Ai-powered Pipeline Prioritization
Just 5%
of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L impact.¹
The Input
Portfolio decisions made using bulk ranking AI tools produce outputs that are costly to generate and virtually impossible to defend when an assumption is questioned.
bfARENAS™ partitions every portfolio decision into the minimum set of structured pairwise comparisons needed to produce a stable, auditable ranking that relies on the following:
Your drug targets, biomarkers, indications, candidate programs, CRO vendor options, or portfolio assets.
Work with our team to order success criteria across independent decision arenas (e.g., scientific evidence, commercial opportunity, reputational impact).
THE WORK
bfARENAS™ replaces fragile, arbitrary numerical weights with structured pairwise comparisons:
01
04
05
Rankings are based on ordered priorities, with stability scores showing how robust each rank is and a complete audit trail from every recommendation back through every pairwise comparison to the underlying evidence:
An AI agent evaluates candidates head-to-head within independent arenas, assembling and challenging evidence.
Resolves arguments systematically based on human-defined priority orderings.
Experts In The Loop
Scientists and executives define the decision criteria, set the priority ordering among arenas and review the ranked output before any decision is made. bfARENAS™ does not make portfolio decisions. It structures them for your review.
“The decision belongs to the team. The audit trail belongs to everyone.”
Teams define evaluation criteria and priorities
Scientific and business assumptions remain visible
Every recommendation can be examined and challenge
The Output
bfARENAS™ replaces weighted scoring with structured pairwise comparison across independent decision arenas that are selected based on identified priorities and criteria for success. Features of the platform:
De-risked asset lists accompanied by rank stability scores
Visibility into ranking assumptions and trade-offs within the arenas
Fully readable arguments detailing every head-to-head comparison back to the underlying evidence
Each comparison, or arena, represents one strategic dimension of the decision. Candidates are evaluated head to head using advocate/critic reasoning: evidence is assembled, arguments are made, challenged, and resolved by an AI agent that serves as a neutral judge. This information can be leveraged when prioritizing drug targets, portfolios, programs, vendor selection, indication expansion, resource allocation, and investment planning.
The Outcome
Defensible portfolio choices that hold firm under board and regulatory scrutiny without changing on every re-run or re-consideration. The platform deliberately rejects numerical weights because the moment weights are assigned, they cannot be justified, creating a decision process that looks rigorous but actually isn’t.
Proof Point: Multi-Level Strategic Decision Support
The following examples were demonstrated at our recent XTalks webinar, illustrating how bfARENAS™ structures decisions across three levels of strategic complexity:
Ranking drug targets across scientific evidence arenas to pinpoint key evidentiary gaps.
Evaluating vendor candidates for a IPF Phase Ib/IIa trial, flagging a candidate mismatch hidden from standard scorecards.
Structuring a 5 program pipeline under capital constraints, surfacing strategic reputational costs invisible to spreadsheet models.
Run a complex portfolio or prioritization decision through bfARENAS™ to stress-test your existing assumptions. As organizations scale their use of AI across their workflows, many are discovering the challenges with reproducing their assessment and importantly, defending their decisions to a steering committee, scientific review board, a regulatory agency, or a board of directors that could withstand an audit.
Reference 1: Challapally, A., Pease, A., Raskar, R., & Chari, P. (2025). The GenAI Divide: State of AI in Business 2025, MIT Project NANDA
