Defensible Prioritization in Biopharma Without Arbitrary Scoring

Biopharma teams routinely face high-stakes prioritization decisions, including which targets to advance, which biomarkers to pursue and which clinical strategies to implement. While data availability continues to increase, many organizations lack a structured, transparent process for translating evidence into consistent and defensible decisions. This webinar examines how a decision-support tool can improve the rigor and clarity of prioritization decisions.

Traditional approaches such as multi-criteria decision analysis and weighted scorecards are widely used but often rely on subjective weighting, inconsistent criteria and simplified scoring systems that may not adequately reflect uncertainty. As a result, decision processes can become difficult to defend, challenging to audit and prone to internal debate.

This webinar will present a novel structured decision-support tool that replaces arbitrary scoring with transparent, repeatable comparisons. The tool organizes available evidence, supports consistent evaluation across alternatives and generates outputs with a clear and auditable rationale. Rather than compressing uncertainty into a single composite score, the tool makes underlying assumptions and evidence drivers explicit, enabling stakeholders to understand what influences a ranking and what conditions could alter an outcome.

Attendees will learn how structured decision environments can support cross-functional alignment, improve confidence in portfolio and trial strategy decisions and strengthen governance without requiring extensive system changes. Practical use cases will be discussed, including portfolio prioritization, target selection, biomarker strategy and clinical trial optimization.

Register for this webinar to learn how a decision-support tool can strengthen defensibility, transparency and consistency in biopharma decision-making.

Speaker

Juan Felipe Beltrán Lacouture, PhD, Senior Director of AI, Machine Learning & Innovation, BullFrog AI

Juan Felipe Beltrán is Senior Director of AI, Machine Learning & Innovation at BullFrog AI, where he leads development of AI systems that transform fragmented clinical trial data into actionable intelligence for pharmaceutical decision-makers. Previously, he developed protein sequencing algorithms at Quantum-Si, with work published in Science. Juan holds a PhD in Computational Biology from Cornell and specializes in making advanced analytics auditable, repeatable and operationally useful for cross-functional drug development teams.

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