Mefloquine pharmacokinetic-pharmacodynamic models: implications for dosing and resistance

Global scenario of Plasmodium vivax occurrence and resistance pattern

Malaria caused by Plasmodium vivax is comparatively less virulent than Plasmodium falciparum, which can also lead to severe disease and death. It shows a wide geographical distribution. Chloroquine serves as a drug of choice, with primaquine as a radical cure. However, with the appearance of resistance to chloroquine and treatment has been shifted to artemisinin combination therapy followed by primaquine as a radical cure. Sulphadoxine-pyrimethamine, mefloquine, and atovaquone-proguanil are other drugs of choice in chloroquine-resistant areas, and later resistance was soon reported for these drugs also. The emergence of drug resistance serves as a major hurdle to controlling and eliminating malaria. The discovery of robust molecular markers and regular surveillance for the presence of mutations in malaria-endemic areas would serve as a helpful tool to combat drug resistance. Here, in this review, we will discuss the endemicity of P. vivax, a historical overview of antimalarial drugs, the appearance of drug resistance and molecular markers with their global distribution along with different measures taken to reduce malaria burden due to P. vivax infection and their resistance.

Pre-existing partner-drug resistance to artemisinin combination therapies facilitates the emergence and spread of artemisinin resistance: a consensus modelling study

BACKGROUND

Artemisinin-resistant genotypes of Plasmodium falciparum have now emerged a minimum of six times on three continents despite recommendations that all artemisinins be deployed as artemisinin combination therapies (ACTs). Widespread resistance to the non-artemisinin partner drugs in ACTs has the potential to limit the clinical and resistance benefits provided by combination therapy. We aimed to model and evaluate the long-term effects of high levels of partner-drug resistance on the early emergence of artemisinin-resistant genotypes.

METHODS

Using a consensus modelling approach, we used three individual-based mathematical models of Plasmodium falciparum transmission to evaluate the effects of pre-existing partner-drug resistance and ACT deployment on the evolution of artemisinin resistance. Each model simulates 100 000 individuals in a particular transmission setting (malaria prevalence of 1%, 5%, 10%, or 20%) with a daily time step that updates individuals' infection status, treatment status, immunity, genotype-specific parasite densities, and clinical state. We modelled varying access to antimalarial drugs if febrile (coverage of 20%, 40%, or 60%) with one primary ACT used as first-line therapy: dihydroartemisinin-piperaquine (DHA-PPQ), artesunate-amodiaquine (ASAQ), or artemether-lumefantrine (AL). The primary outcome was time until 0·25 580Y allele frequency for artemisinin resistance (the establishment time).

FINDINGS

Higher frequencies of pre-existing partner-drug resistant genotypes lead to earlier establishment of artemisinin resistance. Across all models, a 10-fold increase in the frequency of partner-drug resistance genotypes on average corresponded to loss of artemisinin efficacy 2-12 years earlier. Most reductions in time to artemisinin resistance establishment were observed after an increase in frequency of the partner-drug resistance genotype from 0·0 to 0·10.

INTERPRETATION

Partner-drug resistance in ACTs facilitates the early emergence of artemisinin resistance and is a major public health concern. Higher-grade partner-drug resistance has the largest effect, with piperaquine resistance accelerating the early emergence of artemisinin-resistant alleles the most. Continued investment in molecular surveillance of partner-drug resistant genotypes to guide choice of first-line ACT is paramount.

FUNDING

Schmidt Science Fellowship in partnership with the Rhodes Trust; Bill & Melinda Gates Foundation; Wellcome Trust.

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.

Modelling the epidemiology of malaria and spread of HRP2-negative Plasmodium falciparum following the replacement of HRP2-detecting rapid diagnostic tests

Malaria rapid diagnostic tests (RDTs) are dominated by products which use histidine-rich protein 2 (HRP2) to detect Plasmodium falciparum. The emergence of parasites lacking the pfhrp2 gene can lead to high rates of false-negative results amongst these RDTs. One solution to restore the ability to correctly diagnose falciparum malaria is to switch to an RDT which is not solely reliant on HRP2. This study used an agent-based stochastic simulation model to investigate the impact on prevalence and transmission caused by switching the type of RDT used once false-negative rates reached pre-defined thresholds within the treatment-seeking symptomatic population. The results show that low transmission settings were the first to reach the false-negative switch threshold, and that lower thresholds were typically associated with better long-term outcomes. Changing the diagnostic RDT away from a HRP2-only RDT is predicted to restore the ability to correctly diagnose symptomatic malaria infections, but often did not lead to the extinction of HRP2-negative parasites from the population which continued to circulate in low density infections, or return to the parasite prevalence and transmission levels seen prior to the introduction of the HRP2-negative parasite. In contrast, failure to move away from HRP2-only RDTs leads to near fixation of these parasites in the population, and the inability to correctly diagnose symptomatic cases. Overall, these results suggest pfhrp2-deleted parasites are likely to become a significant component of P. falciparum parasite populations, and that long-term strategies are needed for diagnosis and surveillance which do not rely solely on HRP2.

A Computer Modelling Approach To Evaluate the Accuracy of Microsatellite Markers for Classification of Recurrent Infections during Routine Monitoring of Antimalarial Drug Efficacy

Antimalarial drugs have long half-lives, so clinical trials to monitor their efficacy require long periods of follow-up to capture drug failure that may become patent only weeks after treatment. Reinfections often occur during follow-up, so robust methods of distinguishing drug failures (recrudescence) from emerging new infections are needed to produce accurate failure rate estimates. Molecular correction aims to achieve this by comparing the genotype of a patient's pretreatment (initial) blood sample with that of any infection that occurs during follow-up, with matching genotypes indicating drug failure. We use an in silico approach to show that the widely used match-counting method of molecular correction with microsatellite markers is likely to be highly unreliable and may lead to gross under- or overestimates of the true failure rates, depending on the choice of matching criterion. A Bayesian algorithm for molecular correction was previously developed and utilized for analysis of in vivo efficacy trials. We validated this algorithm using in silico data and showed it had high specificity and generated accurate failure rate estimates. This conclusion was robust for multiple drugs, different levels of drug failure rates, different levels of transmission intensity in the study sites, and microsatellite genetic diversity. The Bayesian algorithm was inherently unable to accurately identify low-density recrudescence that occurred in a small number of patients, but this did not appear to compromise its utility as a highly effective molecular correction method for analyzing microsatellite genotypes. Strong consideration should be given to using Bayesian methodology to obtain accurate failure rate estimates during routine monitoring trials of antimalarial efficacy that use microsatellite markers.

