Commercial Planning

The focus of healthcare development has recently shifted towards providing healthcare solutions for niche patient populations with complex co-morbid conditions, clinical attributes and risk factors. This is in response to the raised expectations and requirements by regulators and a reflection of the limited opportunities available to companies to gain a broad indication for their product.

This raises a challenge for the industry to better define their patient segment when historically only an overall prevalence rate was required.

The Epiomic patient segmentation database could deliver a solid foundation to support a robust valuation, product forecast or the identification of a segment with high potential. Utilising a more specific patient population will reduce the level of variability and subsequence risk if it’s aligned with the expected product label.


Atrial Fibrillation Example

Imagine you are working for a company about to launch Amiodarone in Germany for treatment of patients with atrial fibrillation.  To determine the relevant patient population, it is common practice to take the total atrial fibrillation population and assume a percentage of that population that would take up the treatment. This would be based on market research or internal knowledge.

The patient segment required may not be accurately reflected in this assumed population.It will need to be taken from patients with underlying heart disease, and those with no or minimal heart disease with persistent Atrial Fibrillation as indicated in the patient algorithm.


ESC Patient Management Algorithm for Atrial Fibrillation Europace 2010; 12: 1360-1420


However, by quantifying the patients across the management algorithm, a far more robust and defendable target patient population can be determined and therefore a more robustly defended and realistically achievable forecast can be generated.

Wouldn’t it be fantastic to know from the outset how many patients there are that fit the product label indication?

The Epiomic database gives you the ability to do this.  In a user friendly web-based format, Epiomic will allow you to explore the different sub-populations within the disease and quickly create a patient segmentation that is sourced from the latest available data including patient registries and clinical trials.  

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