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Federico Reali

Publications and source records attributed to Federico Reali.

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Best Practices on QSP Model Reporting for Regulatory Use: perspectives from ISoP QSP SIG Working Group

Quantitative systems pharmacology (QSP) models are increasingly applied to inform decision making across drug development and to support regulatory interactions within model informed drug development (MIDD). QSP supports a broad range of applications across drug development and can be tailored to specific therapeutic areas, mechanisms of action, and contexts of use (CoU). While this diversity is a core strength of QSP, it also presents challenges for reporting for regulatory use. Despite the growing impact of QSP models, there is currently no established guidance on how QSP analyses should be documented and reported for regulatory purposes. This white paper, developed by the International Society of Pharmacometrics (ISoP) QSP Special Interest Group Working Group on Credibility Assessment of QSP for Regulatory Use, seeks to address this gap by proposing best practices for QSP model reporting in regulatory settings. The recommendations are grounded in collective real world experience from regulatory interactions and are aligned with reporting guidance established for physiologically based pharmacokinetic (PBPK) modeling and reporting principles outlined in ICH M15. Rather than prescribing a rigid, one size fits all template, this work proposes a flexible, tiered reporting framework that accounts for development phase and model impact. The proposed framework is intended to facilitate regulatory review and enhance transparency while accommodating the inherent diversity of QSP modeling.

math.DS

Mechanistic models of $\alpha$-synuclein homeostasis for Parkinson's disease: A blueprint for therapeutic intervention

Parkinson's disease (PD) is the second most common neurodegenerative disorder worldwide, yet there is no disease-modifying therapy up to this date. The biological complexity underlying PD hampers the investigation of the principal contributors to its pathogenesis. In this context, mechanistic models grounded in molecular-level knowledge provide virtual labs to uncover the primary events triggering PD onset and progression and suggest promising therapeutic targets. Multiple modeling efforts in PD research have focused on the pathological role of $\alpha$-synuclein ($\alpha$syn), a presynaptic protein that emerges from the intricate molecular network as a crucial driver of neurodegeneration. Here, we collect the advances in mathematical modeling of $\alpha$syn homeostasis, focusing on aggregation and degradation pathways, and discussing potential modeling improvements and possible implications in PD therapeutic strategy design.

math.DS