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

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, 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, optimizing 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.

Target Product Profiles for Mosquito Gene Drives: Incorporating Insights From Mathematical Models

“…Key decisions also need to be made regarding the modeled transmission settings, as these will have a significant influence on TPP specification. The LAI analysis presents an interesting case study by selecting two locations where comparable interventions and field studies have been conducted (14). For gene drive mosquito projects, similar reasoning would support modeling population suppression products in Mali, Burkina Faso, Kenya or Uganda (field sites of the Target Malaria project), and population modification products in São Toméand Prıńcipe or the Union of the Comoros (field sites of the UC Irvine Malaria Initiative).…”

“…As the goals of TPPs are product-focused, much of the modeling work in this area does not feature in academic journals. We therefore focus on a handful of published modeling analyses, each conducted by a different research group, that have supported TPP specification for ATSBs (12), odor-baited traps (13), and long-acting injectable drugs (LAIs) for seasonal malaria prevention (14). We summarize these analyses, and additional TPP modeling analyses for malaria vaccines (15) and vector control pesticides (16,17), in Table 1.…”

“…LAIs have been proposed as an alternative to monthly seasonal malaria chemoprevention (SMC) with oral anti-malarials in the hope that longer-lasting injectable drugs can remedy the spread of drug-resistance and the low adherence rates and high deployment costs of SMC (27). In order for LAIs to be implemented, they must be shown to be non-inferior to existing interventions, and in lieu of clinical studies, a preliminary modeling analysis was conducted (14). In this study, the OpenMalaria model (6, 7) was used to predict clinical malaria cases averted by LAIs compared to SMC in the intervention age group (children 0-5 years of age).…”

“…In this study, the OpenMalaria model (6, 7) was used to predict clinical malaria cases averted by LAIs compared to SMC in the intervention age group (children 0-5 years of age). Simulations were conducted for settings that resemble Mali and Senegal in terms of seasonality, mosquito species and interventions, with these two countries being chosen because they are locations where SMC is implemented and clinical trials are frequently conducted (14). The OpenMalaria model is an individual-based simulation of malaria in humans, including heterogeneity in mosquito biting, human immunity and disease susceptibility, and is linked to a deterministic model of mosquito life history (6,7).…”

“…The required half-life of protective efficacy mirrored the duration of seasonal transmission in each setting, and a trade-off was observed between protective efficacy and coverage. Given the importance of decay in LAI protective efficacy, it was recommended that studying this phenomenon be prioritized in potential clinical studies (14). Another interesting aspect of this analysis was the use of machine learning to infer non-inferior tool profiles and parameter sensitivities based on a database of TPP malaria model simulations (28).…”