Improving Methods for Analyzing Antimalarial Drug Efficacy Trials: Molecular Correction Based on Length-Polymorphic Markers msp-1, msp-2, and glurp

Drug efficacy trials monitor the continued efficacy of front-line drugs against falciparum malaria. Overestimating efficacy results in a country retaining a failing drug as first-line treatment with associated increases in morbidity and mortality, while underestimating drug effectiveness leads to removal of an effective treatment with substantial practical and economic implications.

Drug efficacy trials monitor the continued efficacy of front-line drugs against falciparum malaria. Overestimating efficacy results in a country retaining a failing drug as first-line treatment with associated increases in morbidity and mortality, while underestimating drug effectiveness leads to removal of an effective treatment with substantial practical and economic implications. Trials are challenging: they require long durations of follow-up to detect drug failures, and patients are frequently reinfected during that period. Molecular correction based on parasite genotypes distinguishes reinfections from drug failures to ensure the accuracy of failure rate estimates. Several molecular correction “algorithms” have been proposed, but which is most accurate and/or robust remains unknown. We used pharmacological modeling to simulate parasite dynamics and genetic signals that occur in patients enrolled in malaria drug clinical trials. We compared estimates of treatment failure obtained from a selection of proposed molecular correction algorithms against the known “true” failure rate in the model. Our findings are as follows. (i) Molecular correction is essential to avoid substantial overestimates of drug failure rates. (ii) The current WHO-recommended algorithm consistently underestimates the true failure rate. (iii) Newly proposed algorithms produce more accurate failure rate estimates; the most accurate algorithm depends on the choice of drug, trial follow-up length, and transmission intensity. (iv) Long durations of patient follow-up may be counterproductive; large numbers of new infections accumulate and may be misclassified, overestimating drug failure rate. (v) Our model was highly consistent with existing in vivo data. The current WHO-recommended method for molecular correction and analysis of clinical trials should be reevaluated and updated.

Optimal Duration of Follow-up for Assessing Antimalarial Efficacy in Pregnancy: A Retrospective Analysis of a Cohort Followed Up Until Delivery on the Thailand-Myanmar Border

Background

Follow-up for 28–42 days is recommended by the World Health Organization to assess antimalarial drug efficacy for nonpregnant populations. This study aimed to determine the optimal duration for pregnant women, as no specific guidance currently exists.

Methods

The distributions of time to recrudescence (treatment failure), confirmed by polymerase chain reaction genotyping for different antimalarial drugs in pregnancy, were analyzed by accelerated failure time models using secondary data on microscopically confirmed recurrent falciparum malaria collected in prospective studies on the Thailand–Myanmar border between 1994 and 2010.

Results

Of 946 paired isolates from 703 women, the median duration of follow-up for each genotyped recurrence (interquartile range) was 129 (83–174) days, with 429 polymerase chain reaction–confirmed recrudescent. Five different treatments were evaluated, and 382 Plasmodium falciparum recrudescences were identified as eligible. With log-logistic models adjusted for baseline parasitemia, the predicted cumulative proportions of all the recrudescences that were detected by 28 days were 70% (95% confidence interval [CI], 65%–74%) for quinine monotherapy (n = 295), 66% (95% CI, 53%–76%) for artesunate monotherapy (n = 43), 62% (95% CI, 42%–79%) for artemether–lumefantrine (AL; n = 19), 46% (95% CI, 26%–67%) for artesunate with clindamycin (n = 19), and 34% (95% CI, 11%–67%) for dihydroartemisinin–piperaquine (DP; n = 6). Corresponding figures by day 42 were 89% (95% CI, 77%–95%) for AL and 71% (95% CI, 38%–91%) for DP. Follow-up for 63 days was predicted to detect ≥95% of all recrudescence, except for DP.

Conclusions

In low-transmission settings, antimalarial drug efficacy assessments in pregnancy require longer follow-up than for nonpregnant populations.

Five rules for resistance management in the antibiotic apocalypse, a road map for integrated microbial management

Resistance to new antimicrobials can become widespread within 2-3 years. Resistance problems are particularly acute for bacteria that can experience selection as both harmless commensals and pathogenic hospital-acquired infections. New drugs, although welcome, cannot tackle the antimicrobial resistance crisis alone: new drugs must be partnered with more sustainable patterns of use. However, the broader experience of resistance management in other disciplines, and the assumptions on which resistance rests, is not widely appreciated in clinical and microbiological disciplines. Improved awareness of the field of resistance management could improve clinical outcomes and help shape novel solutions. Here, the aim is to develop a pragmatic approach to developing a sustainable integrated means of using antimicrobials, based on an interdisciplinary synthesis of best practice, recent theory and recent clinical data. This synthesis emphasizes the importance of pre-emptive action and the value of reducing the supply of genetic novelty to bacteria under selection. The weight of resistance management experience also cautions against strategies that over-rely on the fitness costs of resistance or low doses. The potential (and pitfalls) of shorter courses, antibiotic combinations and antibiotic mixing or cycling are discussed in depth. Importantly, some of variability in the success of clinical trials of mixing approaches can be explained by the number and diversity of drugs in a trial, as well as whether trials encompass single wards or the wider transmission network that is a hospital. Consideration of the importance of data, and of the initially low frequency of resistance, leads to a number of additional recommendations. Overall, reduction in selection pressure, interference with the transmission of problematic genotypes and multidrug approaches (combinations, mixing or cycling) are all likely to be required for sustainability and the protection of forthcoming drugs.

Population Pharmacokinetics of Mefloquine Intermittent Preventive Treatment for Malaria in Pregnancy in Gabon

Mefloquine was evaluated as an alternative for intermittent preventive treatment of malaria in pregnancy (IPTp) due to increasing resistance against the first-line drug sulfadoxine-pyrimethamine (SP). This study determined the pharmacokinetic characteristics of the mefloquine stereoisomers and the metabolite carboxymefloquine (CMQ) when given as IPTp in pregnant women. Also, the relationship between plasma concentrations of the three analytes and cord samples was evaluated, and potential covariates influencing the pharmacokinetic properties were assessed. A population pharmacokinetic analysis was performed with 264 pregnant women from a randomized controlled trial evaluating a single and a split-dose regimen of two 15-mg/kg mefloquine doses at least 1 month apart versus SP-IPTp. Both enantiomers of mefloquine and its carboxy-metabolite (CMQ), measured in plasma and cord samples, were applied for pharmacokinetic modelling using NONMEM 7.3. Both enantiomers and CMQ were described simultaneously by two-compartment models. In the split-dose group, mefloquine bioavailability was significantly increased by 5%. CMQ induced its own metabolism significantly. Maternal and cord blood concentrations were significantly correlated (r ² = 0.84) at delivery. With the dosing regimens investigated, prophylactic levels are not constantly achieved. A modeling tool for simulation of the pharmacokinetics of alternative mefloquine regimens is presented. This first pharmacokinetic characterization of mefloquine IPTp indicates adequate exposure in both mefloquine regimens; however, concentrations at delivery were below previously suggested threshold levels. Our model can serve as a valuable tool for researchers and clinicians to develop and optimize alternative dosing regimens for IPTp in pregnant women.

