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Alzheimer's Disease: Combination Therapies and Clinical Trials for Combination Therapy Development
Jeffrey L Cummings1,2,3, Amanda M Leisgang Osse4,5, Jefferson W Kinney4,5
1Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV, Las Vegas, NV, USA. jcummings@cnsinnovations.com.
Abstract:
Alzheimer's disease (AD) is a complex multifaceted disease. Recently approved anti-amyloid monoclonal antibodies slow disease progression by approximately 30%, and combination therapy appears necessary to prevent the onset of AD or produce greater slowing of cognitive and functional decline. Combination therapies may address core features, non-specific co-pathology commonly occurring in patients with AD (e.g., inflammation), or non-AD pathologies that may co-occur with AD (e.g., α-synuclein). Combination therapies may be advanced through co-development of more than one new molecular entity or through add-on strategies including an approved agent plus a new molecular entity. Addressing add-on combination therapy is currently urgent since patients on anti-amyloid monoclonal antibodies may be included in clinical trials for experimental agents. Phase 1 information must be generated for each agent in combination drug development. Phase 2 and Phase 3 of add-on therapies may contrast the new molecular entity, the approved agent as standard of care, and the combination. More complex development programs including standard or modified combinatorial designs are required for co-development of two or more new molecular entities. Biomarkers are markedly affected by anti-amyloid monoclonal antibodies, and these effects must be anticipated in add-on trials. Examining target engagement biomarkers and comparing the magnitude and sequence of biomarker changes in those receiving more than one therapy, compared with those on monotherapy, may be informative. Using network-based medicine approaches, computational strategies may identify rational combinations using disease and drug effect network mapping.
Insights
Combination therapies are essential for Alzheimer's disease (AD) treatment, potentially combining new drugs with existing anti-amyloid monoclonal antibodies to slow cognitive decline. Further research is needed to optimize these combination strategies for greater patient benefit.
Area of Science:
- Neuroscience
- Pharmacology
- Clinical Trials
Background:
- Alzheimer's disease (AD) is a complex neurological disorder.
- Current anti-amyloid monoclonal antibodies offer modest slowing of disease progression (approx. 30%).
- Combination therapies are likely necessary for greater efficacy in preventing AD onset or slowing cognitive decline.
Purpose of the Study:
- To explore the necessity and strategies for combination therapies in Alzheimer's disease.
- To outline development pathways for co-developed and add-on combination therapies.
- To address the urgent need for combination therapy research, especially for patients on existing anti-amyloid treatments.
Main Methods:
- Review of potential combination therapy approaches (co-development vs. add-on).
- Consideration of clinical trial designs for add-on therapies (Phase 1, 2, 3).
- Emphasis on biomarker analysis in combination trials and network-based medicine for identifying rational combinations.
Main Results:
- Combination therapies may target core AD pathology, co-pathologies (e.g., inflammation), or co-occurring non-AD pathologies (e.g., alpha-synuclein).
- Add-on combination strategies are critical for patients currently receiving anti-amyloid monoclonal antibodies.
- Biomarker changes must be carefully evaluated in combination trials to understand drug effects.
Conclusions:
- Combination therapies represent a crucial next step in advancing Alzheimer's disease treatment.
- Strategic development, including robust clinical trial designs and biomarker analysis, is essential for successful combination therapy implementation.
- Computational approaches can aid in identifying optimal drug combinations for AD.
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