Pharmacokinetic‐pharmacodynamic (PK/PD) modelling of cotadutide effect in patients with chronic kidney disease and type 2 diabetes mellitus

医学 内科学 内分泌学 肾脏疾病 药效学 糖尿病 肌酐 泌尿科 安慰剂 2型糖尿病 药代动力学 病理 替代医学
作者
Hongtao Yu,Victoria Parker,Viknesh Selvarajah,Lars Hansen,Darren Robertson,Bengt Hamrén,Anis A. Khan,Joanna Parkinson
出处
期刊:British Journal of Clinical Pharmacology [Wiley]
标识
DOI:10.1002/bcp.70093
摘要

Aims Cotadutide is a dual glucagon‐like peptide‐1/glucagon receptor agonist. The objective of the analysis was to develop a pharmacokinetic‐pharmacodynamic (PK/PD) model to describe the relationship between cotadutide exposure and response on urine albumin‐to‐creatinine ratio (UACR), urinary albumin (UALB), and body weight in participants with chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM) using data from a Phase2b study (NCT04515849). Methods A total of 247 participants with CKD and T2DM were randomized and titrated to either 100, 300 or 600 μg cotadutide, 1 mg semaglutide or placebo. UACR was measured biweekly from either morning void (Weeks 14 and 26) or spot urine (other visits). The analysis was implemented using a longitudinal non‐linear mixed‐effect model. The potential impact of covariates on efficacy in participants was quantified. Results PK/PD models were developed, and a significant relationship was identified between cotadutide exposure and PD biomarkers of UACR, UALB and body weight. The models described the data adequately; greater changes in PD responses were observed with higher cotadutide doses. Baseline mean blood pressure and baseline UALB were found to affect the reductions in UACR and UALB, respectively. Model‐predicted relative change from placebo in UACR, UALB and body weight after 26 weeks of 600 μg cotadutide treatment were −45.6% (−52.4%, −38.7%), −47.2% (−56.0%, −39.9%) and −5.3% (−7.6%, −4.1%), respectively. Conclusions This modelling assessment was successfully applied for cotadutide to understand the relationship between cotadutide dosing regimen and the response in UACR, UALB and body weight. These models have general application in analysing and interpreting data from CKD/diabetic kidney disease (DKD) studies.

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