Pharmacokinetics of mefloquine administered with artesunate in patients with uncomplicated falciparum malaria from the Brazilian Amazon basin

Background

A fixed-dose combination of mefloquine with artesunate was evaluated in cases of falciparum malaria in the Brazilian Amazon basin with acceptable efficacy, safety and tolerability. However, there are no data on the pharmacokinetics of mefloquine in this coformulation in Brazil, which is valuable to evaluate whether Plasmodium is exposed to an effective concentration of the drug.

Methods

A prospective, single-arm study was conducted in male patients with slide-confirmed infection by Plasmodium falciparum using two tablets of a fixed-dose combination of artesunate (100 mg) and mefloquine base (200 mg) once daily and over 3 consecutive days. Serial blood samples were collected at admission and throughout 672 h post-administration of the drugs. Mefloquine was measured in each blood sample by high-performance liquid chromatography. The pharmacokinetic parameters were determined by non-compartmental analysis.

Results

A total of 61 patients were enrolled in the study and 450 whole blood samples were collected for mefloquine measurement. The mefloquine half-life was 10.25 days, the maximum concentration (C_max) was 2.53 µg/ml, the area-under-the-curve (AUC_0–∞) was 359 µg^/ml h, the observed clearance (Cl/f) was 0.045 l/kg/h and the volume of distribution (V/f) was 14.6 l/kg. Mefloquine concentrations above 0.5 µg/ml were sustained for a mean time of 9.2 days.

Conclusion

The pharmacokinetic parameters of mefloquine determined in the study suggest an adequate exposure of parasite to mefloquine in the multiple oral dose regimen of the fixed dose combination of mefloquine and artesunate.

Effectiveness and safety of 3 and 5 day courses of artemether-lumefantrine for the treatment of uncomplicated falciparum malaria in an area of emerging artemisinin resistance in Myanmar

BACKGROUND

Artemisinin resistance in Plasmodium falciparum has emerged and spread in Southeast Asia. In areas where resistance is established longer courses of artemisinin-based combination therapy have improved cure rates.

METHODS

The standard 3-day course of artemether-lumefantrine (AL) was compared with an extended 5-day regimen for the treatment of uncomplicated falciparum malaria in Kayin state in South-East Myanmar, an area of emerging artemisinin resistance. Late parasite clearance dynamics were described by microscopy and quantitative ultra-sensitive PCR. Patients were followed up for 42 days.

RESULTS

Of 154 patients recruited (105 adults and 49 children < 14 years) 78 were randomized to 3 days and 76 to 5 days AL. Mutations in the P. falciparum kelch13 propeller gene (k13) were found in 46% (70/152) of infections, with F446I the most prevalent propeller mutation (29%; 20/70). Both regimens were well-tolerated. Parasite clearance profiles were biphasic with a slower submicroscopic phase which was similar in k13 wild-type and mutant infections. The cure rates were 100% (70/70) and 97% (68/70) in the 3- and 5-day arms respectively. Genotyping of the two recurrences was unsuccessful.

CONCLUSION

Despite a high prevalence of k13 mutations, the current first-line treatment, AL, was still highly effective in this area of South-East Myanmar. The extended 5 day regimen was very well tolerated, and would be an option to prolong the useful therapeutic life of AL. Trial registration NCT02020330. Registered 24 December 2013, https://clinicaltrials.gov/NCT02020330.

Characterizing Blood-Stage Antimalarial Drug MIC Values In Vivo Using Reinfection Patterns

The MIC is an essential quantitative measure of the asexual blood-stage effect of an antimalarial drug. In areas of high malaria transmission, and thus frequent individual infection, patients who are treated with slowly eliminated antimalarials become reinfected as drug concentrations decline. In the frequent relapse forms of Plasmodium vivax and in Plasmodium ovale malaria, recurrent infection occurs from relapses which begin to emerge from the liver approximately 2 weeks after the primary illness. An important determinant of the interval from starting treatment of a symptomatic infection to the patency of these recurrent infections is the in vivo concentration-response relationship and thus the in vivo MIC. Using mechanistic knowledge of parasite asexual replication and the pharmacokinetic and pharmacodynamic properties of the antimalarial drugs, a generative statistical model was derived which relates the concentration-response relationship to time of reinfection patency. This model was used to estimate the in vivo MIC of chloroquine in the treatment of Plasmodium vivax malaria.

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.

The Impact of Antimalarial Use on the Emergence and Transmission of Plasmodium falciparum Resistance: A Scoping Review of Mathematical Models

The emergence and transmission of resistance to antimalarial treatments continue to hamper malaria elimination efforts. A scoping review was undertaken regarding the impact of antimalarial treatment in the human population on the emergence and transmission of Plasmodium falciparum resistance, to (i) describe the use of mathematical models used to explore this relationship; (ii) discuss model findings; and (iii) identify factors influencing the emergence and transmission of resistance. Search strategies were developed and deployed in six major databases. Thirty-seven articles met the eligibility criteria and were included in the review: nine articles modeled the emergence of resistance, 19 modeled the transmission of resistance, and nine modeled both the emergence and transmission. The proportion of antimalarial use within the population and the presence of residual drug concentrations were identified to be the main predictors of the emergence and transmission of resistance. Influencing factors pertaining to the human, parasite and mosquito populations are discussed. To ensure the prolonged therapeutic usefulness of antimalarial treatments, the effect of antimalarial drug use on the emergence and transmission of resistance must be understood, and mathematical models are a useful tool for exploring these dynamics.

Modelling the impact of antimalarial quality on the transmission of sulfadoxine-pyrimethamine resistance in Plasmodium falciparum

Background

The use of poor quality antimalarial medicines, including the use of non-recommended medicines for treatment such as sulfadoxine-pyrimethamine (SP) monotherapy, undermines malaria control and elimination efforts. Furthermore, the use of subtherapeutic doses of the active ingredient(s) can theoretically promote the emergence and transmission of drug resistant parasites.

Methods

We developed a deterministic compartmental model to quantify the impact of antimalarial medicine quality on the transmission of SP resistance, and validated it using sensitivity analysis and a comparison with data from Kenya collected in 2006. We modelled human and mosquito population dynamics, incorporating two Plasmodium falciparum subtypes (SP-sensitive and SP-resistant) and both poor quality and good quality (artemether-lumefantrine) antimalarial use.

Findings

The model predicted that an increase in human malaria cases, and among these, an increase in the proportion of SP-resistant infections, resulted from an increase in poor quality SP antimalarial use, whether it was full- or half-dose SP monotherapy.

