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Predicting Clinical Pharmacokinetics/Pharmacodynamics and Impact of Organ Impairment on siRNA-Based Therapeutics Using a Mechanistic Physiologically-Based Pharmacokinetic-Pharmacodynamic Model.

Annie LumenXinwen ZhangSandeep DuttaVijay V Upreti
Published in: Clinical pharmacology and therapeutics (2024)
Approved and emerging siRNA therapeutics are primarily designed for targeted delivery to liver where the therapeutic gene silencing effects occurs. Impairment of hepatic/renal function and its impact on siRNA pharmacokinetics/pharmacodynamics (PKs/PDs) are yet to be mechanistically evaluated to describe the unanticipated clinical observations for this novel modality. We developed pathophysiologically relevant models for organ impairment within a physiologically-based PK-PD (PBPK-PD) modeling framework focusing on modality-specific mechanistic factors to evaluate impact on siRNA PKs and PDs. PBPK-PD models for two US Food and Drug Administration (FDA) approved siRNAs inclisiran and vutrisiran were developed as case studies leveraging available tissue-specific data and translated to humans. Key determinants of the clinical PK and PD of N-acetylgalactosamine conjugated siRNAs (GalNAc-siRNAs) with varying sequences were also identified to inform effective clinical translation strategies for emerging GalNAc-siRNA candidates. A 30-70% reduction in hepatic asialoglycoprotein receptors concentrations still allowed for sufficient amount of free cytoplasmic siRNA for RISC-loading to produce PD effects comparable in extent and duration to normal liver function. This included severe hepatic impairment for which no clinical data are available. Inclusion of other modality agnostic physiological changes relevant to organ impairment did not alter the findings. Changes in renal physiologies, including changes in GFR across various degrees of impairment, well predicted minimal changes in PD for inclisiran and vutrisiran. This work provides a quantitative mechanistic framework and insights on modality-specific factors that drive clinical translation and patient/disease-related factors that impact specific dosing considerations and clinical outcomes to help accelerate the optimal development of siRNA therapeutics.
Keyphrases
  • cancer therapy
  • drug administration
  • small molecule
  • risk assessment
  • high resolution
  • early onset
  • machine learning
  • deep learning
  • drug delivery
  • case report
  • human health
  • genetic diversity