Here’s what a real BD asset screen looked like on Ferma.
Objective: Identify acquirable CDH17 ADC assets before the competitive window closed. Asset universe: 33,575 drugs. Methodology: seven-stage screening funnel, indication fit, mechanism filter, clinical differentiation, IP assessment, deal feasibility, financial valuation, composite ranking. Output: 5 committee-ready targets, each with a composite scorecard, rNPV model, catalyst timeline, and deal validation package. Every data point cited to source.
One Agentic Workflow run. The kind of output that typically takes a pharma BD team one to two weeks to assemble manually, delivered in hours. That’s not a marginal improvement. It’s a structural one.
Why BD Asset Screening Has a Velocity Problem in 2026
The pharma BD landscape has changed faster in the last five years than in the previous twenty. Deal flow is accelerating. Emerging biotechs surface faster than any team can manually evaluate them. China went from marginal to the largest origin of global deal value in five years and western-centric BD platforms consistently miss the early-stage Chinese assets that become tomorrow’s licensing targets.
The tools haven’t kept pace. Cortellis and EvaluatePharma return lists of assets matching your search criteria. Your BD team then manually pulls clinical data, models the financials separately, sources deal comparables from a third platform, and formats the IC package, a process that takes one to two weeks per asset.
How Pharma BD Teams Currently Screen Assets And Where the Process Breaks
A typical Cortellis-based BD screening workflow: Week 1 — query Cortellis, export results, reconcile against PubMed, pull conference presentations manually, begin building composite scorecard in Excel. Week 2 — model rNPV separately, source deal comparables from a third database, format IC package in PowerPoint, review and revise.
At the end of this process, your BD team has a committee-ready package for one asset. The bottleneck is the synthesis step and that’s exactly what AI-powered BD asset screening is built to eliminate.
What an AI-Powered Opportunity Screener Does Differently
Ferma’s Opportunity Screener Agentic Workflow encodes your BD methodology, portfolio fit criteria, clinical differentiation thresholds, deal structure preferences, indication focus as an AI agent that runs the entire evaluation workflow automatically.
- Stage 1 — Define your criteria. Portfolio fit parameters, clinical differentiation standards, deal feasibility thresholds. Your methodology, encoded as the Agentic Workflow’s plan.
- Stage 2 — The 7-stage funnel executes. Ferma screens 23,000+ clinical and commercial drugs through seven sequential filters. Each stage narrows the field. Each decision is cited to the data that generated it.
- Stage 3 — Receive your IC-ready package. Ranked shortlist with composite scorecards, rNPV models, deal comp workbooks, catalyst timelines, and executive summaries for each qualifying target.
The Five Components of a Committee-Ready Diligence Package
- Composite Scorecard — clinical differentiation, IP strength, deal feasibility, and competitive positioning scored across dimensions. Every score traced to source data.
- rNPV Valuation Model — bottom-up risk-adjusted NPV using epidemiology, clinical PoS by phase, pricing benchmarks, and competitive dynamics. Bear, base, and bull scenarios.
- Deal Comparables Workbook — structured comparable deals by TA, mechanism, and phase. Upfront payments, milestones, royalty rates, total deal value. Excel format for the IC deck.
- Catalyst Timeline — upcoming readouts, FDA actions, PDUFA dates, and milestone triggers for the screened asset and its competitive set.
- Executive Summary Brief — single-page brief with scorecard, investment thesis, key risks, and recommended next steps. Formatted for licensing committee review.
When AI Screening Works Best
AI-powered BD asset screening delivers the most value in three scenarios: large outbound screens across a broad asset universe, inbound asset evaluation where your team needs a rapid defensible assessment, and continuous monitoring to track defined therapeutic areas and surface acquirable assets as they emerge.
The common thread is synthesis velocity, the ability to move from data to IC-ready output faster than the deal window allows with manual processes.
Ferma’s Opportunity Screener is trusted by BD teams at 19 of the top 20 global pharma firms. See how Ferma works.
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