Minimal Physiologically-Based Pharmacokinetic (mPBPK) Metamodeling of Target Engagement in Skin Informs Anti-IL17A Drug Development in Psoriasis

基于生理的最小药代动力学(mPBPK)元模型分析皮肤靶点结合情况,为银屑病抗IL-17A药物研发提供信息

阅读:2

Abstract

The pharmacologic effect(s) of biotherapeutics directed against soluble targets are driven by the magnitude and duration of free target suppression at the tissue site(s) of action. Interleukin (IL)-17A is an inflammatory cytokine that plays a key role in the pathogenesis of psoriasis. In this work, clinical trial data from two monoclonal antibodies (mAbs) targeting IL-17A for treatment of psoriasis (secukinumab and ixekizumab) were analyzed simultaneously to quantitatively predict their target engagement (TE) profiles in psoriatic skin. First, a model-based meta-analysis (MBMA) for clinical responses was conducted separately for each drug based on dose. Next, a minimal physiologically-based pharmacokinetic (mPBPK) model was built to assess skin site IL-17A target engagement for ixekizumab and secukinumab simultaneously. The mPBPK model captured the observed drug PK, serum total IL-17A, and skin drug concentration-time profiles reasonably well across the different dosage regimens investigated. The developed mPBPK model was then used to predict the average TE (i.e., free IL-17A suppression) in skin achieved over a 12-weeks treatment period for each drug following their respective regimens and subsequently assess the TE-efficacy response relationship. It was predicted that secukinumab achieved 98.6% average TE in the skin at 300 mg q4w SC while ixekizumab achieved 99.9% average TE under 160 mg (loading) followed by 80 mg q2w SC. While direct quantification of free IL-17A levels at the site of action is technically challenging, integrated mPBPK-MBMA approaches offer quantitative predictions of free IL-17A levels at the site of action to facilitate future drug development via IL-17A suppression in psoriasis.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。