From Radiocopper to Cold Copper: Mechanistic Modeling and Simulation to Define Clinical Response Criteria and Biomarkers for <scp>VTX</scp> ‐801 in Wilson Disease

We developed a comprehensive, mechanistic model of human copper metabolism to support biomarker qualification for VTX-801, an adeno-associated vector-based gene therapy which is being developed to restore the mutated ATP7B copper transporter gene in Wilson disease (WD). The model integrates physiological copper kinetics with pathophysiological features of WD by distinguishing between ceruloplasmin-bound and non-ceruloplasmin-bound copper (NCC), and by explicitly incorporating ATP7B-dependent processes: biliary excretion and ceruloplasmin loading of copper. Literature-derived time-activity data from healthy subjects, heterozygous carriers, and WD patients, as well as clinical radiocopper data in plasma and feces from a pilot study in non-WD subjects, were used for model development and validation. VTX-801's dose-response was quantified in WD mouse models using ceruloplasmin oxidase activity measurement and ⁶⁴Cu fecal excretion. This enabled derivation of activity factors (AFs) corresponding to restored ATP7B function, with 15% and 40% selected as minimal and optimal efficacy targets. Simulations linked AFs to clinical biomarkers, demonstrating that the 48/2-h plasma radioactivity ratio can effectively differentiate VTX-801 responders from non-responders, providing a decision criterion to safely withdraw standard treatment in participants of a phase 1/2 trial. To broaden applicability beyond radiotracer studies, we simulated "cold" copper kinetics under steady-state conditions, deriving expected values for plasma copper, NCC, urinary copper excretion, and relative exchangeable copper (REC). These simulations suggest that REC may also serve as a suitable and simpler to implement, non-radioactive biomarker for ATP7B gene therapy. This model provides a robust quantitative framework to assess copper-related biomarkers in WD and their response to treatment in silico. Trial Registration: EudraCT number: 2019-001157-13.