Crawshaw Jessica R, Gaffney Eamonn A, Gertz Michael, Maini Philip K, Caruso Antonello
Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.
Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Switzerland.
Invest Ophthalmol Vis Sci. 2025 Jun 2;66(6):20. doi: 10.1167/iovs.66.6.20.
Improving our understanding of the ocular pharmacokinetics and pharmacodynamics of anti-vascular endothelial growth factor (VEGF) therapies, such as ranibizumab, is essential to enhance treatment strategies for a range of retinal diseases, and will help inform the development of novel anti-VEGF drug candidates.
In this study, we examine a two-compartment pharmacokinetic/pharmacodynamic model of an intravitreal ranibizumab injection to understand its impact on ocular VEGF suppression. We use Bayesian inference to infer the model parameters from aqueous humor data extracted from healthy cynomolgus macaques. We leverage this approach to explore various sources of uncertainty in the data, offering practical recommendations for minimizing avoidable uncertainty.
The model provides a robust description of ranibizumab pharmacokinetics and pharmacodynamics, identifying the recovery region of the aqueous humor VEGF concentration-time profile as critical for the precise estimation of parameters. Our results advocate focusing on this region in future studies for optimal data collection. We consider standard data correction techniques to reduce the data uncertainty introduced by the lower limit of quantification, identifying the most preferable technique for this model and data. Using a Bayesian approach we obtain an inferred mean posterior distribution of 1459 ± 98 pM for the ranibizumab dissociation constant, a pharmacodynamic parameter with notable variability across the literature.
This study extends our understanding of the ocular pharmacokinetics and pharmacodynamics of ranibizumab and provides theoretical insights for enhanced data collection schemes to be considered for clinical trials and in the development of novel anti-VEGF therapies.
提高我们对抗血管内皮生长因子（VEGF）疗法（如雷珠单抗）的眼内药代动力学和药效学的理解，对于加强一系列视网膜疾病的治疗策略至关重要，并且将有助于为新型抗VEGF候选药物的研发提供信息。
在本研究中，我们研究了玻璃体内注射雷珠单抗的双室药代动力学/药效学模型，以了解其对眼内VEGF抑制的影响。我们使用贝叶斯推断从健康食蟹猴提取的房水数据中推断模型参数。我们利用这种方法探索数据中各种不确定性的来源，为最小化可避免的不确定性提供实用建议。
该模型对雷珠单抗的药代动力学和药效学提供了有力的描述，确定房水VEGF浓度-时间曲线的恢复区域对于参数的精确估计至关重要。我们的结果主张在未来的研究中关注该区域以进行最佳数据收集。我们考虑采用标准数据校正技术来减少由定量下限引入的数据不确定性，确定该模型和数据最适用的技术。使用贝叶斯方法，我们获得了雷珠单抗解离常数的推断平均后验分布为1459±98 pM，该药效学参数在文献中具有显著的变异性。
本研究扩展了我们对雷珠单抗眼内药代动力学和药效学的理解，并为临床试验和新型抗VEGF疗法研发中应考虑的增强数据收集方案提供了理论见解。
