CPT: Pharmacometrics & Systems Pharmacology (Jan 2023)

A pharmacokinetic–pharmacodynamic model for chemoprotective agents against malaria

  • Mohammed H. Cherkaoui‐Rbati,
  • Nicole Andenmatten,
  • Lydia Burgert,
  • Oluwaseun F. Egbelowo,
  • Rolf Fendel,
  • Chiara Fornari,
  • Michael Gabel,
  • John Ward,
  • Jörg J. Möhrle,
  • Nathalie Gobeau

DOI
https://doi.org/10.1002/psp4.12875
Journal volume & issue
Vol. 12, no. 1
pp. 50 – 61

Abstract

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Abstract Chemoprophylactics are a vital tool in the fight against malaria. They can be used to protect populations at risk, such as children younger than the age of 5 in areas of seasonal malaria transmission or pregnant women. Currently approved chemoprophylactics all present challenges. There are either concerns about unacceptable adverse effects such as neuropsychiatric sequalae (mefloquine), risks of hemolysis in patients with G6PD deficiency (8‐aminoquinolines such as tafenoquine), or cost and daily dosing (atovaquone–proguanil). Therefore, there is a need to develop new chemoprophylactic agents to provide more affordable therapies with better compliance through improving properties such as pharmacokinetics to allow weekly, preferably monthly, dosing. Here we present a pharmacokinetic–pharmacodynamic (PKPD) model constructed using DSM265 (a dihydroorotate dehydrogenase inhibitor with activity against the liver schizonts of malaria, therefore, a prophylaxis candidate). The PKPD model mimics the parasite lifecycle by describing parasite dynamics and drug activity during the liver and blood stages. A major challenge is the estimation of model parameters, as only blood‐stage parasites can be observed once they have reached a threshold. By combining qualitative and quantitative knowledge about the parasite from various sources, it has been shown that it is possible to infer information about liver‐stage growth and its initial infection level. Furthermore, by integrating clinical data, the killing effect of the drug on liver‐ and blood‐stage parasites can be included in the PKPD model, and a clinical outcome can be predicted. Despite multiple challenges, the presented model has the potential to help translation from preclinical to late development for new chemoprophylactic candidates.