Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York At Buffalo, 455 Pharmacy Building, Buffalo, NY, 14214-8033, USA.
J Pharmacokinet Pharmacodyn. 2020 Dec;47(6):597-612. doi: 10.1007/s10928-020-09713-0. Epub 2020 Sep 2.
Development of protein therapeutics for ocular disorders, particularly age-related macular degeneration (AMD), is a highly competitive and expanding therapeutic area. However, the application of a predictive and translatable ocular PK model to better understand ocular disposition of protein therapeutics, such as a physiologically-based pharmacokinetic (PBPK) model, is missing from the literature. Here, we present an expansion of an antibody platform PBPK model towards rabbit and incorporate a novel anatomical and physiologically relevant ocular component. Parameters describing all tissues, flows, and binding events were obtained from existing literature and fixed a priori. First, translation of the platform PBPK model to rabbit was confirmed by evaluating the model's ability to predict plasma PK of a systemically administered exogenous antibody. Then, the PBPK model with the new ocular component was validated by estimation of serum and ocular (i.e. aqueous humor, retina, and vitreous humor) PK of two intravitreally administered monoclonal antibodies. We show that the proposed PBPK model is capable of accurately (i.e. within twofold) predicting ocular exposure of antibody-based drugs. The proposed PBPK model can be used for preclinical-to-clinical translation of antibodies developed for ocular disorders, and assessment of ocular toxicity for systemically administered antibody-based therapeutics.
用于眼部疾病（特别是年龄相关性黄斑变性（AMD））的蛋白质治疗药物的开发是一个极具竞争力和不断扩展的治疗领域。然而，文献中缺少应用预测性和可转化的眼部 PK 模型（如基于生理学的药代动力学（PBPK）模型）来更好地了解蛋白质治疗药物在眼部的处置情况。在这里，我们提出了一种针对兔的抗体平台 PBPK 模型的扩展，并纳入了一种新的解剖学和生理学相关的眼部成分。描述所有组织、流量和结合事件的参数均从现有文献中获得，并预先固定。首先，通过评估模型预测系统性给予外源性抗体的血浆 PK 的能力来确认平台 PBPK 模型向兔的转化。然后，通过估计两种玻璃体内给予的单克隆抗体在血清和眼部（即房水、视网膜和玻璃体）中的 PK，对具有新眼部成分的 PBPK 模型进行验证。我们表明，所提出的 PBPK 模型能够准确（即，在两倍以内）预测基于抗体的药物在眼部的暴露情况。该 PBPK 模型可用于将开发用于眼部疾病的抗体从临床前转化为临床，并评估系统给予的基于抗体的治疗药物的眼部毒性。
