The development of disease-modifying treatments for Alzheimer's disease (AD) faces a number of barriers. Among these are the lack of surrogate biomarkers, the exceptional size and duration of clinical trials, difficulties in identifying appropriate populations for clinical trials, and the limitations of monotherapies in addressing such a complex multifactorial disease. This study sets out to first estimate the consequent impact on the expected cost of developing disease-modifying treatments for AD and then to estimate the potential benefits of bringing together industry, academic, and government stakeholders to co-invest in, for example, developing better biomarkers and cognitive assessment tools, building out advanced registries and clinical trial-readiness cohorts, and establishing clinical trial platforms to investigate combinations of candidate drugs and biomarkers from the portfolios of multiple companies. Estimates based on interviews with experts on AD research and development suggest that the cost of one new drug is now $5.7 billion (95% confidence interval (CI) $3.7–9.5 billion) and could be reduced to $2.0 billion (95% CI $1.5–2.9 billion). The associated acceleration in the arrival of disease-modifying treatments could reduce the number of case years of dementia by 7.0 million (95% CI 4.4–9.4 million) in the United States from 2025 through 2040.
As scientific knowledge about gene-environment interactions and the role of epigenetic factors in gene expression grows, new possibilities for personalized medicine may be opened up. In particular, the associations that have been demonstrated between epigenetic markers and certain diseases are an exciting development for personalized medicine. These advances also create new ethical challenges, regarding causal and moral responsibility, due to unique characteristics of how epigenetic effects regulate gene expression, are established and may change over the course of a person's life. This article examines the ethical implications of integrating epigenetic knowledge into personalized medicine.
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