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. 2022 Mar 14;2(3):e0000211.
doi: 10.1371/journal.pgph.0000211. eCollection 2022.

Model-informed target product profiles of long-acting-injectables for use as seasonal malaria prevention

Affiliations

Model-informed target product profiles of long-acting-injectables for use as seasonal malaria prevention

Lydia Burgert et al. PLOS Glob Public Health. .

Abstract

Seasonal malaria chemoprevention (SMC) has proven highly efficacious in reducing malaria incidence. However, the continued success of SMC is threatened by the spread of resistance against one of its main preventive ingredients, Sulfadoxine-Pyrimethamine (SP), operational challenges in delivery, and incomplete adherence to the regimens. Via a simulation study with an individual-based model of malaria dynamics, we provide quantitative evidence to assess long-acting injectables (LAIs) as potential alternatives to SMC. We explored the predicted impact of a range of novel preventive LAIs as a seasonal prevention tool in children aged three months to five years old during late-stage clinical trials and at implementation. LAIs were co-administered with a blood-stage clearing drug once at the beginning of the transmission season. We found the establishment of non-inferiority of LAIs to standard 3 or 4 rounds of SMC with SP-amodiaquine was challenging in clinical trial stages due to high intervention deployment coverage. However, our analysis of implementation settings where the achievable SMC coverage was much lower, show LAIs with fewer visits per season are potential suitable replacements to SMC. Suitability as a replacement with higher impact is possible if the duration of protection of LAIs covered the duration of the transmission season. Furthermore, optimising LAIs coverage and protective efficacy half-life via simulation analysis in settings with an SMC coverage of 60% revealed important trade-offs between protective efficacy decay and deployment coverage. Our analysis additionally highlights that for seasonal deployment for LAIs, it will be necessary to investigate the protective efficacy decay as early as possible during clinical development to ensure a well-informed candidate selection process.

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Conflict of interest statement

The authors have read the journal’s policy and the authors of this manuscript have the following competing interests: J.J.M. is employed by the Medicines for Malaria Venture. All other authors have declared that no other competing interests exist.

