AETIONOMY clinical study recruitment reaches 283 patients recruited

AETIONOMY an IMI funded project, has now recruited over 283 people into the Parkinson’s Disease portion of the European clinical study on neurodegenerative diseases such as Parkinson’s and Alzheimer’s diseases. This milestone means that the project more than 50% completed in both the AD and the PD portion. The Alzheimer’s disease portion is being recruited via EPAD* which has now recruited a total of 289 subjects of which 82 were recruited at the joint center BBRC.

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Developing a “mechanism-based taxonomy” of Alzheimer´s and Parkinson´s Disease.

Currently, the established disease classification systems such as ICD (international classification of disease) make use of phenotypes measured clinically or using standard laboratory and imaging techniques to establish major types and subtypes of diseases.

In contrast to the established disease classification systems, a “mechanism-based taxonomy” is based upon the knowledge about the biological pathways involved in the aetiology of a disease to guide the classification of disease classes and subclasses.

A specific challenge we face in the course of the AETIONOMY project lies in the fact that for most neurodegenerative diseases the dysfunctional biological pathways underlying the disease are not known. AETIONOMY will therefore have to first define new routes towards the identification of the underlying disease mechanisms before organising these and proposing a rational disease taxonomy for Alzheimer’s and Parkinson’s disease. Moreover, we will validate the mechanism-based taxonomy at least partially in the course of a prospective clinical study.

The Virtual Dementia Cohort (VDC): A platform for in-silico testing and validation of candidate mechanisms

Access to clinical datasets is usually restricted by data owners. This results in lengthy legal/ethical approvals and additional data processing efforts. AETIONOMY proposed a way out of this dilemma by the generation of free, virtual patient cohorts.

Our rationale is as follows: Ultimately, all clinical studies are just data. For many of the variables measured in studies like ADNI and PPMI we actually know the distribution of values; for other variables we may quantify our a priori knowledge and assume a distribution around its known mean. The data will be introduced into forward modeling approaches (integrative cause-and-effect modeling informed by biology) and linked to generative brain network models (The Virtual Brain) to create individual Virtual Patient brain models, which produce the entire range of human brain imaging data using Monte Carlo simulations (or related methods). The virtual cohort can by challenged by real-world data any time; it can be “optimised” to fit observational data or distributions observed in ADNI or PPMI or any other cohort better, if desired. Randomizer functions, however, can be used to generate diversity in variables wherever we believe that this should be helpful and lead to better representation of what we know about real patients.



4th AETIONOMY General Assembly on 30th November / 1st December 2017 in Basel (CH) at the site of partner Novartis.

About IMI

AETIONOMY is an IMI funded project (EU and EFPIA effort).