Deal Structure Guide
Biopharma Deal Databases Compared: Choosing the Right Platform in 2026
Coverage, analytical tools, pricing, and workflow fit — an honest comparison of the platforms BD teams actually rely on.
Why your deal database matters
Business development teams in biopharma make decisions that involve hundreds of millions of dollars — licensing upfronts, milestone structures, royalty rates, M&A premiums. The foundation of every one of those decisions is a comparable transaction: what did similar assets trade for, and under what terms?
The quality of that foundation depends entirely on the deal database you use. Bad comps produce bad term sheets. Incomplete data produces anchoring errors that transfer value from one side of the table to the other. A database that shows you the headline deal value but not the milestone structure, the royalty tiers, or the diligence obligations gives you a number without the context that makes the number meaningful.
The market for deal intelligence has changed materially in the past five years. The legacy model — static PDF reports licensed at six-figure annual contracts — is giving way to platforms that combine deal data with analytical tools, valuation engines, and real-time updates. The question is no longer whether to use a deal database. It is which platform fits your workflow, your budget, and the analytical depth your team actually needs.
This guide provides a fair, fact-based comparison of the major platforms. We are transparent about our position: Solidus is our platform, and we believe it offers distinct advantages for teams that need analytical tools alongside their data. But we also recognize that different platforms serve different needs, and the right choice depends on what your team is trying to accomplish.
The major platforms
DealForma is one of the most established names in biopharma deal intelligence. Built specifically for the life sciences licensing and M&A market, DealForma offers a curated database of licensing deals with strong coverage of deal terms — upfronts, milestones, royalty ranges, and territory structures. It is widely used by BD teams at both pharma and biotech companies, and its data is frequently cited in industry analyses. DealForma's strength is its focus: this is a purpose-built pharma deals platform, not a generalist business database that happens to cover life sciences. Pricing is enterprise-oriented, typically requiring an annual contract that reflects the specialized nature of the data.
Cortellis, owned by Clarivate Analytics, is the largest deal database by volume, with over 15,500 deals and access to underlying contract documents through its Cortellis Generics Intelligence and Cortellis Competitive Intelligence modules. Its breadth is its primary advantage — if a deal was publicly announced, Cortellis likely has it. The platform also integrates patent data, clinical trial information, and regulatory intelligence, making it a comprehensive research tool for teams that need to connect deal data with broader competitive intelligence. Cortellis is enterprise-priced and research-oriented; it is the platform of choice for large pharma competitive intelligence departments and consulting firms that need exhaustive coverage. The trade-off is that its analytical tools are built for research workflows rather than deal-level modeling.
Evaluate (now part of Norstella) provides consensus forecasts, pipeline analytics, and deal data with a focus on investor-facing analysis. Its strength lies in commercial forecasting — Evaluate aggregates sell-side analyst projections to produce consensus revenue estimates for both marketed and pipeline drugs. For teams that need to bridge deal intelligence with commercial projections, Evaluate fills a specific niche. Its deal data coverage is solid but generally offers less granularity on individual deal terms than platforms built specifically for transaction benchmarking.
PitchBook, owned by Morningstar, is a broad financial data platform covering venture capital, private equity, and M&A across all industries. Its biopharma coverage is improving but it is not pharma-specialized. PitchBook excels at tracking financing rounds, investor participation, and private company valuations — data that complements deal-level intelligence but does not replace it. For biotech venture investors and PE firms, PitchBook is often a primary tool. For pharma BD teams focused on licensing term benchmarking, it is typically a supplement rather than a primary source.
Solidus — our platform at solidus.ambrosiaventures.co — takes a different approach. Built by deal practitioners rather than data aggregators, Solidus combines a verified database of 1,600+ biopharma transactions with 21 integrated analytical engines: rNPV calculators, Monte Carlo simulators, milestone achievability models, royalty benchmarking, competitive dynamics analysis, and AI-generated deal memos. The thesis behind Solidus is that data without analysis is only half the job. BD teams do not just need to know what comparable deals looked like — they need to model what their deal should look like. The platform offers a free tier for individual users, with Pro and Enterprise tiers for teams that need full analytical access. The trade-off is a smaller total deal count than Cortellis, offset by deeper analytical integration and the verification process that ensures deal terms are accurate at the field level.
What to look for in a deal database
Choosing a deal database is not about finding the platform with the most deals. It is about finding the platform that supports the decisions your team actually makes. Six criteria should drive the evaluation.
Deal term granularity. A database that tells you a deal was worth $1.2B is less useful than one that tells you $75M was upfront, $425M in development milestones, $500M in commercial milestones, and royalties were tiered from 8% to 14% on net sales with a 50% step-down on patent expiry. The granularity of deal term data determines whether you can build credible comp sets or are limited to headline numbers. Ask: does the platform break out upfront, development milestones, regulatory milestones, commercial milestones, and royalty structures separately?
Analytical tools. Data is the input. Analysis is the output. A platform that provides deal data but requires you to export to Excel for every calculation adds friction to the workflow. Look for: built-in rNPV and DCF calculators, Monte Carlo simulation, milestone achievability modeling, and the ability to generate comp-based valuation ranges directly from the data. The difference between a data platform and an analytical platform is the difference between having ingredients and having a kitchen.