Figures

Fig 1
Fig 1. Workflow to assess the target product profile of LAIs.
(a) In an iterative exchange between various stakeholders, definition of TPPs is informed by results from modelling approaches. Simulation of predefined scenarios with OpenMalaria, an individual-based model of malaria dynamics, allows to predict the likely intervention impact (incidence reduction, indicated by the model symbol) of LAIs in the context of deployment setting details (access to healthcare (indicated by the hospital symbol) and seasonality (indicated by the mosquito icon), deployment coverage of the target population and the tool properties (initial protective efficacy against infection, protective efficacy half-life and decay of protective efficacy). The resulting evaluation of LAI impact is communicated and discussed with stakeholders to refine the analysis as LAIs are developed. (b) The analysis in the clinical trial and implementation stage are illustrated on the example of two hypothetical LAIs with different efficacy profiles (denoted LAI 1 and 2). (1) In clinical trial stages, the minimum essential properties to reach a certain health goal are evaluated in a two-arm clinical trial. SMC with SP+AQ is administered (green arrows) three time during the months of September (S), October (O), and November (N) (as in Senegal, filled green arrows) or four times as well as in August (A) (as in Mali, filled and unfilled green arrows) times over the transmission season. LAIs are administered once at the beginning of the transmission season (blue filled arrow for Senegal or blue empty arrow for Mali). The cumulative cases per person over the trial period are tracked. (2) In implementation stages, SMC-SP+AQ is replaced with LAIs after five years of implementation. Impact is assessed in the last implementation year (grey bar) and compared to the baseline of SMC-SP+AQ implementation. Coverages of SMC-SP+AQ and LAIs are independent from each other. (3) Upper panel: The tool properties influencing the establishment of non-inferiority of LAIs to SMC are investigated in the clinical trial stage. Lower panel: At a fixed SMC deployment coverage, the minimum coverage of LAI deployment required to establish non-inferiority is identified.
Fig 2
Fig 2. Parameter space under which sigmoidal LAIs achieve non-inferiority compared with SMC-SP+AQ in the clinical trial stage.
We investigated the ability of sigmoidal LAIs to establish non-inferiority in clinical trials with an optimal deployment coverage (100%) in settings with a short (a, c) and long (b, d) malaria season and over varying initial malaria incidence (initial cases per person per year0.25-5y). The minimum required LAI characteristics are defined as those parameter combinations that achieve non-inferior for different baseline incidence settings. (a, b) SMC–SP+AQ has an initial protective efficacy of 100% and a half-life of 32 days parameterised from previous clinical trial data1. The influence of prevalent SP-resistance (c, d) was analyzed by decreasing the protective efficacy half-life of SP from 32 to 20 days (see S1 Text). The coloured area defines the limits of the parameter space where non-inferiority could be established through comparison of the difference hazard ratio δ between Kaplan-Meier survival estimates (see S1 Text). The white area describes the parameter space where LAIs are inferior. Sigmoidal LAIs can achieve non-inferiority compared with SMC for lower durations of protection in a shorter malaria transmission season. Exponential LAIs and biphasic LAIs could not establish non-inferiority to SMC–SP+AQ.
Fig 3
Fig 3. Achieving targeted malaria incidence reduction depends on the decay shape of the LAIs protective efficacy.
Estimated relationships between initial protective efficacy and efficacy half-life for different incidence reduction criteria (40%, 60% and 80%, line style and color) and clinical incidence settings (increasing color intensity indicates an initial clinical incidence measured in cases per person per year in the target age group of 0.5, 1, 1.5, 2, and 2.8). Each line shows the minimum required LAI characteristics to reach the desired health goal at a 100% LAI deployment coverage at clinical trial stage, with all parameter combinations below a line failing to meet those requirements. The panels show the parameter space of attainable incidence reductions within the specified constrained ranges of initial protective efficacy and half-life for exponential LAIs (a, b), biphasic LAIs (c, d) and sigmoidal LAIs (e, f) in settings with a short (Senegal-like a, c, e) or long (Mali-like b, d, f) malaria season. The incidence reduction was calculated by comparing the incidence over one transmission season after application of the LAI compared with the previous transmission season. The incidence reductions were obtained by predicting the cases per person per year0.25-5y via our emulator approach (See S1 Text) in a fine grid defined over the parameter space (increments of 0.1 h for half-life and 0.01% for initial protective efficacy) and calculating the incidence reduction by comparison to the initial clinical incidence measured in cases per person per year0.25-5y in the respective transmission intensity setting.
Fig 4
Fig 4. Estimated importance of LAI properties and operational factors on the level of clinical incidence reduction.
Results are shown for the implementation stage for sigmoidal LAIs in a setting with low access to care and long malaria transmission season. (a, b) Sobol sensitivity analysis estimates the relative importance of LAI coverage, initial protective efficacy and half-life of protective efficacy to the variance of the emulator through decomposition of variance over the entire evaluated parameter space (coverage 40–100%, initial protective efficacy 70–100% and half-life (a) 30–90 days and (b) 90–150 days). Changes in clinical incidence measured as cases per person per year0.25-5y with increasing tool properties or deployment coverage across the parameter space are shown for (c) half-life (30–150 days), (d) initial protective efficacy (70–100%) and (e) coverage (40–100%). The lines represent the mean and the 95% confidence interval (shaded area) capture the distribution of incidence reduction across all sampled values. The dotted line in panel c indicates the split of half-life range for sensitivity analysis in panels a and b. Increasing color intensity represents increasing initial cases per person per year0.25-5y. Further results for different decay shapes and length of transmission season are shown in the Figs D and E in S1 Text.
Fig 5
Fig 5. Estimated minimal LAI coverage required during implementation stages to achieve non-inferiority in a given setting and predicted gains in cases averted of subsequent sigmoidal LAI coverage increments.
(a) Heatmap of the estimated minimal coverage (colour) of sigmoidal LAIs at which non-inferiority to SMC-SP+AQ (assuming a fixed SMC coverage of 60%) is achieved for different combinations of sigmoidal LAI efficacy and half-life. The results are displayed for intervention scenarios with an underlying disease burden of 1.4 cases per person per year0.25-5y, long malaria transmission season and low access to treatment (E14 = 0.1). In the grey area, non-inferiority of LAIs could not be established for any coverage. The light blue frames capture the tool characteristics where non-inferiority could be reached with a LAI coverage under the reference SMC-SP+AQ coverage of 60%. Further results for additional settings and decay shapes are provided in the S1 Text (Fig H and I in S1 Text). The coloured dots represent four illustrative LAI profiles for which the corresponding predicted relative differences in cases per person per year0.25-5y (Eq 5) are calculated in (b-e) five years after LAI introduction over all LAI coverages as compared with SMC-SP+AQ at 60% coverage (vertical dotted line). The predicted positive increase in relative difference in yearly clinical cases (above the dotted horizontal line) means more clinical cases are averted with LAIs than with SMC-SP+AQ. It thus illustrates the benefit of increasing sigmoidal LAI-coverage above the minimal required coverage to achieve non-inferiority (shown by the grey coloured area). Due to the chosen margin of non-inferiority (here 5%, see Material and Methods), LAIs are non-inferior for a slight negative relative difference in cases per person per year0.25-5y. In the light-blue area in (b), a LAI coverage lower than the SMC-SP+AQ coverage is sufficient to establish non-inferiority. The corresponding analysis for exponential LAIs can be found in Fig J in S1 Text.

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