Ferma Blog

What Is an Agentic Workflow in Pharma? (And Why It’s Replacing Manual CI and BD Research)

Written by Aravindha Kumar Asaithambi | May 31, 2026 2:07:49 PM

Pharma intelligence teams don’t have a data problem. Cortellis, AlphaSense, GlobalData, and a dozen other platforms deliver more data than any team can meaningfully process. What pharma CI, BD, and NPP teams actually have is a synthesis problem, the gap between raw data and the finished competitive landscape, BD screening package, or conference summary that a leadership team can act on.

That gap is where Agentic Workflows come in.

What Is an Agentic Workflow?

An Agentic Workflow is a pre-built, customizable workflow that encodes a specific life sciences research process such as a competitive landscape, opportunity screen, or medical congress coverage brief, end to end. You define the objective and parameters. The Agentic Workflow pulls from multiple data sources simultaneously, applies your methodology, and produces a finished, cited deliverable in your format automatically, without manual assembly.

Each Agentic Workflow is fully customizable to your team's specific use case, data preferences, and methodology, and every report it produces can be tailored to meet your organisation's exact output requirements.

Unlike a database subscription that returns search results for your team to interpret, or a generic AI tool that generates unverified summaries, an Agentic Workflow runs the complete research process from data collection through synthesis and deliverable formatting, with every claim cited to the source that generated it. See how Ferma works.

Ferma currently offers 12+ Agentic Workflows, a number that continues to grow as we collaborate with industry practitioners covering CI, BD&L, NPP, Medical Affairs, and Portfolio Strategy use cases, all running on a single continuously updated data layer across 211,000 clinical trials, 489,000 conference records, and 23,000+ pipeline assets.

How an Agentic Workflow Differs from What You’re Using Today

Most pharma intelligence teams currently operate with one of two tool types, and both leave the synthesis gap open.

Database subscriptions (Cortellis, GlobalData, EvaluatePharma) return structured data your team must manually extract, reconcile across sources, and format into stakeholder-ready outputs. The data exists. The deliverable is still your team’s problem. Cortellis refreshes approximately 60% of its data annually meaning a significant portion of the database is stale at any given time.

AI search tools (AlphaSense) add a search layer on top of documents and transcripts, but they were built for financial services and carry uneven life sciences data coverage particularly in preclinical intelligence, China pipeline, and scientific conference data. They surface relevant documents. They don’t run the workflow.

An Agentic Workflow does what neither category can, it runs the full research process automatically, monitors configured sources continuously, and delivers a finished output your team can distribute the same day the data moves.

What an Agentic Workflow Actually Does - Four Steps

  • Step 1 — Define your objective. Tell Ferma what you’re working on, a competitive landscape, a BD asset screen, a conference coverage brief. Your methodology is encoded as the Agentic Workflow’s plan.
  • Step 2 — Agents execute. Ferma pulls from preclinical, clinical, commercial, regulatory, and conference data simultaneously applying your encoded methodology and surfacing structured intelligence as it emerges. No manual reconciliation. No switching between tools.
  • Step 3 — Review and validate. Every step is auditable. Every data point is cited to source. You own the methodology, agents handle the execution.
  • Step 4 — Receive your finished deliverable. Competitive landscape brief, BD screener package, conference summary, or portfolio analysis, formatted for your stakeholders and exportable to PowerPoint, Excel, or PDF.

Which Pharma Teams Use Agentic Workflows?

  • CI teams use Agentic Workflows for competitive landscapes, pipeline trackers, readout analyses, KOL mapping, and conference coverage, finished and distributed the same day the data moves.

  • BD & Licensing teams use Agentic Workflows for opportunity screeners, rNPV valuation models, deal comparables analyses, and catalyst trackers, IC-ready packages produced automatically in a single workflow run.

  • NPP teams use Agentic Workflows for indication landscapes, patient segmentation models, TPP benchmarking, and unmet need analyses, built on live data, not quarterly TA report exports.

  • Medical Affairs teams use Agentic Workflows for evidence gap analyses, KOL mapping, and conference coverage, so MSLs and KOLs go into every stakeholder conversation with the full competitive evidence picture.

The Shift From Data to Deliverables

The pharma intelligence market has spent 20 years optimising for data access. Agentic Workflows represent a different bet that the constraint isn’t data, it’s synthesis. That the value a pharma intelligence platform should deliver isn’t a database to query, but a finished deliverable your team can act on.

For CI, BD, and NPP teams that spend 40% of their week reconciling data before any analysis can begin, that’s not a marginal improvement. It’s a structural one.

 

Ferma is the life sciences intelligence platform powered by Agentic Workflows — trusted by 19 of the top 20 global pharma firms. See how Ferma works.

 

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