Case Study: Geotargeting & Site Positioning
Are you aware of the actual competition in your specific research area? Do you really know, how many protocols in demand of the same population are open for recruitment?
Whatever the answer is: you can be sure, that the best sites are also known to your competitor.
This does not represent a problem as long as you work in an area with large patient potentials – but the tighter the market is , the more it makes sense to differentiate research-dense areas from those with unrevealed patient potentials.
In addition, strategies to aggregate patients around sites or place sited in the center of patient aggregations will contribute to success.
DBPi conducted an analysis for a large pharmaceutical company to answer the question, why recruitment for 2 studies in an oncologic indication with an incidence of appr. 15.000 p.a. were recruiting so slow, though Feasibility Data showed adequate patient access and the sites selected were well known for indication expertise and research ability. While other countries delivered to target, German sites were falling behind significantly.
Compiling the data of public available sources related a picture, that was explaining the lack of recruitment: each of the selected sites had between 5 and 10 studies for the same or at least parts of the same population open for recruitment.
On the other hands we were able to identify 11 sites with high patient potential and low study density. Following thorough onsite evaluation, 7 sites were qualified for participation and finally delivered 60% of the recruitment.
The approach chosen was first to understand in detail, how patients were referred to specialist clinics, which clinics participated in this respective treatment setting – the patient journey with focus on first line treatment.
In a second step we highlighted, how much research was conducted in parallel at these sites in relation to the annual case numbers.
Resulting is a matrix, showing highly active research sites with high patient potential, balanced sites and sites with high research and medium to low patient numbers – and sites without or very low number of current studies and adequate case numbers.
This was matched with the sponsors own Investigator database and a hit list was created to investigate site potential and research capability.
This approach showed to be successful in the respective situation. Other studies may benefit from similar concepts.
In other cases, patient engagement was started early to understand hurdles to participation and expectations in a planned study. Depending on where site identification stands at that point, one may want to enrich patient potential around given locations or select sites in the center of areas with high patient engagement level. Even a hybrid approach may help to connect study delivery to precursor activities, the existing relations with patients and he budgets invested to create those.