The agency publishes its medicine data for download. Quoting you for a crawl without checking that first would be taking money for work nobody needs.
Plans from €169/month · Free project assessment · Reply within 1 business day
ScrapeIt builds and runs the pipeline as a managed service. You name the therapeutic areas, substances or holders; we collect the register and the documents, extract assessment reports with structure preserved, and hand back CSV, JSON, Excel or a push into your warehouse.
This is public regulatory information, published for use, and it contains no patient data. If your use case feeds regulatory submissions or pharmacovigilance, take it to your own regulatory team before the project starts, since the tolerance for error there is different from ordinary analytics.
The medicine record covers the medicine name, international non proprietary name, active substance, therapeutic area, ATC code where published, marketing authorisation holder, authorisation status, authorisation date and the procedure type.
Status history is kept rather than overwritten. A medicine that was authorised, then suspended, then reinstated has a history that a current status field destroys, and the transitions are precisely what regulatory and competitive teams watch for.
Document records carry the document type, title, publication date and the medicine it belongs to. Where a client needs the content, assessment report text is extracted with its section structure preserved, because the indication section and the discussion section answer different questions and a flat text blob answers neither well.
Safety information is collected as its own record type: referrals, their trigger, the committee involved and the outcome with its date.
Provenance is recorded per row: the page or document each value came from, so any value can be traced back to where it was published.
Assessment report extraction is the substantial piece of work. Reports are long documents with consistent structure, and extracting them section by section - indication, clinical efficacy, safety, conditions of authorisation - produces something an analyst can query rather than read. Doing it well takes account of the fact that the structure has changed over the years.
Shortage notices are a separate and time sensitive record type: which medicine, which countries affected, the reason given and the expected resolution. For supply chain and procurement teams in healthcare that is one of the more operationally useful things the agency publishes.
Joining to clinical trials is the standard extension. An authorisation rests on trials, and the trial identifiers frequently appear in the assessment report, which connects the regulatory record to the study record. That is the same pipeline as our clinical trials work and the two are usually bought together.
Historical depth is good: the register retains withdrawn and superseded medicines, so a retrospective on a therapeutic area is practical as a one time job.
The European Medicines Agency evaluates medicines for the European Union. Its site carries the authorised medicine register, the assessment reports behind each authorisation, safety referrals, shortage notices and the committee outcomes that drive all of it.
Safety referrals and shortage notices sit beside the register as their own record types: a referral with its trigger, the committee involved and the outcome with its date, a shortage with the countries affected, the reason given and the expected resolution.
Then there are the documents. Assessment reports are substantial PDFs per medicine, and the useful content inside them - indications, the committee's reasoning, conditions attached to an authorisation - is not laid out as a table. That is where collection earns its place.
The register is structured around the medicine: name, active substance, therapeutic area, authorisation holder, status and the document set attached.
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Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan details →Most of what people first ask for on this source is the register: authorised medicines with their holders, statuses and authorisation dates, collected on a schedule so every change is caught.
What the register does not give is the reasoning. An assessment report explains what the committee concluded, on what evidence, and with what conditions attached, and for regulatory affairs and competitive intelligence that content is the entire point. It exists as documents per medicine, and turning several thousand of them into structured, queryable text is a real piece of work.
The second thing collection adds is history. A register entry is a snapshot of current state, and the interesting events here are transitions: an authorisation granted, a referral opened, a status changed, a shortage declared. Those exist only if somebody was observing, and once they exist they answer questions about timing that no current-state snapshot can.
The third is joining outward. A medicine record connects to clinical trials, to literature and to national registers, and the value in a regulatory dataset usually sits in the join rather than in any single source. We build that rather than delivering one source and a problem.
The last is that this is public regulatory information: we collect only publicly available data - everything a visitor can see on the EMA website - and we collect it legally.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed extraction company, not a tool you have to learn. Our team builds the pipeline, watches it as the site and the document formats change, and repairs it before your regulatory monitoring goes quiet.
You see a sample first, in your format, over the therapeutic area you actually track, with assessment report extraction applied so you can judge the hard part on real documents.
Yes. The ScrapeIt EMA API returns medicine name, active substance, authorisation holder, status history and assessment report sections as JSON from an endpoint we host, refreshed on the schedule you set. The same data also comes as CSV or XLSX files or straight into your database. The assessment reports - the committee's reasoning, the evidence, the conditions attached - are turned into queryable structured text, which is the work worth paying for.
Yes, as transitions rather than a current value. A medicine authorised, then suspended, then reinstated has a history that a current status field destroys, and those transitions are exactly what regulatory and competitive teams watch. They exist only from the point where observation started.
Section by section - indication, clinical efficacy, safety, conditions of authorisation - so an analyst can query rather than read. The structure has changed over the years, so the extraction accounts for several document generations rather than assuming one layout.
Yes, as their own time sensitive record type: medicine, countries affected, reason given and expected resolution. For procurement and supply chain teams in healthcare it is one of the more operationally useful things the agency publishes.
No. This is regulatory information about medicines: authorisations, assessments, safety referrals and shortages. There is no patient data on these surfaces. If the output feeds regulatory submissions or pharmacovigilance, take it to your regulatory team first, since the error tolerance there differs from ordinary analytics.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
EMA data from €169/month. Free project assessment, reply within 1 business day.
Scrapeit Sp. z o.o.
10/208 Legionowa str., 15-099, Bialystok, Poland
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