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Enable drug R&D for Alzheimer’s disease: from animal models to computational models

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Alzheimer’s disease (AD) and dementia are posing devastating threat to public health and socioeconomy across the world. According to the World Health Organization (WHO), “the total number of people with dementia worldwide in 2010 is estimated at 35.6 million and is projected to nearly double every 20 years,” ...

Alzheimer’s disease (AD) and dementia are posing devastating threat to public health and socioeconomy across the world. According to the World Health Organization (WHO), “the total number of people with dementia worldwide in 2010 is estimated at 35.6 million and is projected to nearly double every 20 years,” and “the total estimated worldwide costs of dementia were US$ 604 billion in 2010.” (Dementia: A Public Health Priority, WHO, 2012) These striking estimates call for urgent availability of efficacious therapeutics, especially disease modifying ones that can slow down disease progression. The etiology of AD remains to be elucidated. The weight of evidence, largely accumulated in the past three decades, has been supporting the amyloid cascade hypothesis. Based on this hypothesis, heroic efforts in the academia and pharmaceutical industry have been going on to identify safe and efficacious amyloid beta lowering agents. Despite tremendous investment, the progress in this regard has been hampered by failures due to lack of efficacy or severe toxicological findings. The amyloid hypothesis, however, remains to be rigorously tested in the clinic.
Drug research and development (R&D) has been plagued with skyrocketing cost and plunging productivity. This is especially true in the neuroscience therapeutic area. Researchers have argued that an increase in the productivity may result from a revamp of research operations at early discovery stages (Dimitri 2011; Williams 2011). Along the same line, we believe that the R&D of disease modifying drugs for AD can benefit from further understanding of the mechanisms and related biochemical events pertinent to the disease, exploration and application of electrophysiological and imaging techniques to assess efficacy of compounds preclinically and clinically, and transition from qualitative to quantitative thinking. Close collaboration between experts in these areas will likely improve the possibility of success. Therefore, we call submissions in these areas, specifically research:
• enhancing understanding of the etiology of AD at the genetic and molecular levels in animal models or humans;
• exploring electrophysiological and imaging techniques to assess compound efficacy preclinically or clinically, or to enable preclinical to clinical translation;
• applying computational models, e.g., PK/PD models, statistical models, empirical-mechanistic hybrid models, to guide cost-effective discovery processes, translate from preclinical models to humans, and assess pharmacological effects in the clinic.
Original research papers are most desired; also welcome are reviews, perspectives, methods, and technology reports.


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