Rami Ayoun Alsoud: Pharmacometric tools to support translational drug development

Abstract

The use of model-informed drug development has been shown to save significant costs and improve decision making early in the drug development process. The work in this PhD thesis aimed to employ pharmacometric tools to support translational drug development from the preclinical to the late clinical stages.

Pharmacometric modeling was used to characterize the treatment-shortening potential of different anti tuberculosis regimens. The results provided additional evidence in favor of the treatment-shortening capacity of the BPaMZ regimen over BPaL and standard of care, HRZE.

Pharmacokinetic-pharmacodynamic (PKPD) modeling was used to enable the evaluation of the exposure-response of a new anti-tubercular drug, MPL-447, in C3HeB/FeJ mice, thought to be of a translational value in tuberculosis drug development. Model-based evaluation revealed a significant impact of necrotic lesion development in mice on both bacterial growth and sensitivity to treatment with MPL-447, highlighting the significance of accounting for the heterogenous lesion profile in the C3HeB/FeJ mouse model when evaluating drug efficacy.

Pharmacokinetic (PK) modeling was employed to perform interspecies PK scaling of the CB 4332 protein using information from three preclinical species. This approach accounted for the impact of immunogenicity and species-related differences in elimination. Simulations predicted the protein plasma concentrations in humans after different dosing regimens and suggested that a 7 mg/kg dose would be required to reach the target at steady-state.

Using combined biomarker data, PKPD modeling was employed to simultaneously analyze two tuberculosis efficacy biomarkers. The final biomarker model facilitated the prediction of the relationship between the two biomarkers over time. With this modeling framework, missing biomarker data can be predicted using information from the other biomarker.

Several model-based approaches were also explored to evaluate pediatric study power in rare diseases. These approaches were performed analyzing pediatric data alone or combined with the adult data. While Bayesian priors performed well when analyzing pediatric data alone, less technical modeling approaches proved sufficient when pediatric and adult data were combined.

In conclusion, the research presented in this thesis has addressed various challenges encountered in translational drug development. The work has contributed to the evaluation of new anti-tubercular drugs and regimens, the assessment of newly proposed animal models, and optimizing the utilization of biomarker information. Furthermore, this thesis has provided insights into the selection of First-in-Human dose for a protein, showcasing the applicability of model-based approaches in this critical decision-making process. The research has contributed to improving analysis approaches for pediatrics in rare diseases.