What a BD team actually has to answer about an asset
When a licensing or acquisition target lands on the desk, the first week of work is surprisingly repetitive. The questions are the same for every asset.
- What has been tested, in whom, and what did the registered endpoints say?
- Who else is in this indication at the same stage, and who is catching up?
- Do the published results match the registry, or did the primary endpoint change?
- What does the market look like for the lead indication?
- How do we summarize all of it for a committee that has twenty minutes?
Different tools handle different questions. Buying one product and expecting it to cover everything is the usual disappointment.
AI tools for biotech BD compared by job
Categories are described from general knowledge of the market. Check each vendor for current features and prices.
ClinicalEvidence
- Best at
- Cited answers on trials and papers for an asset or indication, trial table, alerts, RIS, BibTeX, CSV, XLSX and DOCX export
- Weak spot
- No deal data, patents or sales forecasts
- Typical cost
- Clinician 49 USD per month, Research Team 199 USD per month (99 billed yearly), 3 seats
Enterprise pharma intelligence platforms
- Best at
- Pipelines, deals, patents and forecasts under one license
- Weak spot
- Contract pricing, built for a dedicated CI function
- Typical cost
- Quoted by the vendor
General chatbots
- Best at
- Fast first drafts and brainstorming
- Weak spot
- Can invent citations and trial identifiers
- Typical cost
- Subscription
AI market research tools
- Best at
- Company, market and competitor web research
- Weak spot
- Not trial level evidence
- Typical cost
- Subscription
Consultants and expert networks
- Best at
- Judgment on a specific asset
- Weak spot
- Cost and turnaround
- Typical cost
- Per project
Registry websites
- Best at
- Free raw records
- Weak spot
- Manual, one registry at a time
- Typical cost
- Free
Most small BD groups end up with an evidence tool plus a market research tool, and keep a chatbot for drafting only.
Using an evidence tool for asset due diligence
Evidence work is where mistakes are expensive, so the source behind each claim matters more than speed.
- Pull the asset's registered trials with the clinical trial search and open the trial table to see phase, status, enrollment, sponsor and countries in one view.
- Compare registered primary endpoints with the published results. A changed or dropped endpoint is a due diligence finding, not a footnote.
- Ask who else runs trials in the same indication. Filter by phase and sponsor type to separate large pharma programs from other small companies.
- Save the question and set an alert for the weeks between first look and signing.
- Export the table and references into the memo so the committee can open each source.
Verification shows that a cited record exists and supports the sentence. Your scientific lead still appraises study quality and relevance. Read why AI invents citations before you allow a generic chatbot near this work.
The competitive and market layer
Trials tell you about science and timing. They do not tell you about company size, pricing, partnerships or positioning. For that layer BD teams use web research and market intelligence. A tool that does AI market research and competitive intelligence can cover the commercial side of a competitor set once the evidence work has told you which companies belong in it, and the result sits next to your trial table in the memo.
The trial landscape before protocol design article shows how the same competing trial list feeds clinical planning, which BD teams often reuse for target selection.
Where chatbots belong
A chatbot is useful for turning verified bullet points into prose, tightening a committee summary or preparing questions for management. It is a poor source of facts about an asset. Give it the cited table and ask it to write around it, not to find the evidence.
A practical setup for a small BD group
One analyst and one director can start on Clinician and move to Research Team when a third person joins, since it pools 800 answers across 3 seats at 99 USD per month billed yearly. See pricing. Companies running several concurrent deals often pick Organization for 10 seats and an audit log. Add the market research tool of your choice, and keep any enterprise intelligence platform only if the deal and forecast data pays for itself.
Teams comparing paid options for the registry layer can also read the Trialtrove alternative page and the guide to clinical trial intelligence platforms for biotech.
Questions BD teams ask
What are the best AI tools for biotech business development?
Use a tool per job. ClinicalEvidence handles cited trial and literature evidence from three registries and PubMed. A market research tool handles competitor and commercial context. A chatbot drafts the memo from verified facts. No single product covers all three well.
Can AI do biotech due diligence?
AI speeds up the evidence gathering, not the judgment. It can list an asset's trials, compare registered and reported endpoints and monitor competitors, with a source for each claim. A qualified scientist still appraises the data and the deal team makes the call.
How do you check a competitor's clinical trials before a deal?
Search the registries for the indication and the rival drug, then record phase, sponsor, endpoints, status and countries. ClinicalEvidence does this from one question across ClinicalTrials.gov, the EU Clinical Trials Register and WHO ICTRP, and alerts the team to new trials.
Does ClinicalEvidence use confidential deal information?
No. It works on public registries and published literature. You do not upload internal documents, data room files or patient data.
How much does an AI evidence tool for BD cost?
ClinicalEvidence Clinician is 49 USD per month or 24 USD per month billed yearly. Research Team is 199 USD per month or 99 USD per month billed yearly with 3 seats and 800 pooled answers.