2025 Fall Symposium - Agenda

In today’s biotech and pharma landscape, speed isn’t just a competitive advantage—it’s a necessity. Delays in recognizing a formulary shift, responding to a competitor’s move, or spotting signals that a launch is veering off course can lead to irreversible losses in market share. Yet most commercial teams still operate within rigid, fragmented analytics systems that are too slow to respond in real time.

Join Regeneron’s Executive Director of Commercial Strategy, Insights & Analytics learn how they’re leveraging GenAI across brand lifecycle stages to:

• Adapt faster—from early asset prioritization to LOE defense—by surfacing competitive threats, readiness gaps, and growth opportunities with integrated, AI-powered insights.
• Accelerate brand growth and readiness at every lifecycle stage
• Drive cross-functional collaboration with unified data exploration
• Empower commercial teams with self-service, no-code analytics
• Improve strategic agility in response to market and competitor shifts

This session is intended for senior leaders in Commercial Strategy, Insights & Analytics, Sales Operations, Field Excellence, Brand Management, and Digital/AI Transformation within life sciences organizations.

More information coming soon!

Generative Artificial Intelligence (GenAI) is being adopted rapidly throughout healthcare and healthcare research. In this session, we present a case study that uses GenAI to highlight key findings in breast cancer pathology reports and examine future opportunities for leveraging GenAI to support ongoing innovation in the life sciences/biotech domain. We'll pressure test assumptions, limitations, and the seemingly unlimited possibilities of these methods in transforming the way we work. Live polling will give audience members an active voice in engaging with the discussion.

In an era marked by rapid advancements in technology and shifting market dynamics, the pharmaceutical industry faces the critical challenge of accurately forecasting long-term trends in drug development, market demand, and patient needs. Agentic AI, characterized by its ability to act autonomously, reason and make decisions based on data analysis, offers significant value in long-range forecasting across various industries, including pharmaceuticals. This presentation explores the transformative value of agents in long-range forecasting within the pharmaceutical sector, highlighting their applications, benefits, and implications for future growth We will delve into the areas of current exploration into capabilities of Agentic AI to enable Strategic forecasting.

In today’s fast-paced pharmaceutical environment, unlocking actionable insights from complex data at scale is critical for accelerated decision-making. This session presents a proof-of-concept analytics chatbot developed using Snowflake Cortex Analyst and Streamlit, powered by large language models (LLMs) to enable natural language querying and dynamic visualization within a secure, scalable cloud infrastructure. Designed initially for the analytics team, this solution bridges the gap between technical data access and everyday business questions, delivering rapid, intuitive insights, and it also demonstrates the potential to scale up and extend across the commercial organization.

Attendees will gain a comprehensive understanding of how to leverage large language models (LLMs) and modern data platforms to deliver fast, intuitive, and secure access to commercial insights. Through this session, attendees will:

1. Understand how to design a natural language analytics chatbot using Snowflake Cortex Analyst and Streamlit
2. Learn from real-world implementation challenges, lessons, and technical decisions made during the PoC
3. Gain insights into strategic path forward including building GenAI-ready data foundation and scaling up the analytics chatbot for broader impact

For years, longitudinal ATU (Awareness, Trial, Usage) studies have been a cornerstone of performance tracking in pharma. Yet, despite their strategic value and voluminous data around market trends at brand teams’ disposal, these outcomes are sparsely aggregated to learn from and predict outcomes for the future. Periodic learnings remain locked in static, wave-by-wave deliverables—often buried in slide decks, spreadsheets, and disconnected repositories. Today, with AI challenging conventional channels of insights generation and consumption, there lies immense opportunity to reimagine legacy practices of insights generation, purpose-built towards and integrated view across sources and stakeholders

Traditional forecasting models fall short in rare, one-time gene therapy markets where historical data and recurring treatments are absent. In this session, we present a novel, patient-centric model developed for a gene therapy. By integrating custom-built survival curves and dynamic “time-to-treat” and “enrollment” curves, the model accurately estimates the addressable population by age and tracks the full patient journey from diagnosis to treatment. This real-time, adaptable approach enabled high forecast accuracy, informed age and patient-type specific strategies, and optimized resource allocation. Attendees will learn how this methodology was applied in a rare disease market to uncover true opportunity and drive proactive commercial strategy.

