rationalize ACT or other treatment strategies in antimalarial chemotherapy.

Improving the role and contribution of pharmacokinetic analyses in antimalarial drug clinical trials

It is now World Health Organization (WHO) policy that drug concentrations on day 7 be measured as part of routine assessment in antimalarial drug efficacy trials. The rationale is that this single pharmacological measure serves as a simple and practical predictor of treatment outcome for antimalarial drugs with long half-lives. Herein we review theoretical data and field studies and conclude that the day 7 drug concentration (d7c) actually appears to be a poor predictor of therapeutic outcome. This poor predictive capability combined with the fact that many routine antimalarial trials will have few or no failures means that there appears to be little justification for this WHO recommendation. Pharmacological studies have a huge potential to improve antimalarial dosing, and we propose study designs that use more-focused, sophisticated, and cost-effective ways of generating these data than the mass collection of single d7c concentrations.

Making the most of clinical data: reviewing the role of pharmacokinetic-pharmacodynamic models of anti-malarial drugs

Mechanistic within-host models integrating blood anti-malarial drug concentrations with the parasite-time profile provide a valuable decision tool for determining dosing regimens for anti-malarial treatments, as well as a formative component of population-level drug resistance models. We reviewed published anti-malarial pharmacokinetic-pharmacodynamic models to identify the challenges for these complex models where parameter estimation from clinical field data is limited. The inclusion of key pharmacodynamic processes in the mechanistic structure adopted varies considerably. These include the life cycle of the parasite within the red blood cell, the action of the anti-malarial on a specific stage of the life cycle, and the reduction in parasite growth associated with immunity. With regard to estimation of the pharmacodynamic parameters, the majority of studies simply compared descriptive summaries of the simulated outputs to published observations of host and parasite responses from clinical studies. Few studies formally estimated the pharmacodynamic parameters within a rigorous statistical framework using observed individual patient data. We recommend three steps in the development and evaluation of these models. Firstly, exploration through simulation to assess how the different parameters influence the parasite dynamics. Secondly, application of a simulation-estimation approach to determine whether the model parameters can be estimated with reasonable precision based on sampling designs that mimic clinical efficacy studies. Thirdly, fitting the mechanistic model to the clinical data within a Bayesian framework. We propose that authors present the model both schematically and in equation form and give a detailed description of each parameter, including a biological interpretation of the parameter estimates.

Benefits of a pharmacology antimalarial reference standard and proficiency testing program provided by the Worldwide Antimalarial Resistance Network (WWARN)

Comprehensive assessment of antimalarial drug resistance should include measurements of antimalarial blood or plasma concentrations in clinical trials and in individual assessments of treatment failure so that true resistance can be differentiated from inadequate drug exposure. Pharmacometric modeling is necessary to assess pharmacokinetic-pharmacodynamic relationships in different populations to optimize dosing. To accomplish both effectively and to allow comparison of data from different laboratories, it is essential that drug concentration measurement is accurate. Proficiency testing (PT) of laboratory procedures is necessary for verification of assay results. Within the Worldwide Antimalarial Resistance Network (WWARN), the goal of the quality assurance/quality control (QA/QC) program is to facilitate and sustain high-quality antimalarial assays. The QA/QC program consists of an international PT program for pharmacology laboratories and a reference material (RM) program for the provision of antimalarial drug standards, metabolites, and internal standards for laboratory use. The RM program currently distributes accurately weighed quantities of antimalarial drug standards, metabolites, and internal standards to 44 pharmacology, in vitro, and drug quality testing laboratories. The pharmacology PT program has sent samples to eight laboratories in four rounds of testing. WWARN technical experts have provided advice for correcting identified problems to improve performance of subsequent analysis and ultimately improved the quality of data. Many participants have demonstrated substantial improvements over subsequent rounds of PT. The WWARN QA/QC program has improved the quality and value of antimalarial drug measurement in laboratories globally. It is a model that has potential to be applied to strengthening laboratories more widely and improving the therapeutics of other infectious diseases.

Optimizing the programmatic deployment of the anti-malarials artemether-lumefantrine and dihydroartemisinin-piperaquine using pharmacological modelling

BACKGROUND

Successful programmatic use of anti-malarials faces challenges that are not covered by standard drug development processes. The development of appropriate pragmatic dosing regimens for low-resource settings or community-based use is not formally regulated, even though these may alter factors which can substantially affect individual patient and population level outcome, such as drug exposure, patient adherence and the spread of drug resistance and can affect a drug's reputation and its eventual therapeutic lifespan.

METHODS

An in silico pharmacological model of anti-malarial drug treatment with the pharmacokinetic/pharmacodynamic profiles of artemether-lumefantrine (AM-LF, Coartem®) and dihydroartemisinin-piperaquine (DHA-PPQ, Eurartesim®) was constructed to assess the potential impact of programmatic factors, including regionally optimized, age-based dosing regimens, poor patient adherence, food effects and drug resistance on treatment outcome at population level, and compared both drugs' susceptibility to these factors.

RESULTS

Compared with DHA-PPQ, therapeutic effectiveness of AM-LF seems more robust to factors affecting drug exposure, such as age- instead of weight-based dosing or poor adherence. The model highlights the sub-optimally low ratio of DHA:PPQ which, in combination with the narrow therapeutic dose range of PPQ compared to DHA that drives the weight or age cut-offs, leaves DHA at a high risk of under-dosing.

