Our next MILA-Seminar will take place on June 13th, 2023, from 2-3 p.m.
Speaker: Prof. Jacky Snoep (Stellenbosch University)
Title:Quantitative analysis of drug effects at the whole-body level: a case study for glucose metabolism in malaria patients
Malaria affected an estimated 241 million people in 2020, up from 227 million in 2019 with the highest impact in the WHO African Region which accounts for 95% of cases. In 2020 malaria deaths were estimated at 627 000. Of the four Plasmodium species that cause malaria, Plasmodium falciparum is still the most frequently occurring and the most lethal (2). An additional issue of concern is that malaria is gaining resistance to the current artemisinin combination therapies, especially evident in the African region (1), and new drugs, and methods to measure efficacy are important.
Analysis of whole-body responses to partial inhibition with a drug of one or more reaction steps is challenging; typically, mathematical models at the whole-body level are not fine-grained and do not include individual chemical reaction steps. We propose a hierarchical modelling approach to construct models for disease states at the whole-body level. Such models can simulate effects of drug-induced inhibition of reaction steps on the whole-body physiology. We illustrate the approach for glucose metabolism in malaria patients, by merging two detailed kinetic models for glucose metabolism in the parasite Plasmodium falciparum and the human red blood cell with a coarse-grained model for whole-body glucose metabolism. Particular attention will be paid to model construction, validation, reproducible simulation and data management for the detailed models.
The Snoep Lab’s core research efforts are in Computational Systems Biology; a combined experimental, modeling and theoretical approach to quantitatively understand the functional behavior of Biological Systems resulting from the characteristics of their components. Our main focus is on metabolism of human pathogens, such as Plasmodium falciparum, Mycobacterium tuberculosis, and on modelling disease states such as type 2 diabetes and HIV pathogenesis at a whole body level.