Interpretation

Our findings suggest that an increase in poor quality antimalarial use predicts an increase in the transmission of resistance. This highlights the need for stricter control and regulation on the availability and use of poor quality antimalarial medicines, in order to offer safe and effective treatments, and work towards the eradication of malaria.

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.

Malaria parasite clearance

Following anti-malarial drug treatment asexual malaria parasite killing and clearance appear to be first order processes. Damaged malaria parasites in circulating erythrocytes are removed from the circulation mainly by the spleen. Splenic clearance functions increase markedly in acute malaria. Either the entire infected erythrocytes are removed because of their reduced deformability or increased antibody binding or, for the artemisinins which act on young ring stage parasites, splenic pitting of drug-damaged parasites is an important mechanism of clearance. The once-infected erythrocytes returned to the circulation have shortened survival. This contributes to post-artesunate haemolysis that may follow recovery in non-immune hyperparasitaemic patients. As the parasites mature Plasmodium vivax-infected erythrocytes become more deformable, whereas Plasmodium falciparum-infected erythrocytes become less deformable, but they escape splenic filtration by sequestering in venules and capillaries. Sequestered parasites are killed in situ by anti-malarial drugs and then disintegrate to be cleared by phagocytic leukocytes. After treatment with artemisinin derivatives some asexual parasites become temporarily dormant within their infected erythrocytes, and these may regrow after anti-malarial drug concentrations decline. Artemisinin resistance in P. falciparum reflects reduced ring stage susceptibility and manifests as slow parasite clearance. This is best assessed from the slope of the log-linear phase of parasitaemia reduction and is commonly measured as a parasite clearance half-life. Pharmacokinetic-pharmacodynamic modelling of anti-malarial drug effects on parasite clearance has proved useful in predicting therapeutic responses and in dose-optimization.

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.

Linking Murine and Human Plasmodium falciparum Challenge Models in a Translational Path for Antimalarial Drug Development

Effective progression of candidate antimalarials is dependent on optimal dosing in clinical studies, which is determined by a sound understanding of pharmacokinetics and pharmacodynamics (PK/PD). Recently, two important translational models for antimalarials have been developed: the NOD/SCID/IL2Rγ^−/− (NSG) model, whereby mice are engrafted with noninfected and Plasmodium falciparum-infected human erythrocytes, and the induced blood-stage malaria (IBSM) model in human volunteers. The antimalarial mefloquine was used to directly measure the PK/PD in both models, which were compared to previously published trial data for malaria patients. The clinical part was a single-center, controlled study using a blood-stage Plasmodium falciparum challenge inoculum in volunteers to characterize the effectiveness of mefloquine against early malaria. The study was conducted in three cohorts (n = 8 each) using different doses of mefloquine. The characteristic delay in onset of action of about 24 h was seen in both NSG and IBSM systems. In vivo 50% inhibitory concentrations (IC₅₀s) were estimated at 2.0 μg/ml and 1.8 μg/ml in the NSG and IBSM models, respectively, aligning with 1.8 μg/ml reported previously for patients. In the IBSM model, the parasite reduction ratios were 157 and 195 for the 10- and 15-mg/kg doses, within the range of previously reported clinical data for patients but significantly lower than observed in the mouse model. Linking mouse and human challenge models to clinical trial data can accelerate the accrual of critical data on antimalarial drug activity. Such data can guide large clinical trials required for development of urgently needed novel antimalarial combinations. (This trial was registered at the Australian New Zealand Clinical Trials Registry [http://anzctr.org.au] under registration number ACTRN12612000323820.)

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.

Designing a Pediatric Study for an Antimalarial Drug by Using Information from Adults

The objectives of this study were to design a pharmacokinetic (PK) study by using information about adults and evaluate the robustness of the recommended design through a case study of mefloquine. PK data about adults and children were available from two different randomized studies of the treatment of malaria with the same artesunate-mefloquine combination regimen. A recommended design for pediatric studies of mefloquine was optimized on the basis of an extrapolated model built from adult data through the following approach. (i) An adult PK model was built, and parameters were estimated by using the stochastic approximation expectation-maximization algorithm. (ii) Pediatric PK parameters were then obtained by adding allometry and maturation to the adult model. (iii) A D-optimal design for children was obtained with PFIM by assuming the extrapolated design. Finally, the robustness of the recommended design was evaluated in terms of the relative bias and relative standard errors (RSE) of the parameters in a simulation study with four different models and was compared to the empirical design used for the pediatric study. Combining PK modeling, extrapolation, and design optimization led to a design for children with five sampling times. PK parameters were well estimated by this design with few RSE. Although the extrapolated model did not predict the observed mefloquine concentrations in children very accurately, it allowed precise and unbiased estimates across various model assumptions, contrary to the empirical design. Using information from adult studies combined with allometry and maturation can help provide robust designs for pediatric studies.

Altering Antimalarial Drug Regimens May Dramatically Enhance and Restore Drug Effectiveness

There is considerable concern that malaria parasites are starting to evolve resistance to the current generation of antimalarial drugs, the artemisinin-based combination therapies (ACTs). We use pharmacological modeling to investigate changes in ACT effectiveness likely to occur if current regimens are extended from 3 to 5 days or, alternatively, given twice daily over 3 days. We show that the pharmacology of artemisinins allows both regimen changes to substantially increase the artemisinin killing rate. Malaria patients rarely contain more than 10(12) parasites, while the standard dosing regimens allow approximately 1 in 10(10) parasites to survive artemisinin treatment. Parasite survival falls dramatically, to around 1 in 10(17) parasites if the dose is extended or split; theoretically, this increase in drug killing appears to be more than sufficient to restore failing ACT efficacy. One of the most widely used dosing regimens, artemether-lumefantrine, already successfully employs a twice-daily dosing regimen, and we argue that twice-daily dosing should be incorporated into all ACT regimen design considerations as a simple and effective way of ensuring the continued long-term effectiveness of ACTs.

Triaminopyrimidine is a fast-killing and long-acting antimalarial clinical candidate

The widespread emergence of Plasmodium falciparum (Pf) strains resistant to frontline agents has fuelled the search for fast-acting agents with novel mechanism of action. Here, we report the discovery and optimization of novel antimalarial compounds, the triaminopyrimidines (TAPs), which emerged from a phenotypic screen against the blood stages of Pf. The clinical candidate (compound 12) is efficacious in a mouse model of Pf malaria with an ED₉₉ <30 mg kg⁻¹ and displays good in vivo safety margins in guinea pigs and rats. With a predicted half-life of 36 h in humans, a single dose of 260 mg might be sufficient to maintain therapeutic blood concentration for 4–5 days. Whole-genome sequencing of resistant mutants implicates the vacuolar ATP synthase as a genetic determinant of resistance to TAPs. Our studies highlight the potential of TAPs for single-dose treatment of Pf malaria in combination with other agents in clinical development.

