ARIA-E and isolated ARIA-H in CLARITY AD: pharmacokinetic and pharmacodynamic analyses
<h3>Background</h3> Amyloid-related imaging abnormalities (ARIA) due to oedema/effusion (ARIA-E) or haemorrhage (ARIA-H) have been observed in patients with Alzheimer’s disease (AD) treated with lecanemab. Pharmacokinetic/pharmacodynamic (PK/PD) analyses were performed to explore the potential relationship between the incidence of ARIA, lecanemab exposure and key covariates. <h3>Methods</h3> A total of 177 ARIA-E and 150 ARIA-H incidences were analysed. ARIA-E rate was modelled as a function of lecanemab steady-state exposure and covariates effects were explored. Graphical PK/PD analysis was performed to examine the relationship between isolated ARIA-H and lecanemab exposure. <h3>Results</h3> The observed ARIA-E incidence was modelled using lecanemab maximum concentration at steady-state (Css,max) with <i>ApoE4</i> genotype being a significant covariate. Homozygous carriers had a higher incidence than non-homozygous or noncarriers (p<0.0001). At a mean lecanemab Css,max=305 µg/ml, the predicted ARIA-E incidence was 5.45% in noncarriers, 9.85% in heterozygous, and 28.0% in homozygous carriers. No other covariate had a significant effect on ARIA-E incidence. No relationship was found between the incidence of ARIA-H and lecanemab exposure, but it was associated with <i>ApoE4</i>, with homozygotes having the highest incidence. <h3>Conclusions</h3> ARIA-E incidence increased with lecanemab Css,max, while isolated ARIA-H was unaffected. <i>ApoE4</i> genotype influenced both types of ARIA, with homozygous carriers showing higher incidences.
Authors
- Osamu Takenaka
- Youfang Cao (ORCID: https://orcid.org/0000-0002-5880-0006)
- Reyderman Larisa
- Majid Oneeb
- Hussein Ziad
- Willis Brian A
- Penner Natasha
- Yasuda Sanae
- Todd Lauren
- George Charlotte
Institutions
- Eisai (United Kingdom) (GB)
- Eisai (United States) (US)
- Eisai (Japan) (JP)
Publication Details
- Published
- 2024-11-01
- DOI
- https://doi.org/10.1136/jnnp-2024-abn.140
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.00