Rosa Webinar Series

Webinar Program

The Q-ATN Model of Alzheimer’s Disease: A Work in Progress

Norman A. Mazer, M.D., Ph.D.
Founder and Disease Modeling Consultant, NAM Consulting, Basel, Switzerland

The Q-ATN model is a quantitative, semi-mechanistic model of Alzheimer’s Disease (AD) based on the amyloid (A)/tau (T)/neurodegeneration (N) framework proposed by Clifford Jack Jr. and colleagues [1, 2]. It describes both the natural history of AD as well as the effect of anti-amyloid therapy on A/T/N biomarkers and the clinical outcome measure, CDR-SB. A full description of the Q-ATN model was published one year ago [3] and an update, based on the phase 3 results reported for gantenerumab [4] and lecanemab [5] was presented at the AAIC 2023 meeting [6].

The objectives of this presentation will be to:
- Describe the 4 sequential linkages between the A/T/N biomarkers and CDR-SB that are hypothesized in the Q-ATN model and the data that informed them.
- Explain how treatment with anti-amyloid antibodies can “bend” the trajectory of AD relative to natural history or placebo groups.
- Compare Q-ATN simulations with the available phase 3 trial data on anti-amyloid antibodies including the recent results on Donanemab [7].
- Discuss the current strengths and weaknesses of the Q-ATN model and the potential for further development.

1. Neurology. 2016; 87: 539-547.
2. Alzheimer’s & Dementia. 2018; 14: 535-562.
3. Alzheimer’s & Dementia. 2023 Jun;19(6):2287-97.
4. GRADUATE I and II: Topline Results of Two Global, Phase III, Randomized, Placebo-Controlled Studies Assessing the Efficacy and Safety of Subcutaneous Gantenerumab in Early Alzheimer’s Disease. Presented at CTAD 2022, San Francisco, CA, USA.
5. Imaging, Plasma, and CSF Biomarkers Assessments from Clarity AD. Presented at CTAD 2022, San Francisco, CA, USA.
6. Re-estimation of drug-specific amyloid removal parameters and the rate constant for pathogenic tau turnover brings the Q-ATN model into better alignment with recent phase 3 data from gantenerumab and lecanemab. Presented at AAIC 2023, Amsterdam, The Netherlands.
7. JAMA. 2023 Aug 8;330(6):512-27.