We combine our unique burden of disease modelling with genetic database analysis, literature reviews and policy analysis to help life science companies working on non-communicable diseases (NCDs) and rare genetic diseases at each stage of the drug development lifecycle, from R&D through to market access.

Precision epidemiology HealthLumen

How can we help you?

Our epidemiological modelling covers a wide range of scenarios for NCDs and rare genetic diseases:

  • Determining current and future disease prevalence and burden
  • Quantifying the health and economic value of interventions designed to prevent or manage health conditions
  • Quantifying the impact of industry and public policy changes
  • Estimating the long-term population-level impact of a therapeutic using clinical trial data
  • Generating evidence for policy change
  • Generating data to support emerging technology investment decisions
  • Evaluating the market to determine the potential for therapeutic solutions, improving sales and revenue forecasting

Who uses our services?

Pharmaceutical and biotech companies, biotech investors, and public sector organisations involved in the following:

  • R&D: Epidemiological modelling helps in identifying and prioritising disease targets based on the burden of disease, unmet medical needs, and potential patient populations. Once a target disease is identified, burden of disease studies inform the drug discovery and development process, and provide Medical Affairs teams with the full landscape regarding disease prevalence, risk factors and progression.
  • Clinical trials and defining target populations: By examining disease prevalence, progression rates, and patient demographics, our models help identify the most relevant patient groups to include in trials, ensuring that the studies are both efficient and representative of those who will ultimately benefit from the therapy.
  • HEOR, market access and launch: Our models support HEOR teams and feed into HTA dossiers by providing estimates of the potential market size and penetration of new drugs. These forecasts are key for strategic planning and resource allocation for market launch.
  • Policy impact: Our epidemiological models project the potential impact of a drug on population health into the future, considering various scenarios of drug use and disease evolution. This is critical for understanding the public health significance of a new treatment and for planning post-marketing studies.
  • Post-marketing surveillance and RWE: After launch, our epidemiological models monitor the drug’s impact on population health, and effectiveness in the real world. This can inform future drug development and policy decisions.
  • Commercial – market expansion and supporting policy change: Our models are used to simulate the health and economic impact of proposed interventions – such as earlier screening – before real-world implementation, providing the hard evidence to support the case for changing regulatory guidelines.
  • Patient engagement and advocacy: Understanding the burden of a disease helps highlight the benefits of therapies in addressing specific unmet needs. This is valuable for patient education campaigns, helping to raise awareness about the significance of the disease and the potential benefits of new treatments.

 

What you can expect from us

We have spent over a decade developing our microsimulation software to help you make the best decisions at each stage of the product development lifecycle.

UNDERSTANDING YOUR QUESTIONS

We’ll help you define the population you need to look at, so you are confident you’re asking the right questions and are clear on what you need our answers to achieve.

ESTIMATING DISEASE PREVALENCE AND MODELLING DIFFERENT FUTURES

We’ll create a starter scenario – inputting our robust patient population prevalence estimates – and project different “what-if” scenarios into the future. You can then compare the outcomes of different kinds of interventions to quantify their potential effectiveness.

TURNING ANSWERS INTO ACTION

We’ll interpret the data for you, giving you plain language answers to your original questions. That will help you translate those answers into reliable, data-driven decisions.