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Sensyne Health | Life Sciences

What we do

Build & Protect

We build large datasets of anonymised patient data in collaboration with the NHS, providing a rich source of clinical information while protecting patient privacy.

Curate & Analyse

We curate and analyse the datasets using AI algorithms.

Identify

We identify patterns using proprietary machine learning and deep learning technologies.

Discover

We discover new insights of significant value to patients, clinicians and the life science industry.

The Life Sciences team at Sensyne Health combines clinical and data science expertise to develop machine learning technologies applied to ethically sourced anonymised electronic patient record (EPR) data received from our unique partnership with the NHS.

We use EPR information to create large longitudinal datasets, then develop clinically driven AI technology that analyses and contextualises that information to identify previously unseen patterns and insights that can be used to undertake advanced medical research, improve pharmaceutical development and deliver better patient care.

The current medical discovery system involves interpreting enormous volumes of diverse information. It can be like finding a needle in a haystack, without knowing what a needle is, what a needle looks like or where the haystack is. We aim to change that.

Paul Drayson
CEO

For NHS organisations

We currently work collaboratively with a number of NHS Trusts in a unique and trusted partnership that drives medical research using real world evidence from large datasets of anonymised patient data. It’s a unique model of working where we ensure the NHS receives a commercial return via equity and a share in revenues as well as making a positive social impact.

Learn more about our NHS partnership approach

For life sciences organisations

In response to specific questions that our life sciences partners ask, we work with our own team and clinical experts in the NHS to analyse information about the progression of medical conditions. This enables pharmaceutical companies to use the results derived from clinical artificial intelligence to develop better-targeted drugs with a higher chance of success.

Learn more about our life sciences approach

What we say

Our thoughts, comments, progress, work in action and where we are talking.

Find our latest news

No ordinary job

Join our team. We’re looking for people who share our collective passion for solving healthcare’s biggest challenges.

Join the Life Sciences team

The way we work

Using real-world data has a real-world impact. We use it to:

Improve

Improve clinical trials by distinguishing specific groups of patients and Identifying sub-sets of responders and non-responders.

Understand

Understand the mechanism of disease in the real world in order to personalise treatment and coherently diagnose sufferers of poorly understood diseases.

Predict

Predict clinical events earlier such as stroke or heart failure.

Discover

Discover new treatments faster to address unmet medical needs.

Impact - Using real world evidence

Information based on RWE can provide vital indicators to better prevent, treat and understand the cause and progression of disease. It enables a level of insight and analysis simply not possible to achieve from other research datasets. It is richer, more extensive and more representative of large patient populations.

Approach - ‘Bedside to bench’

Traditionally, medicinal research starts in the lab. We take a different approach. From ‘bedside to bench’ deconstructing the classical R&D pipeline model by putting patient data and patient outcomes at the beginning of the drug discovery and development process.

Please upgrade your browser

We built this website using the latest browser technologies to deliver the very best experience.

What we do

The Life Sciences team at Sensyne Health combines clinical and data science expertise to develop machine learning technologies applied to ethically sourced anonymised electronic patient record (EPR) data received from our unique partnership with the NHS.

The current medical discovery system involves interpreting enormous volumes of diverse information. It can be like finding a needle in a haystack, without knowing what a needle is, what a needle looks like or where the haystack is. We aim to change that.

For NHS organisations

For life sciences organisations

What we say

Our thoughts, comments, progress, work in action and where we are talking.

No ordinary job

Join our team. We’re looking for people who share our collective passion for solving healthcare’s biggest challenges.

The way we work

Using real-world data has a real-world impact. We use it to:

Improve

Understand

Predict

Discover

Impact - Using real world evidence

Approach - ‘Bedside to bench’

Case Studies

Case study

Study on benefits of blood anticoagulants for heart failure patients

January 21, 2020

Case study

Personalising heart failure treatment

October 7, 2019

Case study

Improving stroke prediction

October 7, 2019

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