Accurate diagnosis and prognosis of Alzheimer’s disease in primary care
The overall objective of ADetect is to improve early diagnostics and prognostics of Alzheimer's disease in primary care by utilising novel plasma biomarkers and digital cognitive tests. Misdiagnosis of AD can reach >50% in primary...
ver más
30/09/2024
LUNDS UNIVERSITET
207K€
Presupuesto del proyecto: 207K€
Líder del proyecto
LUNDS UNIVERSITET
No se ha especificado una descripción o un objeto social para esta compañía.
TRL
4-5
Fecha límite participación
Sin fecha límite de participación.
Financiación
concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto
el día 2024-09-30
¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video
Información proyecto ADetect
Duración del proyecto: 25 meses
Fecha Inicio: 2022-08-01
Fecha Fin: 2024-09-30
Líder del proyecto
LUNDS UNIVERSITET
No se ha especificado una descripción o un objeto social para esta compañía.
TRL
4-5
Presupuesto del proyecto
207K€
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
The overall objective of ADetect is to improve early diagnostics and prognostics of Alzheimer's disease in primary care by utilising novel plasma biomarkers and digital cognitive tests. Misdiagnosis of AD can reach >50% in primary care, which has important consequences both at the personal and societal level. Misdiagnosis, however, can be reduced by measuring AD-related pathology. The novel plasma biomarkers may be a cost-effective alternative given their low invasiveness and costs. However, they have not been validated in primary care yet, where much more diverse groups of people are managed. Further, the addition of brief cognitive digital tests that do not require involvement of a specialist may further improve the diagnostic accuracy. Based on the most cost-effective biomarkers, collected in unique prospective study performed in primary care, we will develop algorithms for diagnosis and prognosis of AD in a diverse population, and share them in the form of open and freely available apps. The algorithms will be validated against current standard of truth biomarkers and enhanced to give personalized risk assessments based on patient’s characteristics. Finally, we will investigate whether prospective use of these algorithms will improve treatment, management and care of patients. The development of easy-to-use tools, built on novel cognitive tests and plasma biomarkers, has huge potential to increase the diagnostic accuracy in primary care. A more accurate and timely diagnosis will lead to earlier initiation of currently available AD treatments. Further, when disease-modifying treatments become globally available, there will be an immense pressure on the healthcare system to identify eligible patients. Given the high prevalence of AD, its identification will primarily take place in primary care. With the easy-available proposed biomarkers, we have a great opportunity to develop the necessary tools for primary care to undertake this important task