Burgert, Lydia. Modelling to guide the development of pharmaceutical interventions against malaria. 2022, Doctoral Thesis, University of Basel, Associated Institution, Faculty of Science.
![]()
|
PDF
19Mb |
Official URL: https://edoc.unibas.ch/91671/
Downloads: Statistics Overview
Abstract
The development of new antimalarial compounds and regimens is more urgent than ever as continued burden reduction and ultimately the elimination of malaria are threatened by emerging resistance against current treatments, and sub-optimal adherence to treatment schedules.
Throughout this thesis, I have sought to develop a thorough understanding of parasite-host dynamics along the clinical development pathway of new antimalarials for clinical case management and to evaluate drug efficacy measures, their translation, and their limitations. I analysed parasite growth data from murine and human experiments in the absence of treatment and captured parasite growth in an ensemble of mechanistic mathematical models. Subsequently, I investigated the sensitivity of the experimental efficacy endpoint of parasite clearance after treatment to host-, parasite-, and drug-dynamics throughout the clinical development pathway. Our findings show that the experimental background and/or host dynamics strongly influence parasite clearance with differential impact between the experimental systems. The work culminates in a discussion of the multitude of different host-parasite dynamics in the development stages that compromise the translatability of drug efficacy estimates between the infection experiments.
I then shift the focus to the development of new anti-infective interventions in form of long acting injectables. These are envisioned to protect children living in highly seasonal transmission settings against malaria. I employ a simulation-based approach using an individual-based stochastic model of malaria that allows the efficient investigation of a large range of plausible product properties and deployment modalities and their potential to reach predefined health and impact targets. A non-inferiority analysis to currently implemented drug-based chemoprevention measures reveals the trade-offs between tool and coverage optimisation for the development of new tools. The results assist the specification of use cases and definition of efficacy targets in target product profiles to guide the future development of long-acting injectables.
Through the use of mechanistic parasite growth and individual-based models, the work reported here creates a sound foundation for a comprehensive assessment of experimental and clinical testing results through exploring, understanding and quantifying host-, parasite-, and experimental-factors that influence intervention efficacy and impact.
Throughout this thesis, I have sought to develop a thorough understanding of parasite-host dynamics along the clinical development pathway of new antimalarials for clinical case management and to evaluate drug efficacy measures, their translation, and their limitations. I analysed parasite growth data from murine and human experiments in the absence of treatment and captured parasite growth in an ensemble of mechanistic mathematical models. Subsequently, I investigated the sensitivity of the experimental efficacy endpoint of parasite clearance after treatment to host-, parasite-, and drug-dynamics throughout the clinical development pathway. Our findings show that the experimental background and/or host dynamics strongly influence parasite clearance with differential impact between the experimental systems. The work culminates in a discussion of the multitude of different host-parasite dynamics in the development stages that compromise the translatability of drug efficacy estimates between the infection experiments.
I then shift the focus to the development of new anti-infective interventions in form of long acting injectables. These are envisioned to protect children living in highly seasonal transmission settings against malaria. I employ a simulation-based approach using an individual-based stochastic model of malaria that allows the efficient investigation of a large range of plausible product properties and deployment modalities and their potential to reach predefined health and impact targets. A non-inferiority analysis to currently implemented drug-based chemoprevention measures reveals the trade-offs between tool and coverage optimisation for the development of new tools. The results assist the specification of use cases and definition of efficacy targets in target product profiles to guide the future development of long-acting injectables.
Through the use of mechanistic parasite growth and individual-based models, the work reported here creates a sound foundation for a comprehensive assessment of experimental and clinical testing results through exploring, understanding and quantifying host-, parasite-, and experimental-factors that influence intervention efficacy and impact.
Advisors: | Penny, Melissa and Möhrle, Jörg and Okell, Lucy |
---|---|
Faculties and Departments: | 09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Disease Modelling > Disease Modelling and Intervention Dynamics (Penny) |
UniBasel Contributors: | Penny, Melissa |
Item Type: | Thesis |
Thesis Subtype: | Doctoral Thesis |
Thesis no: | 14910 |
Thesis status: | Complete |
Number of Pages: | xvi, 229 |
Language: | English |
Identification Number: |
|
edoc DOI: | |
Last Modified: | 18 Jul 2024 09:50 |
Deposited On: | 04 Jan 2023 10:26 |
Repository Staff Only: item control page