Population and Quantitative Science

Top areas of focus

  • Creation of large-scale recallable BioResource’s. We will expand major recallable nationally-accessible BioResources, enhancing NIHR infrastructure that enables recall-by-genotype studies
  • Using “living laboratories” for translational research. We will develop the concept of “living laboratories” for biomedical research by involving participants in translation studies that demand high levels of commitment from participants.
  • E-health and clinical informatics. We will substantially expand research infrastructure by systematic collection, organisation and use of routine hospital e-records and residual clinical samples.
  • Therapeutic target prioritisation. We will identify and validate therapeutic targets using human genomics.
  • Precision medicine tools. We will accelerate research translation by facilitating interplay between development and application of quantitative tools for precision medicine studies, focusing on scalable tools relevant to different disease domains.

Introduction to Theme

‘Population and Quantitative Sciences’ will develop and exploit pivotal infrastructure to address two overarching questions:

  • How can therapeutic target discovery and validation be substantially improved?
  • How can disease understanding and management be substantially improved by harnessing high-dimensional (eg, molecular, imaging, e-record) data?

The rationale is to seize, through innovative quantitative approaches, major new opportunities afforded by the ability to measure and analyse, at scale, vast amounts of data on tissues, patients, and populations in relation to genetic make-up, traits, and important diseases.

Our objectives are:


  • Develop and evaluate acceptable and efficient tools for participant recruitment to enable transformative enlargement of the NIHR BioResource
  • Develop and apply tools that enable robust analysis of genomic and multi-omic data in NIHR BioResource cohorts
  • Develop informatics tools that support target validation and medicines re-purposing
  • Attract world-class mathematicians/computer scientists to translational medicine, and provide greater quantitative training for clinical and biomedical scientists


  • Develop, evaluate, and implement methods to introduce new concepts of “living laboratory” translational research platforms
  • Build scalable systems for automated clinical data extraction and cleaning to support national; initiatives (eg, Genomics England), and build a major national e- haemovigilance platform with NHS Blood and Transplant
  • Build and use an extensive toolkit of genetic “instruments” to prioritise thousands of potential therapeutic targets, together with Open Targets
  • Develop a range of biostatistical tools that enable precision medicine studies


  • help build a national “living laboratory” of >1 million patients and volunteers in the NIHR BioResource

Further information

Disease-focused themes in this BRC application have already described the importance of specific conditions to be tackled in collaboration with the Population and Quantitative Sciences theme. In this section, therefore, we highlight the relevance to patients of cross-cutting efforts in this theme that address: a) failures in medicines development and b) challenges and opportunities of using high-dimensional data to improve healthcare.

Attrition is a major challenge in drug discovery and development, with more than half of clinical studies failing because of a compound’s lack of efficacy (rather than toxicity). In cardiovascular disease alone, compounds that have failed in recent years in phase 3 trials due to lack of efficacy include: varespladib, dalcetrapib, niacin, darapladib, and evacetrapib. These failures represent many billion pounds of unrealised effort and investment and patient contribution that, in retrospect, could have been directed towards evaluation of potentially more fruitful targets. The widespread failure of preclinical model systems to adequately predict efficacy in humans has led drug developers to seek other evidence to inform decisions about which targets to pursue and for which indications. To help reduce the unsustainably high rate of failures of compounds, we will develop and accelerate efforts that can help: a) identify novel causal pathways that underpin discovery of new drug targets b) judge the causal relevance to disease of suspected targets before initiation of costly clinical trials and c) select trial participants potentially preferentially susceptible to an agent’s mechanism of action. These strategies will maximise the chances of patient and public benefit of research involvement.