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25 April 2023

PrecisionLife completes data access agreement with King's College London to enable new precision neuroscience treatments and diagnostics in MND/ALS

The techbio company, PrecisionLife, announced that it has agreed a data access and licensing agreement with King’s College London to enable it to generate and commercialise novel insights into Motor Neurone Disease (MND). The agreement will enable the Oxford-based company to identify new MND biomarkers and attract investment and partners to enable the development of new treatments and diagnostic tools.

A person at a laptop keyboard typing, you can only see their hands and the keyboard. A padlock logo is in the middle to show data protection.

PrecisionLife uses a powerful analytics platform to analyse data from large disease populations, generating a much deeper understanding of complex diseases like MND than is possible by other methods.

MND - also known as Amyotrophic Lateral Sclerosis (ALS) and Lou Gehrig's Disease - is a complex disease with variations in symptoms, rate of progression, risk factors and the biological drivers of disease. The platform is able to stratify patients, i.e. it categorises MND patient populations into subgroups that have similar causes and drivers of disease, offering new hope for the development of precision medicine therapies matched to patient needs.

The MND Collections is an MND Association funded resource curated by the MND Association and Professor Ammar Al-Chalabi’s research group at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) at King's College London, working in collaboration with academic clinicians at the universities of Birmingham and Sheffield. The collections rely on more than 3,000 blood samples and clinical information from MND patients and healthy donors, collected between 2003 and 2012.

King’s has provided access to the patient data at the request of MND Association and in collaboration with Professor Al-Chalabi. Sample donor confidentiality is assured by anonymisation of all data and PrecisionLife’s adherence to the highest data security and privacy standards.

Research is at it's most effective when there is active collaboration in the pursuit of a common goal. This agreement speaks to the momentum that MND research is experiencing and I am excited about its potential to bring new developments in this field.

Professor Ammar Al-Chalabi, Professor of Neurology and Complex Disease Genetics, King’s IoPPN

PrecisionLife has previously used its platform to identify 33 new genes associated with increased risk for MND as well as patient stratification biomarkers (PSBs) distinguishing patient subgroups that may respond to targeted treatment approaches. These findings can be applied to the validation of novel drug targets, identification of drug repurposing opportunities, the development of better diagnostic tools, and the selective recruitment of patients into clinical trials who are most likely to respond to new medicines – improving their probability of success.

PrecisionLife has also undertaken retrospective analysis of Phase III clinical trial data in Central Nervous System (CNS) disorders to identify biomarkers of drug response, with the aim of supporting drug developers and regulators with compelling evidence of therapeutic benefit in specific patient groups within a previously unstratified trial population.

Dr Steve Gardner, CEO at PrecisionLife, said: “PrecisionLife is grateful for the support and collaboration of Professor Al-Chalabi and the MND Association in enabling us to access the MND Collections data, and is grateful to all participants, donors and their families and carers, without whom this invaluable research resource would not exist. We’re committed to finding better, more personalised ways of diagnosing, and treating patients and the new data access agreement will help accelerate our progress.”

More information on the study can be found here.

For more information, contact Patrick O'Brien (Senior Media Officer).

In this story

Ammar Al-Chalabi

Professor of Neurology and Complex Disease Genetics