Welcome - what we do

Crystallise takes an innovative approach to managing and modelling biomedical information.

We develop products and tools that help us make our consultancy services more efficient and effective, giving clients the support they need in a timely and affordable way.

Our expertise in medicine, modelling, coding, microbiology and psychology, combined with our experience of working across the pharmaceutical, finance and healthcare sectors, gives us a unique approach to finding ingenious solutions to problems and delivering high-quality new products and services.

Literature Reviews

Transforming literature reviews

We are transforming the way we conduct our literature reviews: Powered by heoro.com

  • Our database of pre-indexed studies on the humanistic and economic burden of disease saves days of screening time.
  • We can search more broadly for studies without incurring greater costs and delays.

Delivered with evidence maps

  • The interactive spreadsheet shows all studies identified by abstract screening, indexed by topic.
  • Targeted reviews become methodologically transparent.
  • Systematic reviews can be scoped quickly and cheaply.

Modelling

A multidisciplinary approach to modelling

Our multidisciplinary knowledge and skill gives us an innovative approach to modelling:

  • Synthetic sample generation
    • We can replicate populations typical of the UK population or clinical study participants.
    • The sample can be used to model the impact of interventions on mortality and other outcomes.
  • Mortality modelling
    • We can identify mortality trends over time for specific diseases and predict individual life expectancy.
    • We track weekly mortality statistics for England to help finance, pharmaceutical and healthcare clients predict trends and financial liabilities.
  • Infectious disease modelling
    • Our flexible approach supports the modelling of new and established pathogens and the impact of interventions and behavioural modifications.
  • Economic modelling
    • We collaborate with experts to conduct network meta-analyses and economic models for HTA submissions.

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