Introduction

The Turing health and medical sciences programme has long-term interests in personalised healthcare and treatment heterogeneity – the analysis of how medical treatments can affect different people in different ways. The programme is seeking to generate insights which improve the understanding of patient and disease heterogeneity and its relevance to clinical outcomes.

The goal of this partnership is to establish a world-leading collaboration in advanced analytics between Roche and the Turing, focused on enabling the transformative benefits of personalised healthcare to become a reality for patients around the world.  Publication of methods and algorithms will follow the principles of open science to ensure that they are reproducible and interoperable. 

Read the news story: The Alan Turing Institute launches a strategic partnership with Roche to generate insights into disease, patient, and outcome heterogeneity using advanced analytics

About Roche

Learn more about Roche here.

Background

This expanded strategic partnership follows a successful Data Study Group at the Turing in April 2019, and a 12-week research project later the same year, explored in the case study Turing and Roche: Towards tailor-made lung cancer treatment.

roche

Projects

Structured missingness in heterogeneous data

The aim of the project is to conduct review of current knowledge on learning from heterogeneous data with structured missingness. Findings will be disseminated to academic and industrial stakeholders and will be used as the basis for an ambitious research programme in learning healthcare outcomes from heterogeneous clinical data.

Community repository

Structured missingness workshop | Wednesday 10 November

Apply to attend

Opportunities and engagement 

For further information on the Partnership and how you can engage, feel free to watch this short video from our event hosted in July 2021.

Contact us

We look forward to hearing from you. If you have any questions about this work please contact [email protected].