AbstractBackgroundLecanemab is a humanized IgG1 monoclonal antibody that binds with high affinity to Aβ soluble protofibrils. Lecanemab has been tested as a disease‐modifying treatment for early Alzheimer’s disease in two clinical studies (NCT01767311 and CLARITY‐AD, NCT03887455). As part of these studies, amyloid PET scans were collected in a subset of patients, demonstrating that lecanemab leads to pronounced reduction in brain amyloid.MethodA model describing the relationship between serum lecanemab exposure and brain amyloid reduction from baseline was developed using data pooled from Phase 2 and 3 studies. Individual serum lecanemab exposure was estimated using a population PK model and correlated with amyloid PET using an indirect response model, with a lecanemab‐dependent increase in the degradation rate of amyloid, introduced as linear function. The model was parametrized in terms of baseline amyloid load, elimination rate constant for amyloid removal (Kout) and exposure effect (DESLP). Inter‐subject variability was estimated for each of the model parameters. Covariates were included in the model using a forward‐inclusion (p<0.01) /backwards‐elimination (p<0.001) approach.ResultA total of 4129 observations from 1088 subjects were included in the dataset. The model estimate of Kout was 0.0496 yr−1 (95% confidence interval: 0.0206, 0.0827), suggesting a re‐accumulation half‐life of brain amyloid of ∼14 years. APOE4 carrier status (homozygous and heterozygous together) was a statistically significant predictor of baseline amyloid (APOE4 noncarriers: 65 CL; APOE4 carriers: 83 CL). Age was a significant covariate on DESLP, with older patients removing amyloid at a faster rate than younger patients. None of the other covariates explored, including presence of antidrug antibodies or baseline MMSE score, had a statistically significant effect on any model parameter.ConclusionAn exposure‐response model has been developed that describes the change in brain amyloid over time during treatment with lecanemab and after stopping lecanemab treatment. This model provides additional insights into factors that may drive differences in the rate of brain amyloid removal between patients.
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