Progression of neurodegeneration in familial Alzheimer's disease (Fonteijn, et al., NeuroImage 2012)

Progression of neurodegeneration in familial Alzheimer’s disease (see Fonteijn, et al., NeuroImage 2012)

The EuroPOND initiative is a unique team of scientists spanning computational neuroscience and clinical neurology. Together we are developing computational models and using state-of-the-art data-science techniques to understand a range of neurological disorders. We are learning characteristic patterns of progression directly from large medical data sets including Alzheimer’s disease, Multiple Sclerosis, normal ageing, and abnormal brain development in preterm infants. These disease signatures will enable improved diagnosis and management of neurological disorders.

The Challenge

The global ageing population has placed neurodegenerative diseases among the biggest public health challenges of 21st century healthcare. We must understand this spectrum of diseases on both mechanistic and phenotypic levels to inform diagnosis, prognosis, monitoring, therapy development, and treatment & care decisions.

The Vision

Our vision is to provide new avenues for understanding the complexity of neurological diseases. Disentangling this complexity by identifying signatures of each disease is essential for meeting the challenge.

The Means

We are building the tools for achieving this vision using data-driven computational-and-statistical modelling, a set of powerful approaches with the ability to provide fine-grained and uniquely holistic pictures of disease progression. Such emerging technologies will underpin support systems for clinical and drug-development applications, specifically by enabling precision medicine through differential diagnosis, patient staging, and personalised prognosis.

The Strategy

We will impact the field through a balance between model utility and complexity. Model utility is the end-game focus in order to impact disease management across the full spectrum from patients to medical health professionals and drug-development companies. Model complexity is unavoidable due to the nature of the disease signatures we seek, and requires methodological development, which is one of EuroPOND’s strengths.