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P21. Neuronet: Improving data access and the development of predictive models

Detailed programme and abstracts

P21.1. EQIPD - European Quality In Preclinical Data

MACLEOD Malcolm1, STECKLER Thomas2, on behalf of The European Quality in Preclinical Data consortium

1University of Edinburgh, Edinburgh, United Kingdom, 2Janssen, Beerse, Belgium

To date, efforts to develop disease modifying treatments for Alzheimer’s disease have been unsuccessful. In addition to the therapeutic challenge of arresting and reversing complex neurodegenerative processes, the preclinical literature is characterised by a low prevalence of reporting of measures which might reduce risks of bias such as randomisation and blinding; over-estimation of efficacy in such studies; a degree of flexibility in the outcome measures reported; and evidence suggesting selective outcome reporting bias (https://doi.org/10.1002/ebm2.15, https://doi.org/10.1371/journal.pbio.1001609). These shortcomings are widely prevalent across biomedical research, and have only become apparent through the curation and analysis of large datasets collated from hundreds of individual studies.

The European Quality in Preclinical Data (EQIPD) IMI consortium seeks to address these issues through a coordinated and multidimensional approach:

We are conducting systematic reviews of data from published and unpublished experiments to evaluate the performance of key experimental approaches.

A systematic review of guidelines for in vivo research has informed a Delphi process providing a thematic overview of recommendations.

We are conducting a series of in vivo experiments (Open Field, Sleep Wake EEG and Irwin test) across multiple academic and industry labs to explore reasons for different findings across labs

We are developing the content and governance of a research quality system suitable for implementation across different types of labs.

We are developing a training platform in relation to experimental design and to the operation of the quality system

We have developed data standards and data warehousing for data collated from reviews of published data; historical industry datasets; and new data generated during the project.

Key additional outputs will include an annotated repository of primary research in Alzheimer’s disease, and a systematically collated set of guidelines for the conduct of in vivo research, to inform the curriculum for research training and continuing professional development.

P21.2. EMIF - European medical information framework

VISSER Pieter Jelle

Maastricht University, Amsterdam UMC, Netherlands

Alzheimer’s disease (AD) is the most common form of dementia. There is yet no treatment available and many clinical studies investigate the underlying pathophysiology, prognosis, and diagnosis of AD. Collaborations between individual studies will increase sample size and this will likely foster progress in clinical AD research. The European Medical Information Framework for Alzheimer’s disease (EMIF-AD, www.emif.eu) was set-up to facilitate re-using and combining AD-related data and ended in June 2018. First, we will give an overview of the infrastructures that were developed as part of the project: 1. the EMIF-AD catalogue which includes meta-data of over 50 cohorts; the EMIF-AD tranSMART database, which includes harmonized subject level data of over 8 cohorts; and the EMIF-AD switchbox which gives remote access to 4 local databases. Next we will present 3 cohorts that were set-up as part of EMIF by enriching ongoing studies with new assessments: the EMIF-AD preclinAD study in 260 cognitively normal individuals, the EMIF-AD 90+ study in 120 elderly older than 90 years, and the EMIF-AD multimodality biomarker discovery in 1200 individuals. We will present major scientific achievements on prevalence and course of predementia AD, genetic and environmental riskfactors for amyloid pathology, the effect of amyloid pathology on cognition in non-demented individuals. Finally, future plans of EMIF-AD will be discussed.

P21.3. ROADMAP - Real world outcomes across the AD spectrum for better care: Multi-modal data access platform

GALLACHER John1, BOUVY Jacoline2, DE REYDET DE VULPILLIERES Frédéric3, DÍAZ Carlos4, LEVITCHI Mihaela5, REED Catherine6, VAN DER LEI Johan7

1University of Oxford, United Kingdom, 2NICE, London, 3Novartis, Switzerland, 4SYNAPSE, Spain, 5Biogen, United States, 6Lilly, United Kingdom, 7Erasmus University, Netherlands

ROADMAP is a public-private partnership to evaluate the usability of multiple data sources, including real-world evidence (RWE), in the decision-making process for new treatments in Alzheimer’s disease (AD), and to advance concepts in disease and pharmacoeconomic modeling. ROADMAP will identify key disease and patient outcomes for stakeholders to make informed funding and treatment decisions, deliver data integration methods and standards, and develop conceptual cost-effectiveness and disease models designed in part to assess whether early treatment provides long-term benefit. ROADMAP provides a stakeholder consensus approach to optimizing patient and societal benefit from new AD treatments.  Initial findings from ROADMAP on the accessibility of real world data, its utility for disease modeling and policy formation will be discussed.

P21.4. IM2PACT – Investigating mechanisms and models predictive of accessibility of therapeutics into the brain

TBC

United Kingdom

 This session is organised by Neuronet.

 

 
 

Last Updated: Thursday 22 August 2019

 

 
  • Acknowledgements

    The 29th AE Conference in The Hague received funding under an operating grant from the European Union’s Health Programme (2014-2020). Alzheimer Europe and Alzheimer Nederlands gratefully acknowledge the support of all conference sponsors.
  • European Union
  • Roche
 
 

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