ArticleCPT: pharmacometrics & systems pharmacology2025
Model-Informed Drug Development of a Sustained Release Formulation of Flucytosine in the Treatment of Cryptococcal Meningitis: A Case Study Using Physiologically Based Pharmacokinetic Modeling.
Article in CPT: pharmacometrics & systems pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This paper presents a case study demonstrating the application of model-informed drug development (MIDD) and early modeling integration in the development of a sustained release (SR) formulation of flucytosine for cryptococcal meningoencephalitis (CM) in HIV-infected patients. The study aimed to showcase the value of physiologically based pharmacokinetic (PBPK) modeling and physiologically based biopharmaceutics modeling (PBBM) in guiding decisions and optimizing therapeutic strategies throughout drug development. The MIDD strategy started with a PBPK model based on limited literature data, iteratively refined informed by data from two Phase 1 clinical studies with various flucytosine formulations under different prandial conditions in healthy participants, enhancing model reliability. The PBPK/PBBM model played a substantial role in guiding SR prototype formulation design, dose selection for studies in healthy participants, and dosage determination for an upcoming Phase 2 clinical study in patients, with a focus on low-weight patients. The flexibility of MIDD allowed quick assessments of ancillary questions during the program. Ad hoc simulations evaluated strategies such as adding a loading dose for SR treatment and assessing drug exposure in unconscious patients, contributing to optimized therapeutic approaches. In conclusion, this case study emphasizes the benefits of MIDD and early model integration in drug development. PBPK/PBBM modeling facilitated informed decisions, leading to successful design and dosing of an SR flucytosine formulation for CM treatment. Continuous knowledge integration within MIDD ensured model adaptability and reliability, demonstrating its value in addressing evolving challenges and optimizing therapeutic outcomes.
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