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Partex and Singapore’s Experimental Drug Development Centre collaborate to bring forward an innovative approach for early drug discovery and development

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Frankfurt, Germany, 3rd June 2024, 9am CET Partex, a leading provider of AI-driven solutions in the pharmaceutical industry, is thrilled...
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Apr 24

Partex Partners with Lupin to Revolutionize Drug Discovery through AI-Driven Asset Search and Evaluation

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Frankfurt, Germany, 23 April 2024 – Partex, a leading provider of AI-driven solutions in the pharmaceutical industry, is thrilled to...
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Does Your Scientific Narrative Resonate in the Pharmaceutical Ecosystem?

Life Science / By

Monitoring the impact of your scientific narrative in real time

The term “scientific narrative” refers to the comprehensive communication strategy to position a therapy and sets forth the quintessence of the mission and vision of a particular therapy. It encompasses all attributes of the therapy from scientific data and health economic arguments to clinical practice and advocacy relevance. To be effective, it needs to be informed by the most recent and relevant data available. Working within the confines of strict marketing regulations, pharma companies rely on the art of storytelling to present scientific information on a specific therapeutic area in order to increase comprehension and engagement.

Pharmaceutical communication is a foundational component of stakeholder engagement and management. In Europe, pharmaceutical communication traditionally focuses solely on interaction with prescribers, while in the US pharma communication also includes direct-to-consumer advertising. Strategic engagement of stakeholders requires tailored communication for different drug development phases, such as clinical trial management, key opinion leader engagement, and commercialization. In recent years, pharma has increasingly participated in conversations on medical forums and similar sites, thereby adding value to their brands. In general, scientific information is only understood by scientists or physicians. But to drive engagement, pharma communication focuses on reaching healthcare and medicine reporters and influencers, the scientific community, patient advocates, and patients.

The digital revolution that transformed the internet into a mass medium has influenced the channels of scientific communication and patient involvement. To maintain relevance in communications, pharma needs to understand and respond to the ongoing exponential growth in digital media. For example, patient advocate blogs might be of equal or similar relevance to medical policymaking and pricing as the comments of a clinical opinion leader at a congress. The challenge is how to drive more positive opinion, engagement, and sentiment for their brand overall. To develop and maintain a sustainable competitive advantage it is important to understand the environment, evolve a brand’s or product’s unique value proposition, ensure globally aligned scientific narrative, and identify new opportunities to advance the strategic vision.

However, unlike other industries, pharma tends to have fewer blockbuster products, and communication efforts have a relatively smaller reward in media where using a brand name is not an option. The digital scientific world and the digital “Twitter world” have set a new bar for the speed of communication dissemination. Staying in sync with the latest trends in the market is, therefore, a necessity. Artificial intelligence technologies can help pharma gain real-time insights into the trends, news, sentiments, guidelines, and other aspects of the changing pharma landscape that inform the design of unique and competitive messaging.

A real-time approach to the scientific narrative

By refining the narrative on a regular basis and keeping the elements updated, a pharma company retains control of their profile within the dynamically changing therapeutic space. This needs to begin at phase II of the drug development process, when the target product profile (TPP) is being developed and fine-tuned. New insights need to be generated—often by revisiting previously asked questions—so that they can be turned into action. This is where AI-empowered data analytics can help generate relevant insights for the important strategic decisions. Questions that can be addressed include:

  • KOL analytics: Who are the established and emerging thought leaders? Who are in their networks?
  • Sentiment watch: What are the patients saying? What is the scientific share of voice? What is the social share of voice?
  • Guideline watch: Is there evidence being reflected in the regulations or guidelines?

Disseminating narratives through key opinion leaders

Key opinion leaders (KOLs) create value through various dissemination channels to help companies reach and actively engage larger audiences. They guide the company’s commercial strategy to resonate with the right people and ensure that their public messaging is powerful enough to garner the attention of news and other media, and to connect with more thought leaders and digital influencers. Through dissemination of economic data, clinical outcomes, presentations, abstracts, attendance at social meetings, participation in medical forums and conferences, and by other means, KOLs help to keep others connected and up to date on a specific therapy.

