Exploring the potential impact of multi-factor precision interventions in Alzheimer's disease with system dynamics
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Jeroen F Uleman1, René J F Melis2, Alfons G Hoekstra3
1Department of Geriatric Medicine, Radboudumc Alzheimer Center, Donders Institute for Medical Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands; Institute for Advanced Study, University of Amsterdam, Amsterdam, the Netherlands.
Abstract:
Numerous clinical trials based on a single-cause paradigm have not resulted in efficacious treatments for Alzheimer's disease (AD). Recently, prevention trials that simultaneously intervened on multiple risk factors have shown mixed results, suggesting that careful design is necessary. Moreover, intensive pilot precision medicine (PM) trial results have been promising but may not generalize to a broader population. These observations suggest that a model-based approach to multi-factor precision medicine (PM) is warranted. We systematically developed a system dynamics model (SDM) of AD for PM using data from two longitudinal studies (N=3660). This method involved a model selection procedure in identifying interaction terms between the SDM components and estimating individualized parameters. We used the SDM to explore simulated single- and double-factor interventions on 14 modifiable risk factors. We quantified the potential impact of double-factor interventions over single-factor interventions as 1.5 [95% CI: 1.5-2.6] and of SDM-based PM over a one-size-fits-all approach as 3.5 [3.1, 3.8] ADAS-cog-13 points in 12 years. Although the model remains to be validated, we tentatively conclude that multi-factor PM could come to play an important role in AD prevention.
Insights
A new system dynamics model (SDM) for Alzheimer's disease (AD) precision medicine (PM) shows promise. Multi-factor interventions using this model may significantly improve AD prevention compared to single-factor or one-size-fits-all approaches.
Area of Science:
- Neuroscience
- Computational Biology
- Public Health
Background:
- Numerous Alzheimer's disease (AD) clinical trials targeting single causes have failed to yield effective treatments.
- Recent multi-factor prevention trials show mixed results, highlighting the need for improved study design.
- Pilot precision medicine (PM) trials show promise but may lack generalizability to wider populations.
Purpose of the Study:
- To develop a model-based approach for multi-factor precision medicine (PM) in Alzheimer's disease (AD) prevention.
- To systematically develop a system dynamics model (SDM) for AD PM using longitudinal data.
- To explore the potential impact of single- and multi-factor interventions on modifiable risk factors.
Main Methods:
- Developed a system dynamics model (SDM) for AD PM using data from 3660 participants in two longitudinal studies.
- Employed a model selection procedure to identify interaction terms and estimate individualized parameters within the SDM.
- Simulated single- and double-factor interventions targeting 14 modifiable risk factors using the developed SDM.
Main Results:
- Quantified the potential impact of double-factor interventions as 1.5 times greater than single-factor interventions (95% CI: 1.5-2.6).
- Demonstrated that SDM-based PM could yield 3.5 points greater improvement on the ADAS-cog-13 scale over 12 years compared to a one-size-fits-all approach (95% CI: 3.1-3.8).
- Identified significant potential for multi-factor PM in Alzheimer's disease prevention.
Conclusions:
- A model-based approach to multi-factor precision medicine (PM) is warranted for Alzheimer's disease (AD) prevention.
- Multi-factor PM interventions, guided by an SDM, show potential for greater efficacy than traditional approaches.
- While validation is needed, multi-factor PM holds promise for the future of AD prevention strategies.
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