Why Evaluate Data
Biopharma data you can build decisions on
Data drives your forecasts, models, investment decisions or AI, so you need to know where it came from and what sits behind it. Evaluate combines broad pharma and biotech coverage with specialist methodology, indication-level detail and human expertise to give your teams intelligence they can use with greater confidence.
Better tools depend on better data
Analytics, AI and proprietary models are becoming more sophisticated.
But a model cannot compensate for missing assets, a dashboard cannot explain an inconsistent forecast, and AI cannot create specialist context that was never in the underlying data.
That is why the data itself matters.
Evaluate is built around the complexity of pharma and biotech, giving teams structured intelligence designed for the questions they actually need to answer.
Why this matters
Better data does more than fill another database
It can help you:
See more
Reduce gaps in the markets and assets you are analyzing.
Question the assumptions
Use forecasts backed by established methodology.
Go deeper
Work at product, indication, company and event level.
Add specialist context
Benefit from human expertise alongside structured data.
Make more of your existing systems
Use Evaluate intelligence within the tools and workflows your teams already rely on.
The Evaluate data difference
See the data for yourself
Tell us which dataset you are considering, and we can provide a representative sample so you can review its structure, fields and relevance to your use case.
Looking for something specific? Tell us what you are trying to analyze and our team can advise on the most useful data to review.
Coverage that helps reduce blind spots
A market view is only as useful as the assets included in it.
Evaluate tracks more than 45,000 products globally and provides three times more Phase I–III forecasts than the average broker report, helping teams look beyond the most visible companies and assets when assessing a market or opportunity.
Use broader coverage to:
- Understand competitive landscapes
- Identify assets that may otherwise be missed
- Build more complete market views
- Strengthen screening and investment research
- Support more robust forecasting
Methodology you can interrogate
A forecast is more effective when you understand how it has been built.
Evaluate applies a proprietary methodology to consensus forecasting, with 87% of Evaluate consensus forecasts following that methodology and 81% incorporating three or more broker models.
This gives your teams a more consistent starting point for their own assumptions, analysis and models.
Why that matters
Pharma & biotech
Build forecasts and base portfolio decisions on a clear external benchmark.
Financial services
Understand the assumptions behind commercial expectations using data built on a consistent methodology, rather than relying on a single headline estimate.
Professional services
Use more defensible inputs in market models and client analysis.
Data and AI teams
Give downstream systems structured inputs with established methodology behind them.
See opportunity at indication level
The commercial outlook for the same product can vary significantly by indication.
Evaluate builds 83% of its consensus forecasts at indication level, with revenue data across approved and pipeline assets. This supports market sizing by indication, mechanism of action and company type.
Use indication-level intelligence to:
- Size more specific markets
- Compare opportunities across indications
- Support business development valuation
- Prioritize portfolios
- Benchmark competitors
- Build more granular forecasting models
Specialist analysts and domain experts sit behind the data
Not every valuable signal can be captured by simply aggregating public information.
Evaluate combines structured data with input from specialist analysts, domain experts and teams with scientific backgrounds to add context where it matters.
That expertise helps interpret important developments, assess their potential significance and strengthen the methodology behind the data. The current methodology includes analyst-driven likelihood-of-approval adjustments around important Phase III readouts, while 65% of event sources extend beyond news wires.
Bring Evaluate data into the workflows you use most
Evaluate intelligence can be used beyond the Evaluate interface.
Relevant data can be delivered for use within custom analytics, dashboards, data environments, internal search platforms and other workflows.
Your data environment
Internal data
Third-party data
Evaluate data
Your workflow
Models
Dashboards
Research platforms
AI / ML
CRM
Investment analysis
Connect different parts of the pharma and biotech picture
Many of the questions teams need to answer cannot be solved with one field or one dataset.
Evaluate’s portfolio spans commercial, company, deal, development and event intelligence, allowing customers to combine relevant datasets around the problem they are trying to solve.
| If you need to understand… | Relevant Evaluate data can include… |
|---|---|
| Market opportunity | Product Sales + Indication Sales + Peak Sales |
| Asset value and risk | Sales + PTRS + Timelines + R&D Costs + NPV |
| Competitive landscape | Product Attributes + Sales + Events + Deals + Patents |
| Partnering opportunities | Product data + Company data + Deals + PTRS |
| Investment catalysts | Events & Catalysts + relevant point-in-time data |
| AI / internal analytics | A tailored combination based on the questions being modelled |
These are examples, not fixed packages. You can choose the datasets relevant to your needs and build the combination around your workflow.
