Trinity Life Sciences Launches the Only Predictive Insights Solution Powered by AIML and Grounded in Market Research and Real-World Data

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New infographic from Trinity Life Sciences, RWD + PMR = Tethering Demand Forecasts to Reality, maps out how integrated insights from primary market research and real-world data can improve market share estimates by nearly 20 times. Image credit: Trinity Life Sciences

WALTHAM, Mass.– Trinity Life Sciences, a leader in global life sciences commercialization solutions, today launched a new solution that accurately predicts stakeholder behavior providing deeper insights. For the first time, life sciences companies can incorporate real-world, healthcare professional (HCP)-specific prescribing behaviors with primary market research (PMR). This integration provides a view of what physicians are currently doing that is independent of what those physicians may say in market research studies.

The new solution, Trinity Real Insights, was created by experts with deep life sciences commercialization knowledge. Within market research studies, stated behaviors by physicians may be out of their control or contain inaccuracies from recall or bias. In contrast, the analytics in RWD studies don’t necessarily account for perceptions, beliefs and attitudes. By default, it is a historical view. Real Insights contains the best of both types of research: stakeholder self-reports AND the behavioral data to explain and predict based on the “why.”

Trinity Real Insights can answer the types of questions life sciences executives are asking:

  • Are we sampling the right physicians to represent our target universe?
  • Is there a risk of overlooking key HCP-level real-world behavioral nuances?
  • Are we controlling for response bias with sole reliance on self-reported data?
  • How can we create a granular, comprehensive view of stakeholders for hyper-targeting?
  • Can HCP-level learnings from one study be seamlessly linked to subsequent studies?
  • Given the inherent uncertainty, how can we explain and defend predictive insights?

“It is now possible to combine primary and secondary real-world data into a single source of truth that optimally supports robust, accurate decision-making,” explained Aparna Deshpande, Senior Partner and Head of Insights at Trinity Life Sciences. “With Trinity Real Insights, our team of PhD-level experts have developed AIML and predictive methods to tackle complex questions efficiently through this type of integrated data asset.”

Rooting predictions in reality boosts confidence in the estimates and outputs. A data-agnostic approach, which identifies, recommends and uses the RWD that best fits each question, allows for seamless integration of secondary/claims data with survey data at the HCP level.

“Each client’s situation is unique. Selecting the data sources that best suit the client and their business question, rather than relying on a single source, allows us to build predictive insights that can be confidently explained,” added Clive Mendonca, Managing Director and Head of Quantitative Insights at Trinity Life Sciences. “And the Real Insights approach is durable—these physician insights can be used by brands to enrich all subsequent studies.”

Trinity Real Insights allows for confident understanding and prediction of future stakeholder decisions through expert integration of PMR and RWD and the novel application of the resulting insights. Clinigraphics, patient mix and relevant prescribing behaviors are grounded in RWD to add an objective lens and a tether to reality. PMR captures the “whys” and “hows” behind current behaviors and future intentions. Trinity deploys AIML-based predictive models to generate an HCP decision map and predict future behavior, including identifying key targets of interest.

Real Insights allows insights and analytics teams to:

  • Assess the entire market from a business insights vantage point
  • Robustly predict future HCP decision-making
  • Gain deeper insights from experts with deep life sciences commercialization knowledge
  • Leverage insights in future initiatives and across engagements with seamless AIML-driven integration