The emergence of resistant Plasmodium strains fuels the search for new antimalarials. Here, the authors present a new class of potent antimalarial compounds, the triaminopyrimidines, that display low toxicity and long half-life in animal models.

Mass campaigns with antimalarial drugs: a modelling comparison of artemether-lumefantrine and DHA-piperaquine with and without primaquine as tools for malaria control and elimination

Background

Antimalarial drugs are a powerful tool for malaria control and elimination. Artemisinin-based combination therapies (ACTs) can reduce transmission when widely distributed in a campaign setting. Modelling mass antimalarial campaigns can elucidate how to most effectively deploy drug-based interventions and quantitatively compare the effects of cure, prophylaxis, and transmission-blocking in suppressing parasite prevalence.

Methods

A previously established agent-based model that includes innate and adaptive immunity was used to simulate malaria infections and transmission. Pharmacokinetics of artemether, lumefantrine, dihydroartemisinin, piperaquine, and primaquine were modelled with a double-exponential distribution-elimination model including weight-dependent parameters and age-dependent dosing. Drug killing of asexual parasites and gametocytes was calibrated to clinical data. Mass distribution of ACTs and primaquine was simulated with seasonal mosquito dynamics at a range of transmission intensities.

Results

A single mass campaign with antimalarial drugs is insufficient to permanently reduce malaria prevalence when transmission is high. Current diagnostics are insufficiently sensitive to accurately identify asymptomatic infections, and mass-screen-and-treat campaigns are much less efficacious than mass drug administrations. Improving campaign coverage leads to decreased prevalence one month after the end of the campaign, while increasing compliance lengthens the duration of protection against reinfection. Use of a long-lasting prophylactic as part of a mass drug administration regimen confers the most benefit under conditions of high transmission and moderately high coverage. Addition of primaquine can reduce prevalence but exerts its largest effect when coupled with a long-lasting prophylactic.

Conclusions

Mass administration of antimalarial drugs can be a powerful tool to reduce prevalence for a few months post-campaign. A slow-decaying prophylactic administered with a parasite-clearing drug offers strong protection against reinfection, especially in highly endemic areas. Transmission-blocking drugs have only limited effects unless administered with a prophylactic under very high coverage.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-015-0887-y) 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.

The practice and clinical implications of tablet splitting in international health

Objective

Tablet splitting is frequently performed to facilitate correct dosing, but the practice and implications in low-income settings have rarely been discussed.

Methods

We selected eight drugs, with narrow therapeutic indices or critical dosages, frequently divided in the Lao PDR (Laos). These were split, by common techniques used in Laos, by four nurses and four laypersons. The mean percentage deviation from the theoretical expected weight and weight loss of divided tablets/capsules were recorded.

Results

Five of eight study drugs failed, on splitting, to meet European Pharmacopoeia recommendations for tablet weight deviation from the expected weight of tablet/capsule halves with 10% deviating by more than 25%. There was a significant difference in splitting accuracy between nurses and laypersons (P = 0.027). Coated and unscored tablets were less accurately split than uncoated (P = 0.03 and 0.0019 for each half) and scored (0.0001 for both halves) tablets.

Conclusion

These findings have potential clinical implications on treatment outcome and the development of antimicrobial resistance. Investment by drug companies in a wider range of dosage units, particularly for narrow therapeutic index and critical dosage medicines, is strongly recommended.

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.

Pharmacological considerations in the design of anti-malarial drug combination therapies - is matching half-lives enough?

Anti-malarial drugs are now mainly deployed as combination therapy (CT), primarily as a mechanism to prevent or slow the spread of resistance. This strategy is justified by mathematical arguments that generally assume that drug 'resistance' is a binary all-or-nothing genetic trait. Herein, a pharmacological, rather than a purely genetic, approach is used to investigate resistance and it is argued that this provides additional insight into the design principles of anti-malarial CTs. It is usually suggested that half-lives of constituent drugs in a CT be matched: it appears more important that their post-treatment anti-malarial activity profiles be matched and strategies identified that may achieve this. In particular, the considerable variation in pharmacological parameters noted in both human and parasites populations may compromise this matching and it is, therefore, essential to accurately quantify the population pharmacokinetics of the drugs in the CTs. Increasing drug dosages will likely follow a law of diminishing returns in efficacy, i.e. a certain increase in dose will not necessarily lead to the same percent increase in efficacy. This may allow individual drug dosages to be lowered without proportional decrease in efficacy, reducing any potential toxicity, and allowing the other drug(s) in the CT to compensate for this reduced dosage; this is a dangerous strategy which is discussed further. Finally, pharmacokinetic and pharmacodynamic drug interactions and the role of resistance mechanisms are discussed. This approach generated an idealized target product profile (TPP) for anti-malarial CTs. There is a restricted pipeline of anti-malarial drugs but awareness of pharmacological design principles during the development stages could optimize CT design pre-deployment. This may help prevent changes in drug dosages and/or regimen that have previously occurred post-deployment in most current anti-malarial drugs.

Modeling within-host effects of drugs on Plasmodium falciparum transmission and prospects for malaria elimination

Achieving a theoretical foundation for malaria elimination will require a detailed understanding of the quantitative relationships between patient treatment-seeking behavior, treatment coverage, and the effects of curative therapies that also block Plasmodium parasite transmission to mosquito vectors. Here, we report a mechanistic, within-host mathematical model that uses pharmacokinetic (PK) and pharmacodynamic (PD) data to simulate the effects of artemisinin-based combination therapies (ACTs) on Plasmodium falciparum transmission. To contextualize this model, we created a set of global maps of the fold reductions that would be necessary to reduce the malaria R C (i.e. its basic reproductive number under control) to below 1 and thus interrupt transmission. This modeling was applied to low-transmission settings, defined as having a R 0<10 based on 2010 data. Our modeling predicts that treating 93-98% of symptomatic infections with an ACT within five days of fever onset would interrupt malaria transmission for ∼91% of the at-risk population of Southeast Asia and ∼74% of the global at-risk population, and lead these populations towards malaria elimination. This level of treatment coverage corresponds to an estimated 81-85% of all infected individuals in these settings. At this coverage level with ACTs, the addition of the gametocytocidal agent primaquine affords no major gains in transmission reduction. Indeed, we estimate that it would require switching ∼180 people from ACTs to ACTs plus primaquine to achieve the same transmission reduction as switching a single individual from untreated to treated with ACTs. Our model thus predicts that the addition of gametocytocidal drugs to treatment regimens provides very small population-wide benefits and that the focus of control efforts in Southeast Asia should be on increasing prompt ACT coverage. Prospects for elimination in much of Sub-Saharan Africa appear far less favorable currently, due to high rates of infection and less frequent and less rapid treatment.