Different teams have different questions, but the same need for dependable data
Pharma & biotech
Which markets are changing? Which assets deserve investment? Where are competitors moving?
Use Evaluate data across forecasting, portfolio strategy, competitive intelligence, partnering and internal analytics.
Financial services
What is the commercial opportunity? Where is the risk? What could change the investment case?
Use structured pharma and biotech data across research, valuation, screening and diligence.
Quantitative research
What was known at the time, what changed and what happened next?
Selected Evaluate datasets are specifically structured for point-in-time quantitative analysis, including company ownership and catalyst changes.
Professional services
How do we build a stronger evidence base for client recommendations?
Use Evaluate data within proprietary models, research platforms and analytical workflows.
Give AI more than public information to work with
General-purpose AI can synthesize huge volumes of public information quickly. But specialist pharma and biotech questions often require data that is structured, consistent and traceable back to a trusted source.
Public web information can come from many different sources, with varying levels of reliability, accuracy, structure and methodology. The same drug, company or event may also be described differently across sources, creating duplication and inconsistency that makes it hard to build a reliable view.
Evaluate gives AI-enabled workflows access to curated, harmonized and proprietary pharma and biotech data, including intelligence that general-purpose models do not inherently have access to.
Public information can provide:
- Company disclosures and announcements
- High-level clinical trial information
- Published financial information
- News, websites and other publicly available sources
Evaluate data can add:
- Proprietary product and indication intelligence
- Historical and forecast sales
- Indication-level sales and opportunity
- Standardized product and company information
- Market, competitive and event context
- Data with a clear source and established methodology
Give your AI a more consistent view
Instead of pulling together fragmented information from multiple sources, Evaluate provides structured and harmonized data designed to be used consistently across products, indications, companies and markets.
That means your teams can understand where the information has come from, reference the underlying data and give AI models more reliable domain-specific context for specialist pharma and biotech questions.
You can integrate Evaluate data into AI-enabled systems, predictive models and other approved applications. Licensing options are available to enable you to give internal tools access to curated and proprietary intelligence alongside your own data.
Put better biopharma data behind your next decision
Choose the Evaluate datasets relevant to your needs and use them within the models, systems and workflows your teams already rely on. Give us the questions you need to answer and we will help identify the data and access approach that fits.
Tell us what data you need
Tell us briefly about the question, workflow or problem you are trying to solve.
Not sure which datasets you need? Tell us what you are trying to solve, and we can help identify the right options.
Common questions
Frequently Asked Questions
What makes Evaluate data different?
Evaluate combines broad pharma and biotech coverage with specialist methodology, indication-level forecasting and analyst input. The data is built around life sciences-specific questions rather than broad cross-industry analysis.
How are Evaluate forecasts created?
Evaluate applies proprietary methodology to consensus forecasting. 87% of Evaluate consensus forecasts follow this methodology and 81% incorporate three or more broker models.
Does Evaluate offer point-in-time data?
Yes, selected Evaluate datasets are available for point-in-time analysis. Relevant datasets include historical company ownership and catalyst updates structured to support quantitative research and historical analysis.
Can Evaluate data be combined with our own data?
Yes. Current Evaluate use cases include combining Evaluate datasets with customer and other third-party data in analytics, dashboards, knowledge-management and predictive workflows.
Where does Evaluate data come from?
Evaluate draws on a broad range of sources, including company disclosures, published financial information, clinical and regulatory information, market developments and other specialist sources, structured and supported by established methodologies and specialist analysis.
Is indication-level data available?
Yes. 83% of Evaluate consensus forecasts are built at indication level, including revenue data across approved and pipeline assets, supporting more granular market sizing, valuation and portfolio analysis.
Can Evaluate data be used in AI and machine-learning applications?
Licensing options are available for appropriate AI-enabled uses. Evaluate’s current offering includes curated and harmonized data delivery with AI use rights, with the exact access model depending on the use case.