More information coming soon!

This Spotlight Session is designed to spark thinking about the practical impact of AI on our very human lives. AND the session is guaranteed to generate laughter, levity, and discussion. The session is compact, featuring an engaging video, followed by practical AI “pro-tips,” intended to remind us to inject “human intelligence into artificial intelligence,” to quote a brilliant PhD.

What could possibly go wrong?

Traditional HCP targeting approaches are often inadequate for effective customer engagement. These methods over-rely on historical prescribing data, lack content personalization, do not adapt to changes in the market environment and have implementation challenges that prevent rich insights from becoming actionable.

Our HCP segmentation approach integrates the traditional approach of based market potential with attitudinal growth-based segments (HCP needs and preferences) to drive effective 'where to play' and 'how to win' strategies. This dual-dimension approach has allowed us to develop segment-specific roadmaps for behavior change by addressing segment-level drivers and barriers and leveraging unique motivational insights of each segment.

The nuanced understanding of each HCP segment enabled field teams and digital media teams to deliver personalized engagement strategies tailored to each physician's specific needs rather than relying solely on prescription volume or market potential. The result was a more strategic resource allocation, more relevant messaging, and ultimately more effective customer engagement that positioned our product for optimal growth following the new indication launch.

When market conditions shift with things that are out of your control – like sudden changes in patient access, provider behavior, or regional demand – sales forecasts can quickly become unreliable, leading to inventory issues and missed opportunities. This session will show how to tackle these challenges by combining traditional forecasting methods with machine learning and real-world market signals like outreach efforts and community trends. The result? More accurate forecasts, smarter planning, and better regional performance. Join us to learn how to turn unpredictable markets into actionable insights.

As AI models grow in complexity, the need to explain their outputs in clear, contextual, and actionable ways has never been more urgent—especially in regulated domains like life sciences. Generative AI (GenAI) is emerging as a transformative force in bridging the gap between sophisticated model behavior and stakeholder understanding.In this presentation, we explore how GenAI, when paired with Agentic AI, is reshaping the landscape of AI explainability and commercial activation. First, we demonstrate how attention weights from transformer-based models (e.g., BERT) can be translated into intuitive narratives, helping commercial teams understand the evolving signals behind HCP behavior and model-driven recommendations. For example, it will be quite insightful to know about the most effective content to be shared with a specific HCP post a patient switch.Next, we show how GenAI can complement traditional driver analysis (e.g., XGBoost) by generating actionable insights and business-ready summaries that elevate the relevance and timeliness of recommendations. For example. it will be be quite helpful to understand "which cohort of HCPs engagement is declining and why? Is it because of stale content or overuse of a particular content? And, what should be the corrective action."Going a step further, we introduce the role of Agentic AI—intelligent agents that not only interpret model outputs but also continuously monitor recommendations, adapt based on downstream feedback, and autonomously generate (GenAI powered) tailored, timely suggestions for field teams. This agent-powered loop brings explainability closer to execution, paving the way for a new generation of GenAI-powered recommendation systems that are self-evolving, context-aware, and deeply aligned with business goals.Together, these innovations are enabling a more human-centered, trustworthy, and dynamic application of AI—turning black box models into transparent, high-impact decision support tools for pharma.

Large-language-model copilots are only as good as the proprietary content they ingest. In pharma, that content is overwhelmingly unstructured—slide decks, study reports, CRM notes, emails, call recordings, SharePoint folders. Left unmanaged it is duplicative, outdated, and context-poor, causing hallucinations and missed insights. Simply “plugging in” Copilot or any off-the-shelf LLM won’t create value; a Retrieval-Augmented Generation (RAG) pipeline fed by high-quality data will.