Optimal sampling designs for estimation of Plasmodium falciparum clearance rates in patients treated with artemisinin derivatives

BACKGROUND

The emergence of Plasmodium falciparum resistance to artemisinins in Southeast Asia threatens the control of malaria worldwide. The pharmacodynamic hallmark of artemisinin derivatives is rapid parasite clearance (a short parasite half-life), therefore, the in vivo phenotype of slow clearance defines the reduced susceptibility to the drug. Measurement of parasite counts every six hours during the first three days after treatment have been recommended to measure the parasite clearance half-life, but it remains unclear whether simpler sampling intervals and frequencies might also be sufficient to reliably estimate this parameter.

METHODS

A total of 2,746 parasite density-time profiles were selected from 13 clinical trials in Thailand, Cambodia, Mali, Vietnam, and Kenya. In these studies, parasite densities were measured every six hours until negative after treatment with an artemisinin derivative (alone or in combination with a partner drug). The WWARN Parasite Clearance Estimator (PCE) tool was used to estimate "reference" half-lives from these six-hourly measurements. The effect of four alternative sampling schedules on half-life estimation was investigated, and compared to the reference half-life (time zero, 6, 12, 24 (A1); zero, 6, 18, 24 (A2); zero, 12, 18, 24 (A3) or zero, 12, 24 (A4) hours and then every 12 hours). Statistical bootstrap methods were used to estimate the sampling distribution of half-lives for parasite populations with different geometric mean half-lives. A simulation study was performed to investigate a suite of 16 potential alternative schedules and half-life estimates generated by each of the schedules were compared to the "true" half-life. The candidate schedules in the simulation study included (among others) six-hourly sampling, schedule A1, schedule A4, and a convenience sampling schedule at six, seven, 24, 25, 48 and 49 hours.

RESULTS

The median (range) parasite half-life for all clinical studies combined was 3.1 (0.7-12.9) hours. Schedule A1 consistently performed the best, and schedule A4 the worst, both for the individual patient estimates and for the populations generated with the bootstrapping algorithm. In both cases, the differences between the reference and alternative schedules decreased as half-life increased. In the simulation study, 24-hourly sampling performed the worst, and six-hourly sampling the best. The simulation study confirmed that more dense parasite sampling schedules are required to accurately estimate half-life for profiles with short half-life (≤ three hours) and/or low initial parasite density (≤ 10,000 per μL). Among schedules in the simulation study with six or fewer measurements in the first 48 hours, a schedule with measurements at times (time windows) of 0 (0-2), 6 (4-8), 12 (10-14), 24 (22-26), 36 (34-36) and 48 (46-50) hours, or at times 6, 7 (two samples in time window 5-8), 24, 25 (two samples during time 23-26), and 48, 49 (two samples during time 47-50) hours, until negative most accurately estimated the "true" half-life. For a given schedule, continuing sampling after two days had little effect on the estimation of half-life, provided that adequate sampling was performed in the first two days and the half-life was less than three hours. If the measured parasitaemia at two days exceeded 1,000 per μL, continued sampling for at least once a day was needed for accurate half-life estimates.

CONCLUSIONS

This study has revealed important insights on sampling schedules for accurate and reliable estimation of Plasmodium falciparum half-life following treatment with an artemisinin derivative (alone or in combination with a partner drug). Accurate measurement of short half-lives (rapid clearance) requires more dense sampling schedules (with more than twice daily sampling). A more intensive sampling schedule is, therefore, recommended in locations where P. falciparum susceptibility to artemisinins is not known and the necessary resources are available. Counting parasite density at six hours is important, and less frequent sampling is satisfactory for estimating long parasite half-lives in areas where artemisinin resistance is present.

Accessible mutational trajectories for the evolution of pyrimethamine resistance in the malaria parasite Plasmodium vivax

Antifolate antimalarials, such as pyrimethamine, have experienced a dramatic reduction in therapeutic efficacy as resistance has evolved in multiple malaria species. We present evidence from one such species, Plasmodium vivax, which has experienced sustained selection for pyrimethamine resistance at the dihydrofolate reductase (DHFR) locus since the 1970s. Using a transgenic Saccharomyces cerevisiae model expressing the P. vivax DHFR enzyme, we assayed growth rate and resistance of all 16 combinations of four DHFR amino acid substitutions. These substitutions were selected based on their known association with drug resistance, both in natural isolates and in laboratory settings, in the related malaria species P. falciparum. We observed a strong correlation between the resistance phenotypes for these 16 P. vivax alleles and previously observed resistance data for P. falciparum, which was surprising since nucleotide diversity levels and common polymorphic variants of DHFR differ between the two species. Similar results were observed when we expressed the P. vivax alleles in a transgenic bacterial system. This suggests common constraints on enzyme evolution in the orthologous DHFR proteins. The interplay of negative trade-offs between the evolution of novel resistance and compromised endogenous function varies at different drug dosages, and so too do the major trajectories for DHFR evolution. In simulations, it is only at very high drug dosages that the most resistant quadruple mutant DHFR allele is favored by selection. This is in agreement with common polymorphic DHFR data in P. vivax, from which this quadruple mutant is missing. We propose that clinical dosages of pyrimethamine may have historically been too low to select for the most resistant allele, or that the fitness cost of the most resistant allele was untenable without a compensatory mutation elsewhere in the genome.

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.

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.

High-throughput analysis of antimalarial susceptibility data by the WorldWide Antimalarial Resistance Network (WWARN) in vitro analysis and reporting tool

Assessment of in vitro susceptibility is a fundamental component of antimalarial surveillance studies, but wide variations in the measurement of parasite growth and the calculation of inhibitory constants make comparisons of data from different laboratories difficult. Here we describe a Web-based, high-throughput in vitro analysis and reporting tool (IVART) generating inhibitory constants for large data sets. Fourteen primary data sets examining laboratory-determined susceptibility to artemisinin derivatives and artemisinin combination therapy partner drugs were collated from 11 laboratories. Drug concentrations associated with half-maximal inhibition of growth (IC50s) were determined by a modified sigmoid Emax model-fitting algorithm, allowing standardized analysis of 7,350 concentration-inhibition assays involving 1,592 isolates. Examination of concentration-inhibition data revealed evidence of apparent paradoxical growth at high concentrations of nonartemisinin drugs, supporting amendment of the method for calculating the maximal drug effect in each assay. Criteria for defining more-reliable IC50s based on estimated confidence intervals and growth ratios improved correlation coefficients for the drug pairs mefloquine-quinine and chloroquine-desethylamodiaquine in 9 of 11 and 8 of 8 data sets, respectively. Further analysis showed that maximal drug inhibition was higher for artemisinins than for other drugs, particularly in ELISA (enzyme-linked immunosorbent assay)-based assays, a finding consistent with the earlier onset of action of these drugs in the parasite life cycle. This is the first high-throughput analytical approach to apply consistent constraints and reliability criteria to large, diverse antimalarial susceptibility data sets. The data also illustrate the distinct biological properties of artemisinins and underline the need to apply more sensitive approaches to assessing in vitro susceptibility to these drugs.

