mathematical modelling; parasite dynamics; drugs; vaccines; neglected tropical diseases; malaria
Camponovo Flavia, Lee Tamsin E., Russell Jonathan R., Burgert Lydia, Gerardin Jaline, Penny Melissa A. (2021), Mechanistic within-host models of the asexual Plasmodium falciparum infection: a review and analytical assessment, in Malaria Journal
, 20(1), 309.
Burgert Lydia, Zaloumis Sophie, Dini Saber, Marquart Louise, Cao Pengxing, Cherkaoui Mohammed, Gobeau Nathalie, McCarthy James, Simpson Julie A., Möhrle Jörg J., Penny Melissa A. (2021), Parasite-host dynamics throughout antimalarial drug development stages complicate the translation of parasite clearance, in Antimicrobial Agents and Chemotherapy
, 65(4), e01539.
Camponovo Flavia, Campo Joseph J, Le Timothy Q, Oberai Amit, Hung Christopher, Pablo Jozelyn V, Teng Andy A, Liang Xiaowu, Sim B Kim Lee, Jongo Said, Abdulla Salim, Tanner Marcel, Hoffman Stephen L, Daubenberger Claudia, Penny Melissa A (2020), Proteome-wide analysis of a malaria vaccine study reveals personalized humoral immune profiles in Tanzanian adults., in eLife
, 9, e53080.
Penny Melissa A., Camponovo Flavia, Chitnis Nakul, Smith Thomas A., Tanner Marcel (2020), Future use-cases of vaccines in malaria control and elimination, in Parasite Epidemiology and Control
, 10, e00145.
Burgert Lydia, Rottmann Matthias, Wittlin Sergio, Gobeau Nathalie, Krause Andreas, Dingemanse Jasper, Möhrle Jörg J, Penny Melissa A (2020), Ensemble modeling highlights importance of understanding parasite-host behavior in preclinical antimalarial drug development., in Scientific reports
, 10(1), 4410.
Camponovo Flavia, Ockenhouse Chris F, Lee Cynthia, Penny Melissa A (2019), Mass campaigns combining antimalarial drugs and anti-infective vaccines as seasonal interventions for malaria control, elimination and prevention of resurgence: a modelling study., in BMC infectious diseases
, 19(1), 920-920.
Lee Tamsin E., Penny Melissa A. (2019), Identifying key factors of the transmission dynamics of drug-resistant malaria, in Journal of Theoretical Biology
, 462, 210-220.
Reiker Theresa, Golumbeanu Monica, Shattock Andrew, Burgert Lydia, Smith Thomas, Filippi Sarah, Cameron Ewan, Penny Melissa, Emulator-based Bayesian optimization for efficient multi-objective calibration of an individual-based model of malaria, in Nature Communications
Following years of investment in strategies to control malaria, elimination is becoming tangible. But optimal delivery strategies and profiles for drug and vaccines for elimination differ from those of disease control. This is because disease and immunity dynamics change as elimination approaches. Individual-level variations in immune responses and pharmacokinetics-dynamics, variations between parasites in ability to evade interventions, and the alignment of the profiles of new drugs and vaccines with the delivery capacity of health systems, all become more important. Ignoring these factors and their influence on the drop off from efficacy in trials to the effectiveness of interventions in real life will result in, at best, the roll out of inefficient tools, and, at worst, wasted investment and failure to achieve elimination.Mathematical modelling has been essential to understand complex interactions in malaria transmission between mosquito and human hosts and is gaining a greater role in clinical development of drugs and vaccines. But models to date have generally been used at very specific stages (e.g. pharmacometric modelling of drugs in human clinical trials; assessing public health impact of vaccines in Phase 3), rather than in generating evidence for decision-making along the whole pathway from pre-clinical to clinical, through to population, health systems and environmental contexts. Strategic use of novel mathematical models that identify key determinants of intervention impact, could make resource allocation much more efficient. The comprehensive model framework developed in this project will identify these key determinants and integrate them with data on variation in vaccine response and drug dynamics to predict intervention effectiveness, and optimise strategies for elimination and avoidance of drug resistance and vaccine insensitivity. Building on the applicant’s experience in malaria modelling and public health, we specifically aim to:(1)Elucidate the link between preclinical malaria parasite-drug dynamics and host-parasite-drug dynamics in early human clinical testing. Through model development and use of extensive preclinical and clinical data we will explore predictability of pharmaco-kinetic and -dynamic determinants in preclinical models for optimal human dosing. (2)Understand and optimise malaria vaccine immunogenicity and protection combining early clinical data and newly developed mathematical models. Through simulation of parasite and immune kinetic models, fitted to individual level data, we will evaluate kinetics resulting in longer protection;(3)Determine key vaccine, operational, population, and epidemiological determinants of public health impact when targeting malaria control and elimination, by linking models of individual immunity with population-scale models;(4)Optimise the role of new drugs and intervention strategies for malaria elimination and mitigation of drug resistance. Through development of new models of evolution of malaria drug resistance, we will elucidate drug properties, operational and health system factors that limit drug resistance and assist in malaria elimination.As an overarching aim we will bring these building blocks together by:(5) Synthesising evidence from the global community and from aims 1-4 to influence the models and to guide profiles of drugs and vaccines for malaria control and elimination Thus ensuring integration of the findings of the model-based research into a systematic framework for the innovation of new tools from preclinical stages to delivery.The research benefits from access to unique resources, with models developed and validated with data from historical, and on-going laboratory and clinical studies with Swiss TPH participation. The research builds on the applicant’s previous research and proven networks of partners within or affiliated with Swiss TPH and ETHZ, with expertise ranging from statistics, mathematical modelling, immunology, vaccine and drug development, epidemiology to health systems. The comprehensive model framework and evidence compiled in this proposal, will improve malaria drug and vaccine development and public health policy by linking basic science innovations through to application, via a novel holistic approach distinct from existing mathematical-epidemiological models or industry efforts. The multi-dimensional approach and the new mathematical models will be significant advances for epidemiological modelling and understanding of parasite, host and population interactions. Of most immediate relevance for malaria eradication, the project will also inform efforts to eliminate other neglected tropical diseases, while sustaining the positions of the applicant, Swiss TPH, ETHZ and Switzerland as global leaders in malaria and neglected disease research and control.