“Key opinion leader” (KOL) is a term most often used to refer to a medical partner, expert, or external advisor whose voice is highly respected within their specific therapeutic field. KOLs have become vital to the drug development process, and many pharmaceutical companies are seeking deeper collaborations with KOLs.

Findings from a 2015 online survey presented at the Medical Affairs Leaders Forum in Berlin, Germany, revealed that the majority of the senior medical community believe the term KOL is often inappropriately used for people who do not necessarily warrant the title. The term “key scientific leader” (KSL) may be an alternative to KOL.
The trend to engage KSLs during earlier stages—prior to clinical trials and commercialization—creates the need to identify KSLs with broad and current experiences in initial drug development, trial design, and more.

Because effective methods of identifying and engaging key scientific leaders are continually evolving, a provider of medical insights can offer life sciences companies many strategies to help guide them in a thoughtful partnership with KSLs. Traditional methods include searching literature databases and compiling surveys; however, these are limited and run the risk of “responder bias,” which is discussed later. In this blog, we’ll further explore new and different approaches to identifying KSLs through social network analysis (SNA).

What Is Social Network Analysis?
In SNA, interactions between thought leaders and experts in a given therapeutic field are tracked as relationships or connections that create a social network construct. Relationships are based on shared information and collaboration across different research communities and are assigned value, otherwise called social capital. The results of an SNA specifically examine the social structure of these networks and evaluate the position of the members within it.

A network, for example, could involve thousands of researchers and medical experts from around the world. In this case, SNA is used to capture the collaboration of participants in the network; these participants come from pharmaceutical companies, educational institutions, advisory boards, and regulatory bodies. Analysis of these collaborations can provide context and insight about how important one acting body is within the network hierarchy. Furthermore, a structural analysis of a network can project the cohesiveness of a group or collaboration.

How Is Social Network Analysis Used to Identify Key Scientific Leaders?
Techniques used to analyze and evaluate key players in a network generally measure communications and productivity. Data are collected from various sources and used to map the professional qualities of a thought leader. What are these data, exactly? Nodes, representing social network users or user groups, and ties, representing the relationships among users, are converted into quantifiable data. Nodes and ties attribute certain properties, eg, age or qualification of a person, or the strength of a relationship based on frequency of interaction. Based on the defined properties, the nodes or ties can be selectively extracted and a new network created.

Since the goals of the analysis can be tailored to the distinct requirements of a company, specific measures are then applied to the new network. Applications of SNA include the use of centrality measures, for example, that can identify the profiles of coauthors and author collaborations. In this case, the nodes are the authors and the collaborations are the ties. Thus, a social network based on “author collaboration” is born.

Each company has a different reason to identify thought leaders. For example, some pharmaceutical companies seek key scientific leaders with clinical experience in certain disease areas or research experience. Identifying the appropriate thought leader for an effective partnership should consider the company’s objectives; a KSL may be selected based on their experience and reputation, which considers factors like the number of publications, media presence, or seminar leadership. All of these can be determined by the properties used to define a network, as well as the measures applied to the network itself.

What Are the Benefits of Social Network Analysis?
As mentioned, SNA can be tailored to the needs of a company or product, specifically by defining the properties of a social network and the types of measures applied to it. Another key benefit of SNA is its scalability, meaning the approach to analyzing the network relationships can be applied to an entire community, or to a sample group of members. This can benefit a company if it is looking for a KSL whose expertise is specific to a focused area of research.

Furthermore, the general methodology behind SNA eliminates the responder bias—that which influences a participant’s response away from a truthful or accurate response—that is frequently associated with observation and survey methods used in traditional approaches to identifying KSLs. Social network analysis can demonstrate a KSL’s influence using facts derived from measurable data instead of personal opinions or referrals. While a thought leader’s publication history and their reputation as a key speaker on medical issues are still highly regarded, there are also forward-thinking individuals who fly under the radar. This is especially true for younger researchers, physicians focused on rare or recently discovered diseases, or those working on innovative treatment modalities, who may frequently offer a substantially better position in forming strategic KSL partnerships.

The value of social network analysis to identify key scientific leaders is demonstrated in its quick adoption by the medical sectors beyond pharma. Smaller companies, medical device manufacturers, and numerous other industries are using SNA methodology to provide insight into identifying the leading experts in a certain field. In turn, proper KSL identification can effectively influence an efficient path to market access. Beyond this goal, finding the right scientific leaders can help companies strategically develop their product and brand, or direct innovative research activities.