Organising mechanistic knowledge about neurodegenerative diseases for the improvement of drug development and therapy
Today, diseases are defined largely on the basis of symptoms, yet while two patients may share the same diagnosis, the underlying causes of their symptoms may be very different. This means that a treatment that works in one patient may prove ineffective in another. There is now broad recognition that a new approach to disease classification is needed, and that is where the AETIONOMY project came in. AETIONOMY aimed to pave the way towards a new approach to the classification of neurodegenerative diseases, particularly Alzheimer’s and Parkinson’s diseases, thereby improving drug development and increasing patients’ chances of receiving a treatment that works for them.
Two key project outputs are:
- The AETIONOMY Knowledge Base, a unification point of the knowledge and data management on neurodegeneration with a main focus on Alzheimer’s and Parkinson’s diseases.
- NeuroMMSig, a mechanistic interpretation of multiscale, multimodal clinical data, representing essential pathophysiology mechanisms of neurodegenerative diseases. Researchers can explore the biology that underpins disease development through this user interface.
European Medical Information Framework
The EMIF project aimed to develop a common information framework of patient-level data that links up and facilitates access to diverse medical and research data sources, opening up new avenues of research for scientists. The project focussed initially on questions relating to obesity and Alzheimer’s disease to provide a focus and guidance for the development of the framework.
Click here to download the EMIF Brochure providing an overview of the main achievements to date.
During its project lifetime, EMIF has developed and made the EMIF Data Catalogue publicly available to the research community. The EMIF Data Catalogue is a text-book example of EMIF’s mission to improve identification, access and assessment, and (re)use of health data within the European Union. You can access it from here.
MOPEAD - Models of patient engagement for Alzheimer’s disease
Since researchers are increasingly focusing their efforts on better understanding the early onset of dementia and finding ways to prevent its onset in the first place, they need to work with people who are still in the very earliest stages of the disease. The MOPEAD project aimed to identify and test different models for engaging with this important group and to determine which models work best in different situations. The project also aimed to better understand the earliest stages of dementia and works to facilitate recruitment for clinical trials. Findings from the research project are currently under submission in scientific journals and will be made available on the project website.
PRISM - Psychiatric Ratings using Intermediate Stratified Markers: providing quantitative biological measures to facilitate the discovery and development of new treatments for social and cognitive deficits in AD, SZ, and MD
Social withdrawal is a common early symptom of many neurological disorders, including schizophrenia, Alzheimer’s disease, and major depressive disorder. However, the underlying, biological causes of this symptom are still poorly understood and may differ from one disease to another. The PRISM project carried out a range of tests, including blood tests, brain scans, and measures of behaviour, on patients with these diseases in a bid to determine which biological parameters correlate with specific clinical symptoms, like social withdrawal. The hope is that the project’s findings will shed new light on the causes of mental illness and their symptoms and facilitate the development of much-needed new treatments.
Real world outcomes across the Alzheimer's disease (AD) spectrum for better care: multi-modal data access platform
Currently, strictly controlled clinical trials are used to assess the safety and benefits of potential AD treatments for patients. However, clinical trials do not provide information on the health benefits for patients in their daily lives, the ‘real world’. The ROADMAP project aimed to deliver a series of methods and tools that allow the scalable, transferable integration of data on patient outcomes in the real world. The tools were developed and tested through pilot exercises. The project conducted patient engagement and addressed ethical, legal and social implications of adopting a real world evidence approach to Alzheimer’s disease.
The project was part of IMI’s Big Data for Better Outcomes programme, which aims to facilitate the use of diverse data sources to deliver results that reflect health outcomes of treatments that are meaningful for patients, clinicians, regulators, researchers, healthcare decision-makers, and others.
ROADMAP's Interactive Data Cube offers an overview of availability of European real-world data on Alzheimer's disease - have a look at the tool via this link: https://datacube.roadmap-alzheimer.org