Retrospective Analysis Using Pharmacokinetic/Pharmacodynamic Modeling and Simulation Offers Improvements in Efficiency of the Design of Volunteer Infection Studies for Antimalarial Drug Development

Abstract

Volunteer infection studies using the induced blood stage malaria (IBSM) model have been shown to facilitate antimalarial drug development. Such studies have traditionally been undertaken in single-dose cohorts, as many as necessary to obtain the dose-response relationship. To enhance ethical and logistic aspects of such studies, and to reduce the number of cohorts needed to establish the dose-response relationship, we undertook a retrospective in silico analysis of previously accrued data to improve study design. A pharmacokinetic (PK)/pharmacodynamic (PD) model was developed from initial fictive-cohort data for OZ439 (mixing the data of the three single-dose cohorts as: n = 2 on 100 mg, 2 on 200 mg, and 4 on 500 mg). A three-compartment model described OZ439 PKs. Net growth of parasites was modeled using a Gompertz function and drug-induced parasite death using a Hill function. Parameter estimates for the PK and PD models were comparable for the multidose single-cohort vs. the pooled analysis of all cohorts. Simulations based on the multidose single-cohort design described the complete data from the original IBSM study. The novel design allows for the ascertainment of the PK/PD relationship early in the study, providing a basis for rational dose selection for subsequent cohorts and studies. Volunteer infection studies using the induced blood stage malaria (IBSM) model have been recognized as a valuable system for defining the key pharmacokinetic (PK) and pharmacodynamic (PD) relationships for dose selection in antimalarial drug development. 1-7 In such studies, healthy volunteers are inoculated intravenously with a given quantity (with small variability) of Plasmodium-infected red cells. Parasitemia is then followed by quantitative polymerase chain reaction until a prespecified treatment threshold is reached when the test drug is administered. Parasite and drug concentrations are then measured. These studies are www.cts-journal.com M&S to Improve Efficiency of VIS Studies Andrews et al.

Keystone Malaria Symposium 2022: a vibrant discussion of progress made and challenges ahead from drug discovery to treatment

“…Dr Catteruccia also presented antimalarial screening results that identified P. falciparum cytochrome B, PfATP4, dihydrofolate reductase, and elongation factor 2 as promising targets for killing P. falciparum parasites in the mosquito. Dr James McCarthy (Peter Doherty Institute for Infection and Immunity) highlighted promising clinical trial data for an ACT partner drug candidate ZY-19489 [14], as well as retrospective in silico pharmacokinetic/pharmacodynamic modeling on an earlier OZ439-PPQ study [15]. Dr McCarthy also showed clinical data supporting 50 mg tafenoquine as the smallest dose that can kill gametocytes [16].…”

Model‐Informed Drug Development for Anti‐Infectives: State of the Art and Future

“…Real-time population PK/PD modeling on a cohort-by-cohort basis can inform dose selection of subsequent cohorts to investigate doses that will be most informative of the exposure response. 190 The strain of parasite administered in malaria CHIM studies is most often 3D7 or NF54, both P. falciparum strains that are well-characterized and drug sensitive. More recently, researchers have developed CHIM studies using an artemisinin-resistant strain of malaria to evaluate the efficacy of therapeutics against drug-resistant malaria.…”

“…Innovative alternative phase II designs, specific to malaria, can leverage data from malaria CHIM studies with modeling and simulation techniques to better understand dose/exposure response and enable efficient and optimal dose or doses of the combination for phase II doseresponse and phase III confirmatory clinical trials. 190 Adaptive and variable sample sizes could potentially provide opportunity for subsets of populations to be studied on an as-needed basis without the confounding factors present in a field study, thereby increasing safety for patients and de-risking antimalarial clinical trial design. Although field studies will always be necessary to demonstrate that the dose-response relationship is similar between naturally infected patients living in endemic areas and subjects in a malaria CHIM study with no prior exposure, the use of modeling and simulation could potentially decrease the number and size of these confirmatory studies.…”