Webinar- Predictive Intelligence - The Secret Weapon in Pharma BD Assessment with GSK, Veeva, Verix

This webinar provides an in-depth exploration of how predictive intelligence and intelligent automation serve as a "secret weapon" in pharmaceutical Business Development (BD) assessments. Featuring perspectives from a strategic investor (GSK), a data provider (Veeva), and an analytics platform vendor (Verix), the discussion centers on transforming the complex, high-stakes process of evaluating M&A and licensing opportunities. The core challenge identified by Jacob Pajooki (GSK) is the need to integrate vast, disparate data sets—scientific, commercial, and financial—under immense time pressure and often with incomplete information, making BD assessments a blend of "art and science."

The speakers emphasize that while data is foundational, the true value is realized by efficiently converting that data into actionable insights. Traditional BD processes often get stuck due to data silos (clinical, market, epidemiology), lack of a systematic framework, and difficulties in achieving stakeholder alignment. The solution presented leverages best-in-class data assets, specifically Veeva Compass Patient data, combined with Verix’s automated analytics platform, Tavana. This integration aims to provide a more robust, real-world informed opinion of an asset's potential, moving beyond high-level epidemiology reports to quantify the truly eligible patient population and understand the commercial effort required for launch.

The Verix Tavana platform is introduced as a modular, automated solution designed to streamline the forecasting process, which is traditionally manual and time-consuming. The platform incorporates building blocks for landscape assessment, patient prediction, patient-based forecasting, SGA estimation, and Monte Carlo simulation. By automating these analytical tasks, the platform frees up human expertise to focus on less structured problems and critical judgment calls, thereby accelerating the time to decision-grade insights. The quantitative benefits highlighted include a 50% reduction in cost and cutting the assessment timeline from approximately six weeks to under one week, enabling unlimited assessments at a fixed cost. This approach ensures consistency and a data-driven basis for comparing competing opportunities, which is crucial for achieving rapid alignment among the large stakeholder teams typical of strategic investors like GSK.

The discussion also delves into the critical role of granular, real-world data (RWD) in refining valuations. Jacob from GSK provided examples where detailed longitudinal patient data reveals roadblocks, such as high market inertia or a widely distributed patient population, which can significantly shrink the realistic market potential compared to initial scientific belief. Veeva Compass Patient data, characterized by its completeness, unlimited access, and daily updates, addresses these data limitations by providing anonymous longitudinal data encompassing prescriptions, procedures, and diagnoses, including visibility into previously blocked segments like specialty pharmacy and hospital/HCO settings. This timeliness and depth are essential for understanding the current state of the market and ensuring the valuation reflects the true scope of commercial investment needed for a near-term launch.

Detailed Key Takeaways

• BD Assessments are High-Stakes and Complex: Pharmaceutical BD assessments are high-stakes exercises involving billions of dollars, requiring a difficult blend of scientific rationale, commercial strategy, and precise timing, often conducted under pressure with incomplete information.
• The Need for Data Integration and Structure: A major pain point is breaking down data silos (clinical, market, competitive landscape, epidemiology) and integrating them quickly. Implementing a systematic framework and disciplined approach to data sources is essential for scaling BD evaluation efforts.
• Automation Accelerates Decision-Making: Leveraging advanced analytics and automation (like the Verix Tavana platform) converts manual forecasting and data sifting into streamlined, consistent processes, freeing up human experts to focus their judgment on critical, less-structured issues (e.g., IP, manufacturing, instinct).
• RWD Refines Market Potential: Relying solely on high-level epidemiology data can lead to inaccurate forecasts. Robust, deep, and broad real-world data (RWD) is necessary to quantify the truly eligible patient population, understand patient distribution, and assess the commercial effort (field force size, investment) required for market penetration.
• Longitudinal Patient Data is Critical for Commercialization: Tracking patient history and treatment cycles reveals market inertia and patient flow roadblocks. For late-stage assets (launching in 2-3 years), understanding these dynamics is crucial for accurately scoping the required commercial investment and balancing the Net Present Value (NPV) equation.
• Platform-Based Approach Drives Efficiency: Utilizing a modular, platform-based solution (like Tavana) allows companies to conduct rapid evaluations, reducing the time to decision-grade insights from six weeks to under one week, demonstrating a significant ROI (50% cost reduction) and enabling unlimited assessments at a fixed cost.
• Data Timeliness is Essential for Valuation: Daily data updates (as provided by Veeva Compass Patient) are critical for BD efforts, providing the most timely view of the market, allowing teams to see how the market is reacting to recent clinical or competitor activities and ensuring the valuation reflects the current state.
• Addressing Data Blind Spots: Comprehensive data networks must include visibility into previously blocked segments, such as specialty pharmacy and hospital/HCO settings, to provide a full 360-degree view of the market dynamics and competitive landscape.
• The Role of AI is Supportive, Not Autonomous: The advanced analytics platform operates on a "human-in-the-loop" model, combining human intelligence with machine learning. The platform provides a comprehensive, robust view of the market faster, informing the "go/no-go" decision and confidence level, rather than making autonomous decisions.
• Data Granularity Impacts Investment Assumptions: Detailed, data-driven assessments often lead to a more realistic view of investment costs. While traditional approaches might be overly ambitious on forecasts and overly conservative on costs, granular data can rationalize lower investment costs, helping maintain a strong NPV.
• Supporting the Full Commercial Cycle: Beyond BD, foundational patient data (like Veeva Compass Patient) supports other commercial use cases, including building triggers and alerts based on daily activity, and improving segmentation and targeting accuracy by providing a complete view of HCP and patient interactions.

Tools/Resources Mentioned

• Veeva Compass Patient: Anonymous patient longitudinal data network that includes prescriptions, procedures, and diagnoses. Noted for completeness, unlimited access, and daily updates, providing visibility into specialty pharmacy and hospital settings.
• Verix Tavana Platform: An automated, modular platform for advanced analytics and predictive intelligence. Used to build fit-for-purpose tools for BD assessment, forecasting, and commercial operations.
• Veeva CRM: Mentioned in the context of integrating triggers and alerts built off Compass Patient data.

Key Concepts

• Predictive Intelligence: The use of advanced analytics, machine learning, and automation to forecast future market conditions, patient behavior, and commercial potential of an asset, particularly within the context of BD assessments.
• Business Development (BD) Assessment: High-stakes evaluation process in life sciences (M&A, licensing) that integrates scientific, commercial, and financial data to determine the value and viability of an asset.
• Net Present Value (NPV): A financial metric used in BD to evaluate the profitability of an investment opportunity, calculated by balancing the expected future revenue (forecast) against the required investment (commercialization costs).
• Human-in-the-Loop (HITL): An AI/ML approach where human expertise and judgment are integrated into the automated process. The technology provides robust data and insights, but the final decision-making authority remains with the human experts.