Portfolio Approach to Optimize Site Selection

Site selection is one of the most important and at the same time challenging problems in clinical trials planning. Poor site selection may cause enrollment delays, resource waste on low or zero enrollment, and even potentially compromise trial results.

Site selection is a complex process, which includes sites identification, sites assessment, sites validation. and selection of a set of sites aligned with study goals and limited resources.

Many factors affect the site selection process. Some of them are generic, others are trial specific (Figure 1). Some factors are qualitative and subjective, such as “Experience and qualifications of Principal Investigator” or “Staff turnover.” The value of each factor can be evaluated qualitatively (e.g., excellent – 10, the worst – 1). Or it can be quantitative, such as “Planned patients’ enrollment” or “Projected enrollment rate.” The factors could be extracted from historical databases, questionnaires, etc. Some companies use data mining techniques for site identification. Examples of clinical trial-related factors are “Trial budget,” “Enrollment target,” etc. A variety of business rules are also related to the entire trial, e.g., “If a country is selected, then minimum two sites per country should be selected,” or “Priority site”-forced site prioritization.  

Traditionally, site selection efforts are focused on a selection of “best” clinical sites based on:

Site rankings according to a criteria has limitations. For example, site selection based on sorting of predicted enrollment rates does not take into account parameters like cost per patient, site capacity, or “soft” attributes such as experience of PI, facility quality, etc. The value of site selection based on extrapolation of historical performance may be limited due to high site turnover [Getz, 2018] or a limited or lack of historical data for new sites. Site selection based on sorting of ranking index also does not take into account budgeting and other constraints, as well as study goals and business rules.

Often, the site selection process mistakenly identifies with only site identification and feasibility assessment. After identifying the “best” sites and evaluating them, it is assumed that the best sites will be selected somehow from a feasible set of “best” sites.  

Often, a feasible set of sites is identified based on an informal process which may include, but not be limited to:

More advanced techniques (AI, data mining) could be applied for large sites’ databases but not transferrable to all sites.

Usually, all feasible sites are divided into three major tiers. Their advantages and disadvantages are presented in Table 1.

Sites could “migrate” from tier to tier depending on most recent performance assessments.

A high-level overview of the traditional site selection process is presented in Figure 2 and described below.