Alzheimer’s disease (AD), burdens every aspect of a person’s life and has a significant socio-economic impact. There is no cure for such a condition and available treatments only address (partially) some symptoms but do not slow disease progression. Only a fraction of people with dementia get a timely diagnosis and many more are at risk. However, we still do not understand the final play out of potential risks on prognosis and who will eventually become a patient and when. Lack of reliable and affordable diagnostic/prognostic tools hampers identifying people who could take part in clinical trials and diagnosis in clinical practice for disease management. On the other hand, increased success in diagnosis without a curative treatment being available could mean an exponential increase in disease numbers, leading to a potential collapse in health care systems already under hard pressure.
To tackle the above challenge, it is fundamental to foster an “all-around” approach, able to deliver from the lab to the clinic. Robust tools, methods, and resources are needed to significantly de-risk the dementia area and to transform scientific knowledge to outcomes for the patients. The achievement of such opportunities depends on the ability to break silos and work together with a common agenda, across the public-private space. The silos are both scientific (e.g. “disease silos”) and due to differences in culture and incentives among the complex stakeholder community (industry, academia, regulators, payers, etc.). Importantly, the patients must be partners to ensure meaningful outputs and outreach to the citizens for full societal impact. This approach of “radical collaboration” has been very successfully implemented by the public-private partnerships of the European Innovative Medicines Initiative. The aim of this research topic is to demonstrate the power of such collaborative efforts in delivering new knowledge and resources for the dementia research community and the patients, and to foster new approaches for the translation of research outputs into valuable outcomes for people with dementia.
Thus, topic editors will welcome any types of manuscripts supported by the Journal – comprised of research article, brief research article, review, and mini-review – pertaining, but not limited to the following themes:
• Understanding of AD natural history and disease taxonomy.
• Filling AD pipeline with targets beyond the “usual suspects”.
• Trustworthy tools and methods for translation from target to treatment, shortening timelines and increasing the robustness of the system and its outputs. This includes (digital) biomarkers and endpoints for patient stratification and treatment effect assessment.
• (Sustainable) Infrastructures (e.g. clinical trial networks, biobanks, platforms) to support pre-clinical and clinical research.
• Innovative solutions for patient screening, recruitment, and the early generation of the patient and payer-relevant data.
• Big data approaches, advanced data analytics, and modeling (machine learning/artificial intelligence) to support dementia R&D.
• patient involvement and collaboration in research and development, including gathering of patient preferences, ethical, legal, and social aspects of dementia research.
Submissions highlighting the patient/citizen active collaboration/contribution are particularly welcome.
Alzheimer’s disease (AD), burdens every aspect of a person’s life and has a significant socio-economic impact. There is no cure for such a condition and available treatments only address (partially) some symptoms but do not slow disease progression. Only a fraction of people with dementia get a timely diagnosis and many more are at risk. However, we still do not understand the final play out of potential risks on prognosis and who will eventually become a patient and when. Lack of reliable and affordable diagnostic/prognostic tools hampers identifying people who could take part in clinical trials and diagnosis in clinical practice for disease management. On the other hand, increased success in diagnosis without a curative treatment being available could mean an exponential increase in disease numbers, leading to a potential collapse in health care systems already under hard pressure.
To tackle the above challenge, it is fundamental to foster an “all-around” approach, able to deliver from the lab to the clinic. Robust tools, methods, and resources are needed to significantly de-risk the dementia area and to transform scientific knowledge to outcomes for the patients. The achievement of such opportunities depends on the ability to break silos and work together with a common agenda, across the public-private space. The silos are both scientific (e.g. “disease silos”) and due to differences in culture and incentives among the complex stakeholder community (industry, academia, regulators, payers, etc.). Importantly, the patients must be partners to ensure meaningful outputs and outreach to the citizens for full societal impact. This approach of “radical collaboration” has been very successfully implemented by the public-private partnerships of the European Innovative Medicines Initiative. The aim of this research topic is to demonstrate the power of such collaborative efforts in delivering new knowledge and resources for the dementia research community and the patients, and to foster new approaches for the translation of research outputs into valuable outcomes for people with dementia.
Thus, topic editors will welcome any types of manuscripts supported by the Journal – comprised of research article, brief research article, review, and mini-review – pertaining, but not limited to the following themes:
• Understanding of AD natural history and disease taxonomy.
• Filling AD pipeline with targets beyond the “usual suspects”.
• Trustworthy tools and methods for translation from target to treatment, shortening timelines and increasing the robustness of the system and its outputs. This includes (digital) biomarkers and endpoints for patient stratification and treatment effect assessment.
• (Sustainable) Infrastructures (e.g. clinical trial networks, biobanks, platforms) to support pre-clinical and clinical research.
• Innovative solutions for patient screening, recruitment, and the early generation of the patient and payer-relevant data.
• Big data approaches, advanced data analytics, and modeling (machine learning/artificial intelligence) to support dementia R&D.
• patient involvement and collaboration in research and development, including gathering of patient preferences, ethical, legal, and social aspects of dementia research.
Submissions highlighting the patient/citizen active collaboration/contribution are particularly welcome.