CONCLUSION

Pharmacological modelling of real-life scenarios can provide valuable supportive data and highlight modifiable determinants of therapeutic effectiveness that can help optimize the deployment of anti-malarials in control programmes.

Pharmacokinetic and pharmacodynamic considerations in antimalarial dose optimization

Antimalarial drugs have usually been first deployed in areas of malaria endemicity at doses which were too low, particularly for high-risk groups such as young children and pregnant women. This may accelerate the emergence and spread of resistance, thereby shortening the useful life of the drug, but it is an inevitable consequence of the current imprecise method of dose finding. An alternative approach to dose finding is suggested in which phase 2 studies concentrate initially on pharmacokinetic-pharmacodynamic (PK-PD) characterization and in vivo calibration of in vitro susceptibility information. PD assessment is facilitated in malaria because serial parasite densities are readily assessed by microscopy, and at low densities by quantitative PCR, so that initial therapeutic responses can be quantitated accurately. If the in vivo MIC could be characterized early in phase 2 studies, it would provide a sound basis for the choice of dose in all target populations in subsequent combination treatments. Population PK assessments in phase 2b and phase 3 studies which characterize PK differences between different age groups, clinical disease states, and human populations can then be combined with the PK-PD observations to provide a sound evidence base for dose recommendations in different target groups.

Nonlinear mixed-effects modelling of in vitro drug susceptibility and molecular correlates of multidrug resistant Plasmodium falciparum

The analysis of in vitro anti-malarial drug susceptibility testing is vulnerable to the effects of different statistical approaches and selection biases. These confounding factors were assessed with respect to pfmdr1 gene mutation and amplification in 490 clinical isolates. Two statistical approaches for estimating the drug concentration associated with 50% effect (EC₅₀) were compared: the commonly used standard two-stage (STS) method, and nonlinear mixed-effects modelling. The in vitro concentration-effect relationships for, chloroquine, mefloquine, lumefantrine and artesunate, were derived from clinical isolates obtained from patients on the western border of Thailand. All isolates were genotyped for polymorphisms in the pfmdr1 gene. The EC₅₀ estimates were similar for the two statistical approaches but 15–28% of isolates in the STS method had a high coefficient of variation (>15%) for individual estimates of EC₅₀ and these isolates had EC₅₀ values that were 32 to 66% higher than isolates derived with more precision. In total 41% (202/490) of isolates had amplification of pfmdr1 and single nucleotide polymorphisms were found in 50 (10%). Pfmdr1 amplification was associated with an increase in EC₅₀ for mefloquine (139% relative increase in EC₅₀ for 2 copies, 188% for 3+ copies), lumefantrine (82% and 75% for 2 and 3+ copies respectively) and artesunate (63% and 127% for 2 and 3+ copies respectively). In contrast pfmdr1 mutation at codons 86 or 1042 were associated with an increase in chloroquine EC₅₀ (44–48%). Sample size calculations showed that to demonstrate an EC₅₀ shift of 50% or more with 80% power if the prevalence was 10% would require 430 isolates and 245 isolates if the prevalence was 20%. In conclusion, although nonlinear mixed-effects modelling did not demonstrate any major advantage for determining estimates of anti-malarial drug susceptibility, the method includes all isolates, thereby, potentially improving confirmation of candidate molecular markers of anti-malarial drug susceptibility.

Improving pharmacokinetic-pharmacodynamic modeling to investigate anti-infective chemotherapy with application to the current generation of antimalarial drugs

Mechanism-based pharmacokinetic-pharmacodynamic (PK/PD) modelling is the standard computational technique for simulating drug treatment of infectious diseases with the potential to enhance our understanding of drug treatment outcomes, drug deployment strategies, and dosing regimens. Standard methodologies assume only a single drug is used, it acts only in its unconverted form, and that oral drugs are instantaneously absorbed across the gut wall to their site of action. For drugs with short half-lives, this absorption period accounts for a significant period of their time in the body. Treatment of infectious diseases often uses combination therapies, so we refined and substantially extended the PK/PD methodologies to incorporate (i) time lags and drug concentration profiles resulting from absorption across the gut wall and, if required, conversion to another active form; (ii) multiple drugs within a treatment combination; (iii) differing modes of action of drugs in the combination: additive, synergistic, antagonistic; (iv) drugs converted to an active metabolite with a similar mode of action. This methodology was applied to a case study of two first-line malaria treatments based on artemisinin combination therapies (ACTs, artemether-lumefantrine and artesunate-mefloquine) where the likelihood of increased artemisinin tolerance/resistance has led to speculation on their continued long-term effectiveness. We note previous estimates of artemisinin kill rate were underestimated by a factor of seven, both the unconverted and converted form of the artemisinins kill parasites and the extended PK/PD methodology produced results consistent with field observations. The simulations predict that a potentially rapid decline in ACT effectiveness is likely to occur as artemisinin resistance spreads, emphasising the importance of containing the spread of artemisinin resistance before it results in widespread drug failure. We found that PK/PD data is generally very poorly reported in the malaria literature, severely reducing its value for subsequent re-application, and we make specific recommendations to improve this situation.