We are now extending our relationships with some of the largest COVID-19 collaborative research projects and are offering free use of our unique analytics platform and support from its data and biomedical science teams to the on-going collaborative efforts of the medical research community in the fight against COVID-19 coronavirus.

Our precisionlife platform can analyse large scale, complex multi-omic and epidemiological data to generate disease insights that are not possible with current tools. It is routinely used to analyse very large anonymised patient datasets (>100,000 patients) and with detailed insights into complex diseases returned within hours.

The platform can be used to help:

– Identify the complex genetic factors associated with patients’ different disease severity and outcomes
– Understanding risk factors such as smoking, gender, ethnicity, blood group and underlying health conditions
– Developing tests to identify whether people are at high- / low-risk for serious forms of the disease
– Informing the hunt for existing drugs that will be effective for given patient sub-groups, especially those at risk of late-stage disease
– Identification of novel drugs targets especially for more serious late-stage disease

To be effective, the tools require data from a minimum of several hundred COVID-19 patients, ideally including genotype/whole genome sequence with additional data including disease severity, co-morbidities, and epidemiological/phenotype information such as blood group, smoking, gender, ethnicity etc. The methods work hypothesis-free and do not require training.

The platform has been validated on over 20 complex disease studies and with disease specialists, development partners and in pre-clinical assays/models. Several of these studies have focused on respiratory and immune response/auto-immune diseases.

Initial study and its findings: https://www.medrxiv.org/content/10.1101/2020.06.17.20134015v2.full.pdf

If teams are interested in the data contained in PrecisionLife, please contact dta.yusheng@gmail.com. The data access will be provided through Email.