Quantitative pharmacological modelling for optimizing treatment of sepsis

Liu, F.

Sepsis is a life-threatening condition caused by a dysregulated host response to infection, it is associated with significant morbidity, mortality, and with a high financial burden on global healthcare systems. Bacterial infections are the primary cause of sepsis, but the growing prevalence of antimicrobial resistance complicates the effectiveness of antimicrobial treatments. Moreover, limited understanding of the host immune response during sepsis hinders the discovery of valuable biomarkers and drug targets. As such, there is an urgent need to improve the treatment of sepsis. To tackle this challenge, we have concentrated our efforts on optimizing current treatment strategies and on facilitating the discovery of novel host inflammatory response directed therapeutics. In this thesis, we have utilized quantitative pharmacological modeling approaches to assess the adequacy of current dose regimens and to evaluate antibiotic pharmacokinetic variability, thereby optimizing...Show moreSepsis is a life-threatening condition caused by a dysregulated host response to infection, it is associated with significant morbidity, mortality, and with a high financial burden on global healthcare systems. Bacterial infections are the primary cause of sepsis, but the growing prevalence of antimicrobial resistance complicates the effectiveness of antimicrobial treatments. Moreover, limited understanding of the host immune response during sepsis hinders the discovery of valuable biomarkers and drug targets. As such, there is an urgent need to improve the treatment of sepsis. To tackle this challenge, we have concentrated our efforts on optimizing current treatment strategies and on facilitating the discovery of novel host inflammatory response directed therapeutics. In this thesis, we have utilized quantitative pharmacological modeling approaches to assess the adequacy of current dose regimens and to evaluate antibiotic pharmacokinetic variability, thereby optimizing antimicrobial therapies for sepsis. Additionally, our researches had aimed to deepen our understanding of the underlying dynamics of sepsis pathology, enabling the identification of promising biomarkers and therapeutic targets for sepsis. Our work demonstrated how quantitative modeling strategies can support the design of optimized treatment strategies, and how systematic model-based integration of disease mechanisms can help to overcome the translational challenges in sepsis drug development.
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Quantitative pharmacological modelling for optimizing treatment of sepsis