Mechanism-based model of parasite growth and dihydroartemisinin pharmacodynamics in murine malaria

Murine models are used to study erythrocytic stages of malaria infection, because parasite morphology and development are comparable to those in human malaria infections. Mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) models for antimalarials are scarce, despite their potential to optimize antimalarial combination therapy. The aim of this study was to develop a mechanism-based growth model (MBGM) for Plasmodium berghei and then characterize the parasiticidal effect of dihydroartemisinin (DHA) in murine malaria (MBGM-PK-PD). Stage-specific (ring, early trophozoite, late trophozoite, and schizont) parasite density data from Swiss mice inoculated with Plasmodium berghei were used for model development in S-ADAPT. A single dose of intraperitoneal DHA (10 to 100 mg/kg) or vehicle was administered 56 h postinoculation. The MBGM explicitly reflected all four erythrocytic stages of the 24-hour P. berghei life cycle. Merozoite invasion of erythrocytes was described by a first-order process that declined with increasing parasitemia. An efflux pathway with subsequent return was additionally required to describe the schizont data, thus representing parasite sequestration or trapping in the microvasculature, with a return to circulation. A 1-compartment model with zero-order absorption described the PK of DHA, with an estimated clearance and distribution volume of 1.95 liters h(-1) and 0.851 liter, respectively. Parasite killing was described by a turnover model, with DHA inhibiting the production of physiological intermediates (IC(50), 1.46 ng/ml). Overall, the MBGM-PK-PD described the rise in parasitemia, the nadir following DHA dosing, and subsequent parasite resurgence. This novel model is a promising tool for studying malaria infections, identifying the stage specificity of antimalarials, and providing insight into antimalarial treatment strategies.

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

Background

Mechanistic within-host models relating blood anti-malarial drug concentrations with the parasite-time profile help in assessing dosing schedules and partner drugs for new anti-malarial treatments. A comprehensive simulation study to assess the utility of a stage-specific pharmacokinetic-pharmacodynamic (PK-PD) model for predicting within-host parasite response was performed.

Methods

Three anti-malarial combination therapies were selected: artesunate-mefloquine, dihydroartemisinin-piperaquine, and artemether-lumefantrine. The PK-PD model included parameters to represent the concentration-time profiles of both drugs, the initial parasite burden and distribution across the parasite life cycle, and the parasite multiplication factor due to asexual reproduction. The model also included the maximal killing rate of each drug, and the blood drug concentration associated with half of that killing effect (in vivo EC50), derived from the in vitro IC50, the extent of binding to 0.5% Albumax present in the in vitro testing media, and the drugs plasma protein binding and whole blood to plasma partitioning ratio. All stochastic simulations were performed using a Latin-Hypercube-Sampling approach.

Results

The simulations demonstrated that the proportion of patients cured was highly sensitive to the in vivo EC50 and the maximal killing rate of the partner drug co-administered with the artemisinin derivative. The in vivo EC50 values that corresponded to on average 95% of patients cured were much higher than the adjusted values derived from the in vitro IC50. The proportion clinically cured was not strongly influenced by changes in the parameters defining the age distribution of the initial parasite burden (mean age of 4 to 16 hours) and the parasite multiplication factor every life cycle (ranging from 8 to 12 fold/cycle). The median parasite clearance times, however, lengthened as the standard deviation of the initial parasite burden increased (i.e. the infection became more asynchronous).

Conclusions

This simulation study demonstrates that the PD effect predicted from in vitro growth inhibition assays does not accord well with the PD effect of the anti-malarials observed within the patient. This simulation-based PK-PD modelling approach should not be considered as a replacement to conducting clinical trials but instead as a decision tool to improve the design of a clinical trial during drug development.

Effect of artesunate-mefloquine fixed-dose combination in malaria transmission in Amazon basin communities

Background

Studies in South-East Asia have suggested that early diagnosis and treatment with artesunate (AS) and mefloquine (MQ) combination therapy may reduce the transmission of Plasmodium falciparum malaria and the progression of MQ resistance.

Methods

The effectiveness of a fixed-dose combination of AS and MQ (ASMQ) in reducing malaria transmission was tested in isolated communities of the Juruá valley in the Amazon region.

Priority municipalities within the Brazilian Legal Amazon area were selected according to pre-specified criteria. Routine national malaria control programmatic procedures were followed. Existing health structures were reinforced and health care workers were trained to treat with ASMQ all confirmed falciparum malaria cases that match inclusion criteria. A local pharmacovigilance structure was implemented. Incidence of malaria and hospitalizations were recorded two years before, during, and after the fixed-dose ASMQ intervention. In total, between July 2006 and December 2008, 23,845 patients received ASMQ. Two statistical modelling approaches were applied to monthly time series of P. falciparum malaria incidence rates, P. falciparum/Plasmodium vivax infection ratio, and malaria hospital admissions rates. All the time series ranged from January 2004 to December 2008, whilst the intervention period span from July 2006 to December 2008.

Results

The ASMQ intervention had a highly significant impact on the mean level of each time series, adjusted for trend and season, of 0.34 (95%CI 0.20 – 0.58) for the P. falciparum malaria incidence rates, 0.67 (95%CI 0.50 – 0.89) for the P. falciparum/P. vivax infection ratio, and 0.53 (95%CI 0.41 – 0.69) for the hospital admission rates. There was also a significant change in the seasonal (or monthly) pattern of the time series before and after intervention, with the elimination of the malaria seasonal peak in the rainy months of the years following the introduction of ASMQ. No serious adverse events relating to the use of fixed-dose ASMQ were reported.

Conclusions

In the remote region of the Juruá valley, the early detection of malaria by health care workers and treatment with fixed-dose ASMQ was feasible and efficacious, and significantly reduced the incidence and morbidity of P. falciparum malaria.

Pyronaridine-artesunate versus mefloquine plus artesunate for malaria

BACKGROUND

Pyronaridine-artesunate is an artemisinin-based combination therapy under evaluation for the treatment of Plasmodium falciparum and P. vivax malaria.

METHODS

We conducted a phase 3, open-label, multicenter, noninferiority trial that included 1271 patients between 3 and 60 years of age from Asia (81.3%) or Africa (18.7%) with microscopically confirmed, uncomplicated P. falciparum malaria. Patients underwent randomization for treatment with a fixed-dose combination of 180 mg of pyronaridine and 60 mg of artesunate or with 250 mg of mefloquine plus 100 mg of artesunate. Doses were calculated according to body weight and administered once daily for 3 days.