This talk lays out a pragmatic, six-step playbook for making unstructured data GenAI-ready:

1. Frame the business question first – attack data quality problem-by-problem; don’t boil the ocean.
2. Inventory & score candidate content – apply a “less-is-more” mindset; include only sources you trust.
3. Stand-up a cross-functional data guild – domain owners, data stewards, annotators, and GenAI engineers share accountability.
4. Human-AI curation loop – experts define taxonomies and “golden terms”; GenAI assists with summarization, deduplication, tagging, and draft knowledge-graph creation; humans arbitrate entity resolution and final scoring.
5. Build & stress-test the RAG layer – validate with “50 golden questions,” audit outputs regularly as foundation models update.
6. Institutionalize continuous quality – embed feedback hooks, root-cause analysis, and creator education so each new document arrives production-ready.
7. Early adopters report 50-70 % faster insight retrieval and double-digit drops in hallucination rates once curated corpora replace raw file shares. The investment—largely process and metadata discipline—pays back quickly through higher-confidence decision support in competitive intelligence, PMR analysis, and patient-journey planning.

Take-away: Treat unstructured data as a product. Pair relentless human stewardship with GenAI accelerators, and your RAG applications will move from demo-ware to durable economic value.

This year’s panel will take an interactive “choose your own adventure” approach. Panelists will take turns giving a brief, 3-minute introduction to the proposed topics, and then the audience will vote on which questions the panel will dive into.

Poor drug adherence is associated with adverse health outcomes- hospitalizations, disease progression, lower quality of life, higher healthcare costs and lost brand revenues. Rates of patient nonadherence to therapies range from 30% to as high as 60% for chronic diseases. Patients usually drop out of prescribed treatment plans due to a variety of reasons. This workshop explores using AI/ML based models to proactively identify patients at higher risk of non-adherence and likely reasons for non-adherence- who can then be targeted through enhanced, and tailored, intervention programs which eventually allow healthcare organizations to effectively allocate resources by prioritizing patients who would benefit the most from a medication adherence intervention.

We will cover:

• Defining Patient Adherence & key challenges with adherence
• Scoring patients based on non-adherence risk using AI/ML models
• Identifying key drivers of non-adherence across disease areas
• Examples of omnichannel interventions and how to assess the impact

This workshop will explore how Dynamic Targeting is redefining commercial operations by empowering field teams with smart, fast, and rep-informed decisions. Participants will learn how a combination of AI-powered solutions are enabling pharma organizations to move beyond historical data and static segmentation—toward predictive, flexible, and hyper-personalized engagement strategies.

In the rapidly evolving pharmaceutical landscape, the success of drug launches is critical yet challenging, with many failing to meet expectations. As we anticipate over 400 drug launches between now and 2029, the need to close the performance gap is more pressing than ever. Our workshop, "Digital Forward Launch," will explore how AI and digital capabilities can revolutionize launch strategies to meet and exceed revenue forecasts. Drawing on ZS's extensive research across 50+ brands, we will delve into the critical first 12-24 months post-launch, where brand growth metrics such as new patient starts and new prescribers often plateau. We will discuss how a new "AI and digital-centric" mindset can transform commercial planning and execution, as well as agile decision-making, to enhance launch performance.

Participants will learn about the impact of personalized customer engagement on launch outcomes, with case studies demonstrating significant improvements in sales and brand adoption through AI-enabled personalization. Key pivots in launch commercialization, such as next-gen predictive targeting, new message intelligence and related content creation, and barriers-driven engagement will be discussed as essential components of this new paradigm. We look forward to an engaging discussion to share our thinking, and hearing your thoughts on the topic. The Digital Forward Launch approach can significantly enhance launch performance through AI-enabled capabilities, focusing on revenue acceleration and strategic agility. Engage with industry pioneers and gain insights into implementing these innovative strategies to ensure successful drug launches in the future.

In commercial pharma, speed to insight is the new competitive advantage. Join this hands-on session to see how AI Agents democratize diagnostic analysis, empowering business teams to uncover root causes of underperformance, misaligned targeting, and access barriers. Learn how top organizations are using Tellius to make faster, smarter moves than the competition.