Published 10 Nov 2020 | 4 min read

Our mission at Genomics is to use genetic data to drive transformational insights into human biology and disease. Our approach focuses on using existing information, generated through scientific research, clinical and population health programmes across the world, but combining data sources and data types both in new ways and at a scale that is unique.

To achieve this, we have assembled data on tens of thousands of studies linking genetic variation in populations from across the globe to traits ranging from chronic conditions such as cardiovascular disease and cancer to biomarkers, tissue-specific gene expression profiles, and even behavioural and cognitive traits. This is combined with other views on gene function, such as from CRISPR screens and clinical genetics, as well as a host of information on genome function at scales ranging from entire tissues to single cells. Each data point gives a peek into the complexity of biology; the tangled result of millions of years of evolution. Our goal is to put the pieces together.

We are, of course, not alone in believing that such data can transform our understanding of genetic risk, the nodal biological pathways that mediate the transition to disease and opportunities for intervention. But what makes us different, we believe, is our ability to synthesize this information. The data engineering and data harmonisation techniques we have built, coupled with innovative new statistical and computational methodologies, allow us to find the new angles, the extra power, the interpretability that makes the difference.

These insights are already making the difference in healthcare. For example, our precision health tools can pinpoint individuals at high risk of developing serious diseases potentially decades before the onset of symptoms and at a point where intervention is highly effective. Our tools combine genetic risk with other factors such as age, lifestyle and readily-accessible biomarkers to quantify future risk and to define the appropriate clinical pathway for an individual – for example to increase the frequency of cancer screening or take preventative treatments.

Of course, the work is never done and we strive constantly to improve the effectiveness of our methods and tools. For example, the data sources from which we draw are often biased towards particular countries and groups. We are committed to making these tools work for all members of society and seek opportunities to partner with organisations to reduce inequality in performance. Likewise, new technologies are driving our ability to measure human biology at a resolution and scale previously unimaginable. There is so much more to learn. But that’s where the excitement comes.

– Professor Gil McVean, Co-Founder and Chief Scientific Officer