RESULTS

Pyronaridine-artesunate was noninferior to mefloquine plus artesunate for the primary outcome: adequate clinical and parasitologic response in the per-protocol population on day 28, corrected for reinfection with the use of polymerase-chain-reaction (PCR) genotyping. For this outcome, efficacy in the group receiving pyronaridine-artesunate was 99.2% (743 of 749 patients; 95% confidence interval [CI], 98.3 to 99.7) and that in the group receiving mefloquine plus artesunate was 97.8% (360 of 368 patients; 95% CI, 95.8 to 99.1), with a treatment difference of 1.4 percentage points (95% CI, 0.0 to 3.5; P=0.05). In the intention-to-treat population, efficacy on day 42 in the group receiving pyronaridine-artesunate was 83.1% (705 of 848 patients; 95% CI, 80.4 to 85.6) and that in the group receiving mefloquine plus artesunate was 83.9% (355 of 423 patients; 95% CI, 80.1 to 87.3). In Cambodia, where there were 211 study patients, the median parasite clearance time was prolonged for both treatments: 64 hours versus 16.0 to 38.9 hours in other countries (P<0.001, on the basis of Kaplan-Meier estimates). Kaplan-Meier estimates of the recrudescence rate in the intention-to-treat population in Cambodia until day 42 were higher with pyronaridine-artesunate than with mefloquine plus artesunate (10.2% [95% CI, 5.4 to 18.6] vs. 0%; P=0.04 as calculated with the log-rank test), but similar for the other countries combined (4.7% [95% CI, 3.3 to 6.7] and 2.8% [95% CI, 1.5 to 5.3], respectively; P=0.24). Elevated levels of aminotransferases were observed in those receiving pyronaridine-artesunate. Two patients receiving mefloquine plus artesunate had seizures.

CONCLUSIONS

Fixed-dose pyronaridine-artesunate was efficacious in the treatment of uncomplicated P. falciparum malaria. In Cambodia, extended parasite clearance times were suggestive of in vivo resistance to artemisinin. (Funded by Shin Poong Pharmaceutical Company and the Medicines for Malaria Venture; ClinicalTrials.gov number, NCT00403260.).

Pharmacokinetics of ferroquine, a novel 4-aminoquinoline, in asymptomatic carriers of Plasmodium falciparum infections

Ferroquine (SSR97193), a ferrocene-quinoline conjugate, is a promising novel antimalarial currently undergoing clinical evaluation. This study characterizes its pharmacokinetic properties. Young male African volunteers with asymptomatic Plasmodium falciparum infection were administered a single oral dose (n = 40) or a repeated oral dose (n = 26) given over 3 days of ferroquine in two dose-escalation, double-blind, randomized, placebo-controlled clinical trials. In addition, a food interaction study was performed in a subsample of participants (n = 16). The studies were carried out in Lambaréné, Gabon. After single-dose administration of ferroquine, dose linearity was demonstrated in a dose range of 400 to 1,200 mg for maximum mean blood concentrations ([C(max)] 82 to 270 ng/ml) and in a dose range of 400 to 1,600 mg for overall exposure to ferroquine (area under the concentration-time curve [AUC], 13,100 to 49,200 ng · h/ml). Overall mean estimate for blood apparent terminal half-life of ferroquine was 16 days and 31 days for its active and major metabolite desmethylferroquine (SSR97213). In the 3-day repeated-dose study, C(max) and overall cumulated exposure to ferroquine (AUC(cum)) increased in proportion with the dose from day 1 to day 3 between 400 and 800 mg. No major food effect on ferroquine pharmacokinetics was observed after single administration of 100 mg of ferroquine except for a slight delay of time to maximum blood concentration (t(max)) by approximately 3 h. The pharmacokinetics of ferroquine and its active main metabolite are characterized by sustained levels in blood, and the properties of ferroquine as a partner drug in antimalarial combination therapy should be evaluated.

Challenges in antimalarial drug discovery

Malaria is one of the most devastating diseases in the world, affecting almost 225 million people a year, and causing over 780,000 deaths, most of which are children under the age of 5 years. Following the recent call for the eradication of the disease, supported by the WHO, there has been increasing investment into antimalarial drug-discovery projects. These activities are aimed at generating the next generation of molecules focused on the treatment and transmission-blocking of Plasmodium falciparum and Plasmodium vivax endo- and exo-erythrocytic stages of the parasite. This article summarizes the current top-level thinking regarding the prosecution of such endeavors and the disease-specific considerations in project planning.

Standardizing the measurement of parasite clearance in falciparum malaria: the parasite clearance estimator

Background

A significant reduction in parasite clearance rates following artesunate treatment of falciparum malaria, and increased failure rates following artemisinin combination treatments (ACT), signaled emergent artemisinin resistance in Western Cambodia. Accurate measurement of parasite clearance is therefore essential to assess the spread of artemisinin resistance in Plasmodium falciparum. The slope of the log-parasitaemia versus time relationship is considered to be the most robust measure of anti-malarial effect. However, an initial lag phase of numerical instability often precedes a steady exponential decline in the parasite count after the start of anti-malarial treatment. This lag complicates the clearance estimation, introduces observer subjectivity, and may influence the accuracy and consistency of reported results.

Methods

To address this problem, a new approach to modelling clearance of malaria parasites from parasitaemia-time profiles has been explored and validated. The methodology detects when a lag phase is present, selects the most appropriate model (linear, quadratic or cubic) to fit log-transformed parasite data, and calculates estimates of parasite clearance adjusted for this lag phase. Departing from previous approaches, parasite counts below the level of detection are accounted for and not excluded from the calculation.

Results

Data from large clinical studies with frequent parasite counts were examined. The effect of a lag phase on parasite clearance rate estimates is discussed, using individual patient data examples. As part of the World Wide Antimalarial Resistance Network's (WWARN) efforts to make innovative approaches available to the malaria community, an automated informatics tool: the parasite clearance estimator has been developed.

Conclusions

The parasite clearance estimator provides a consistent, reliable and accurate method to estimate the lag phase and malaria parasite clearance rate. It could be used to detect early signs of emerging resistance to artemisinin derivatives and other compounds which affect ring-stage clearance.

Population biological principles of drug-resistance evolution in infectious diseases

The emergence of resistant pathogens in response to selection pressure by drugs and their possible disappearance when drug use is discontinued are evolutionary processes common to many pathogens. Population biological models have been used to study the dynamics of resistance in viruses, bacteria, and eukaryotic microparasites both at the level of the individual treated host and of the treated host population. Despite the existence of generic features that underlie such evolutionary dynamics, different conclusions have been reached about the key factors affecting the rate of resistance evolution and how to best use drugs to minimise the risk of generating high levels of resistance. Improved understanding of generic versus specific population biological aspects will help to translate results between different studies, and allow development of a more rational basis for sustainable drug use than exists at present.