Loukas Zagkos

Loukas Zagkos
Consultant Bioinformatician, LCP Health Analytics


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I am a consultant bioinformatician in Health Analytics at LCP. I also serve as an associate editor at Age & Ageing and have an ongoing academic affiliation at Imperial College London and Brunel University London. My background is in applied mathematics and statistics and pursued a PhD in mathematical biology. I worked as a research fellow in genetic epidemiology at Brunel University London, before moving to Imperial College London to work as a research associate in molecular epidemiology.

At LCP, I am a member of the Integrated Omics team, where my role is to utilise large-scale human genetic data to explore causal relationships between modifiable risk factors and clinical health outcomes. Among my roles, I am responsible for generating, automating and running pipelines to inform drug development decisions. 

Our health analytics approach leverages the increasing availability of data and our cutting-edge modelling approaches to put timely actionable data in the hands of key stakeholders.

We integrate a wealth of health and health-related datasets and develop bespoke interactive visualisations to make it accessible and rapid for clients to glean insights across a range of areas.

Supporting our clients to achieve equitable health outcomes is a golden thread throughout our work. We combine our expertise to translate evidence into change and apply population health analytics to help reduce inequalities in health and health outcomes.

We help our clients identify technological and data led solutions to solve the issues they face. From risk modelling for pension clients to providing insight to the energy market, we use the latest cutting-edge technology to help clients make better and more informed business decisions.

Multimorbidity, living with two or more conditions is one of the biggest challenges facing patients and health systems today. We leverage real world datasets and innovative approaches to generate evidence that identifies patient groups with the greatest unmet needs in a more holistic manner that reflects the drivers of ill health.