Update frequency. The biopharma deal landscape shifts weekly. A database updated quarterly misses the transactions that matter most in active negotiations. Ask: how quickly are new deals added after announcement? Are deal terms updated when amendments or additional disclosures become available?
Modality and therapeutic area coverage. Not all databases cover all modalities with equal depth. If your pipeline is concentrated in antibody-drug conjugates, cell therapy, or gene therapy, verify that the platform has sufficient deal coverage in those specific modalities to build meaningful comp sets. A database with 10,000 deals but only 15 ADC transactions is not useful for ADC benchmarking.
Pricing accessibility. Enterprise platforms with six-figure annual contracts serve large pharma competitive intelligence departments well. They are prohibitively expensive for biotech companies, academic medical centers, venture investors, and boutique advisory firms. Consider whether the platform offers flexible pricing — per-user tiers, limited free access, or usage-based models — that match your team's budget and the frequency of your deal-level analysis needs.
Workflow integration. The best database is the one your team actually uses. Consider how the platform fits into existing workflows: does it support data export in formats your team works with? Can you share analyses with colleagues without requiring each person to have a license? Does it integrate with the presentation and modeling tools your BD team already uses?
Matching the platform to your needs
There is no single best deal database. The right choice depends on what your team needs, how it works, and what decisions the data will inform.
For enterprise research and competitive intelligence departments at large pharma, Cortellis is the natural fit. Its breadth of coverage, integration with patent and clinical trial data, and enterprise-grade infrastructure support the comprehensive research workflows these teams require. The investment is significant, but for organizations making dozens of BD decisions annually across multiple therapeutic areas, the depth of coverage justifies the cost.
For teams focused on commercial forecasting and investor-facing analysis, Evaluate provides a differentiated offering. Its consensus forecast data bridges deal intelligence with commercial projections in a way that other platforms do not, making it particularly valuable for investor relations, corporate strategy, and commercial planning teams.
For venture and PE investors tracking biopharma financing and private company activity, PitchBook remains the primary tool. Its strength is in the financial data ecosystem — round sizes, investor participation, post-money valuations — that deal-focused platforms do not prioritize. It complements rather than replaces a deal-term database.
For BD teams that need analytical tools alongside their data — teams that are actively modeling deals, running valuations, benchmarking term sheets, or preparing for licensing negotiations — Solidus is purpose-built for that workflow. The integrated rNPV calculator, Monte Carlo simulator, milestone achievability engine, and AI deal memo tools eliminate the gap between finding a comparable transaction and modeling what your transaction should look like. The free tier makes it accessible to teams at any budget level, and the verified data ensures that the deal terms you are benchmarking against are accurate at the field level.
The mistake most teams make is choosing a platform based on deal count alone. A database with 15,000 deals is not more useful than one with 1,600 if the 1,600 are verified at the field level and integrated with the analytical tools you need. Coverage matters — but coverage without analytical depth is a reference library, not a workbench.
The second mistake is paying for capabilities you do not use. Teams that run 3-5 comp analyses per year do not need an enterprise platform designed for daily competitive intelligence workflows. Match the investment to the actual usage pattern.
Explore Solidus and see how it compares to your current platform at solidus.ambrosiaventures.co. Compare specific alternatives at solidus.ambrosiaventures.co/compare/dealforma and solidus.ambrosiaventures.co/compare/cortellis.
Frequently asked questions
Which biopharma deal database has the most deals?
Cortellis (Clarivate) has the largest database by volume with over 15,500 deals, including access to underlying contract documents. DealForma and Evaluate also maintain substantial databases focused on biopharma licensing and M&A. Solidus tracks 1,600+ verified transactions with deeper analytical integration. However, deal count alone is not the most useful metric — the granularity of deal terms, the accuracy of the data, and the analytical tools available to work with the data are equally important in determining which platform best serves your needs.
Are there free biopharma deal databases?
Most enterprise deal databases — Cortellis, DealForma, Evaluate — require annual contracts, typically in the five- to six-figure range. PitchBook offers institutional licensing. Solidus is the primary platform that offers a free tier with access to deal data and basic analytical tools, with Pro and Enterprise tiers for teams that need full access to all 21 analytical engines, Monte Carlo simulation, and AI deal memos. Public sources — SEC filings, press releases, ClinicalTrials.gov — provide raw deal announcements, but extracting structured deal terms from these sources requires significant manual effort.
Can I export deal data for my own analysis?
Export capabilities vary by platform and licensing tier. Most enterprise platforms offer data export in CSV or Excel formats, though some restrict export volumes or require higher-tier subscriptions for bulk export. Solidus supports data export and integrates analytical tools directly into the platform, reducing the need to export data into external spreadsheets for modeling. When evaluating platforms, confirm that the export format, volume limits, and licensing terms align with your workflow — particularly if your team needs to incorporate deal data into internal models, board presentations, or regulatory submissions.
Related Insights
Further reading from our research.
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