Reuse of R&D data and the promise of FAIR data lakes

Talk at BioData World Congress 2019 

 

FAIR data lakes

Reuse of R&D data and the promise of FAIR data lakes – Talk by Kees van Bochove at BioData World Congress 2019

 

At the Bio Data World conference in Basel in December 2019, Kees van Bochove, Founder of The Hyve gave a talk on re-use of pharma R&D data, and what strategies could be used to realize operationalization of FAIR data at scale.

 

Tackling the Clinical Data Challenges When Analyzing a Million Genomes 

Talk at BioIT World 2019 

Clinical data challenges

Tackling the Clinical Data Challenges When Analyzing a Million Genomes – Talk by Kees van Bochove at Bio-IT World Expo 2019

 

Population genetics and genomics is an emerging topic for the application of machine learning methods in healthcare and biomedical sciences. Currently, several large genomics initiatives, such as Genomics England, UK Biobank, the All of Us Project, and Europe’s 1 Million Genomes Initiative are all in the process of making both clinical and genomics data available from large numbers of patients to benefit biomedical research. However, a key challenge in these initiatives is the standardization of the clinical and outcomes data in such a way that machine learning methods can be effectively trained to discover useful medical and scientific insights. In this talk, we will look at what data is available at scale, and review some of examples of the application of common data and evidence models such as OMOP, FHIR, GA4GH etc. in order to achieve this, based on projects which The Hyve has executed with some of these initiatives to harmonize their clinical, genomics, imaging and wearables data and make it FAIR.

 

How 2019 became the year FAIR landed in biopharmaceutical R&D

Keynote at Proventa International’s Bioinformatics East Coast Strategy Meeting 2019 and Talk at Pharmaceutical IT & Data Congress 2019

 

FAIR biopharmaceutical

How 2019 became the year FAIR landed in biopharmaceutical R&D – Talk by Kees van Bochove at Proventa’s Bioinformatics Strategy Meeting 2019 and Pharmaceutical IT & Data Congress 2019

 

  • Fairspace: a new cloud service to enable collaborative science
  • Implementation of FAIR in practice: which of the 15 principles to start with and what’s the RoI?
  • Common Data Models: OMOP/OHDSI, i2b2/tranSMART, CDISC, FHIR, etc: how do they relate, and which one to choose

 

Large scale observational clinical research with OHDSI 

Talk at i2b2 tranSMART Tübingen Symposium 2019

 

observational clinical research OHDSI

Large scale observational clinical research with OHDSI – Talk by Maxim Moinat at i2b2 tranSMART Foundation Symposium 2019

 

Observational Health Data Sciences and Informatics (OHDSI) is a multi-stakeholder,  interdisciplinary, international collaborative with a mission to improve health by empowering a community to collaboratively generate the evidence that promotes better health decisions and better care. With 200 researchers from 25 countries and half a billion unique patients, OHDSI carries out federated studies at sufficient scale to answer questions about diagnosis and treatment. At the heart of the OHDSI platform is the OMOP Common Data Model, currently at v6, around which a toolset is built for carrying out reusable, repeatable and reproducible observational clinical research on a large scale.

 

Overview of the features and architecture of Glowing Bear and tranSMART

GlowingBear tranSMART features & architecture

Overview of the features and architecture of Glowing Bear and tranSMART – Talk by Gijs Kant at i2b2 tranSMART Foundation Symposium 2019

Talk at i2b2 tranSMART Tübingen Symposium 2019

 

Glowing Bear is a cohort selection user interface for the TranSMART clinical data warehouse. In recent years, features for several use cases have been added: time series data, standard ontologies, family relations, sample-level lab data. Meanwhile, the structure of the platform has been transformed to be more modular and maintainable. We give an overview of the added features and the changes to the data model and architecture.

 

Easy and secure deployment of Glowing Bear and tranSMART

GlowingBear tranSMART deployment

Easy and secure deployment of Glowing Bear and tranSMART – Talk by Ewelina Grudzién at i2b2 tranSMART Foundation Symposium 2019

Talk at i2b2 tranSMART Tübingen Symposium 2019

 

Deployment of tranSMART and all its dependencies used to be a complex task, mainly because of many dependencies, different versions and configuration options. With the new structure of the platform, dockerization of all its components and a main compose scripts it is not only faster to deploy everything, but also easier to manage the configuration, ensure security and monitor the components.

 

Building ETL pipelines for tranSMART 17.X – New tools for the data loader

ETL pipelines tranSMART 17

Building ETL pipelines to tranSMART 17.X – Talk by Alessia Peviani at i2b2 tranSMART Foundation Symposium 2019

Talk at i2b2 tranSMART Tübingen Symposium 2019

 

An overview of data loading tools to tranSMART 17.X for Jupyter Notebook and automated ETL pipelines

 

Applying the OMOP data model & OHDSI software to national European health data registries: the IMI EMIF project

Talk at SCOPE Summit 2017 –  Real World Data track 

 

Open source for RWD

Open source community for “Real World Data” Analysis – Talk by Kees van Bochove at SCOPE Summit 2017

 

A large open source initiative for standardisation and epidemiological analysis for real world data is OHDSI: Observational Health Data Sciences and Informatics. OHDSI leverages the OMOP common data model for observational data, and provides data analysis tools for a broad range of use cases. This talk will explain OMOP and OHDSI with case study IMI EMIF, in which health data from over 50 million patients from 13 national and regional European registries is brought together.