Improving oncology KOL engagement

Combining technology with human insights is a powerful tool in identifying and engaging effectively with oncology experts.

The oncology market is growing in both size and complexity, driven by combination therapies and increasingly personalised treatments. By 2020, oncology is expected to account for around 30% of the pharmaceutical industry’s product pipeline and 25% of its revenue.

In such a rapidly advancing environment, with masses of new data being published every day, it is increasingly difficult for pharmaceutical companies to absorb the complex network of experts, activities, and information. Identifying the most knowledgeable scientific experts in a specific area, and engaging with them in the right way, is a major challenge.

Thought leaders in oncology often specialise in particular cancers, which requires companies to be more targeted, in terms of who they approach, and more granular in the types of information they share.

Engaging key opinion leaders (KOLs) is, of course, critical to the commercial success of a drug – and oncology KOLs are unusually influential. As well as informing other physicians of new diagnostics and treatments, KOLs help to translate clinical data for patients, payers, and policy makers, and they evaluate treatments in terms of both efficacy and value. They drive innovation, patient outcomes, and global health policy, and they can make or break a new drug in the market.

However, as oncology is one of the biggest speciality areas in life sciences, the ecosystem of oncology experts is equally large. Identifying a thought leader with a particular field of expertise requires complex mapping and analysis of customer data. Often that data is held across disparate sources, making it difficult to gain in-depth understanding of expertise, interests, relationships, and affiliations. Yet, this data can help to inform an approach to a KOL and maximise the value of any subsequent interaction. Mapping this information absorbs huge resources and countless hours. It also relies on accurate, up-to-date source data, which, in such a fast-moving field, is not always accessible.

In addition, traditional tools to engage with these experts are fragmented, providing limited visibility of engagement activity across an organisation. Different teams from the same pharmaceutical company may unknowingly reach out to the same KOL. With teams overlapping and failing to coordinate their activities, the experience for the KOL – arguably that company’s most important customer – is not a good one.

“Seventeen different people from the same company contacted me in the course of one month,” said one respondent surveyed in a UK study of the industry’s relationship with KOLs. The experience is cited by the study as number one of the top 10 poor KOL practices.

Streamlining KOL engagement, while effectively building and maintaining long and meaningful relationships, is a top priority for oncology pharma companies. As a result, many are looking at technology for a solution to this vital process. But moving from a small-project to an enterprise-wide approach to KOL identification and engagement represents a fundamental shift in mind-set. The case for replacing local market knowledge and strategy with data and algorithms is difficult to argue with a process that has long relied on human interaction and personal relationships.

Convincing customers to make this leap is a challenge for many technology players. However, technology has enabled the creation of a data platform that consolidates tens of thousands of oncology experts and millions of activities worldwide into a single, enterprise-wide source.

One of the early adopters of this technology, a top-10 pharmaceutical company, had previously experienced huge internal inefficiencies in its legacy systems and processes. It had more that 100 fragmented projects mapping KOLs. There was a lot of waste and operational inefficiency, with many different systems, hundreds of lists, taking thousands of hours, and draining millions of dollars – and no way of centralising the company’s approach to identifying and engaging with KOLs.

Now, with its new KOL identification, profiling and segmentation capabilities, the company has been able to identify and target customers and customer groups in seconds, as opposed to months. The system also provides global visibility of the company’s KOL activity, so it can see which team is focusing on which experts, and manage and coordinate across the organisation accordingly.

For example, it can engage in the right way with experts and avoid using them for small and potentially less relevant projects, when another team might really need their strategic guidance for bigger, more important projects. In short, the system drives a better customer experience.

But technology is only part of the picture. Calibration of data to ensure information is continuously updated and of the highest quality is one of the most important aspects of this kind of solution. And it relies on people. Advanced analytics and hundreds of curators update and identify data from thousands of different sources.

Organising this fragmented data, making it accessible, and linking it to particular experts requires a team of engineers and curators sifting through the data and feeding it back into the algorithm to continually reinforce the system.

The human factor will continue to play an important part in the KOL identification and engagement process. Algorithms can never fully replace local market knowledge or strategy. There will always be a place for real thinking and logic. With a tool that can target someone who is an expert in biomarkers, for example, a company will ask, “Why are we not engaging with this person?” There may, of course, be a reason not to engage with a particular KOL, and that’s where subjective, personal market knowledge is still valuable.

But identifying KOLs in the first place is 90% of the work. By removing the manual effort, teams can be freed to focus on the work that requires strategic thinking and human logic. Tailored data platforms make processes faster, more efficient, replicable, and compliant. And that is the true power of technology.

About the author:

Killian Weiss is Veeva Oncology Link General Manager at Veeva Systems, Europe.