To ensure the success of scientific narratives, it is important to expand the network of KOLs and use them wisely to distribute the information where it will have the greatest impact. For this, key questions need to be answered in innovative ways, and new insights need to be generated in real time and turned into action. Some of the questions for which information needs to be gathered and the resulting actions are:

    • Question: Who of the therapeutic area experts (TAEs) support which mechanism of action (MoA), clinical concept, and drug? Action: Developing a list of TAEs to engage or reengage with.
    • Question: Are you investing in the right people early enough to engage with them? Action: Developing a list of “top speakers on hot topics” (i.e., topic experts).
    • Question: Are you investing in the right scientific channels (e.g., publications and congresses), and do you have a competitive communication mix and share of voice? Action: Understanding the strengths and shortcomings of your own communication as compared with competitors’ around key events. Identifying the level of discussion for the chosen drugs in top congresses and the congresses of a pharma company’s interest. This will be a great help in determining whether you are investing your money in the right congresses and will also help in identifying the congresses you should pursue.
    • Question: How is your scientific narrative disseminated, by whom, and through which communication channels? Action: Establishing new communication partners for new communication channels, top bloggers, and blog forums.
    • Question: Who are the medical and nonmedical digital opinion leaders influencing the perceptions of therapeutic offerings? Action: Understanding the impact of your narrative in scientific media and exploring whether there is a need and opportunity to respond. Finding out who tells what story about specific therapies and therapeutics, and how to connect with people and topics of interest.
  • Question: Are there networks of emerging KOLs for the therapeutic area? Action: Checking publications/congresses/societies to engage with KOLs for a new therapeutic/drug/treatment concept.

New insights can be generated only when new connections can be made. Artificial intelligence technologies such as machine learning or network analysis can automate these processes. New levels of engaging TAEs and KOLs can be enabled based on integrated and continuously updated data that taps into the wealth of information generated from millions of documents from various asset classes such as publications, congresses, clinical trials, societies, HTAs, advocacy groups, and others.

Intelligent analytics can help identify top and emerging KOLs with expertise in areas ranging from research and discovery to policy making, access, and reimbursement. Visualizing their network helps to determine how to best engage with the right person to disseminate scientific narrative about a therapy in the most efficient way. This helps to build positive brand awareness, enhance public messaging, and stay focused on the success of treatments.

KOLs drive innovation in the industry, but their monopoly in shaping scientific and public opinion is often sidestepped by new communication channels that provide information faster than ever, such as formularies, limited lists, and guidelines. Although we are in an era of so-called evidence-based medicine, it is more important than ever to stay informed about patients’ and practitioners’ opinions and interpretations.

Leveraging sentiment analysis for efficient scientific narratives

Within today’s communication mix there is a need to stay on top of social media conversations and trending topics to ensure that the scientific narrative will have the most influence. Measurement is certainly becoming a top priority. Most companies evaluate the success of their scientific narrative by tracking the basic metrics: shares, likes, time on page, unique visits, page views, and so forth. But tracking can be expanded to include more behavioral metrics.

Ultimately, part of the strategy should be to measure across various audiences whether or not their opinions about the company are more positive than they were before engaging with the content. Using AI can support leveraging data from social media not only to measure performance but also to improve the outcomes on an ongoing basis. Optimizing social messages to drive positive opinion, engagement, and sentiment towards the brand can be achieved with sentiment analysis.

Usually a scientific narrative strategy for participating in and adding value to scientific conversations across various social channels, such as Twitter, blogs, medical forums, and the like, is based on a few questions. These include what is being discussed on social media about similar drugs, what topics are trending, what are competitors saying about their drugs, and what kind of sentiments are driven among patients, physicians, and KOLs about the company and the drugs they have launched. Finding answers to these questions may take weeks via manual research but can be achieved quickly by implementing automated AI-based solutions. Information that can be obtained includes:

  • Insights into scientific sentiments for drugs around predefined MoAs, which allow pharma companies to identify a drug that has a significant amount of commentary around a given MoA in scientific forums
  • Insights into sentiments about competitors’ drugs using effective graphical visualization of the competitors and their drugs, obtained with the help of AI
  • Algorithm-based identification of the top bloggers for a given indication—the digital influencers that pharma companies should follow on social forums/blogs

Sentiment analysis can be leveraged to improve products, discover unmet needs, identify market opportunities, and generate positive feedback about the brand. For this, social media conversations and all the trending topics need to be monitored in real time to ensure the story will be relevant. It is also important to ensure that the focus is on critical milestones when it comes to developing and promoting a narrative. For example, events such as medical meetings and regulatory announcements typically draw a lot of external attention. Moreover, knowing how social sentiment changes following engagement with new content can improve the optimization process and future narrative strategies.

Aligning pharma messaging with guidelines at various geographies

Guideline comparison allows pharma companies to be the first to know about changes and whether and how the scientific communication needs to be adjusted. Intuitive and real-time guideline monitoring can be achieved with continuously updated data ensuring the latest and most relevant results. Trend analysis for guidelines around indications/drugs of interest helps identify opportunities to strategize the scientific narrative. AI-based tools can be leveraged for the latest information on recent guidelines changes, news, and events specific to a given indication.

Our proprietary life sciences ontology coupled with our AI technologies have created the capability of monitoring over 95% of publicly available digital media. The combination enables a real-time picture of the promoted therapy in comparison to competing alternatives. Results are presented in visualizations that show summarized perceptions and trends, enabling the users to generate actionable insights from the “digital echo” of a therapy.

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