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Updated: Sep 12, 2025

A High-Throughput Luciferase Assay to Evaluate Proteolysis of the Single-Turnover Protease PCSK9
Published on: August 28, 2018
A Case Study of Model-Informed Drug Development of a Novel PCSK9 Antisense Oligonucleotide. Part 2: Phase 2 to Phase
Jane Knöchel1, Catarina Nilsson1, Björn Carlsson2
1Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, AstraZeneca AB R&D, Gothenburg, Sweden.
Abstract:
In this second part of a case study on the practical use of model-informed drug development (MIDD), we describe the clinical development of AZD8233, a novel proprotein convertase subtilisin/kexin type 9 (PCSK9) antisense oligonucleotide, from phase 2b to the start of phase 3. The case study exemplifies the use of MIDD to answer key design questions for the phase 3 program, including the design of a pivotal phase 3 study, a head-to-head study, and a cardiovascular outcome study informed by model-averaging analysis. Extensive phase 3 study simulations assessed the impact of drop-out, readout timing, dose frequency, and analysis method on study outcomes. The final phase 3 design assumed around 1% monthly drop-out (based on other PCSK9 inhibitor trials), used an EMA/FDA-approved analysis method, and set the primary readout at week 16. A simulated study predicted a reduction in low-density lipoprotein cholesterol (LDL-C) by week 16 of -69% with AZD8233 60 mg every 4 weeks. A virtual head-to-head study showed AZD8233 lowered LDL-C by 27% more than an active competitor (inclisiran) at day 270. Predicted cardiovascular relative risk reduction (RRR) for AZD8233 on top of statins ranged from 24% to 49% based on model choice; a model-averaging approach predicted an RRR of 27% assuming 63% LDL-C reduction from a 130 mg/dL baseline. This case study highlights the importance of cross-functional collaboration and other key MIDD enablers to ensure that MIDD extends beyond a simple simulation exercise and is instead considered an integral part of drug development dedicated to quantitative decision making.
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