Learn how
to obtain high-quality and robust
AI-enabled real world evidence.

Get daily advice about the use of AI in clinical research:

By the way, if you register you will receive our masterclass about AI in healthcare:

  • 54 min of content.
  • An astonishing simple explanation about what AI and machine learning are.
  • Specific and tangible examples of its application in healthcare.
  • The exact steps to follow in order to start a project in AI.
  • How to critically read the projects of others.
  • A tip to distinguish bullshit from truth when buying AI.
  • A gift: a compelling newsletter which you subscribe to in order to be continually updated, providing you with a quick 5 minute overview just once a week. 
  • Another gift: the best more extensive course to follow providing you with an insightful deeper dive into AI applications in healthcare.

What we do:

  • Sometimes the simplest way can also be the best one.
  • And the best way is not a cut of a database, nor a group of preselected variables, nor a certain number of patients. It’s not that. And neither a very costly registry.
  • The best way we can imagine is to retrieve the actual complete information about what is happening at the points of care.
  • It’s having access to the complete medical records information.

Every single patient. Every single variable.
The most realistic data source possible.

Every single patient. Every single variable.
The most realistic data source possible.

  • In order to get this, you basically need:
    • A combined team of data scientists and clinicians with experience in research (in our case, lead by oncologists).
    • A system able to retrieve information from any healthcare provider (as long as they have electronic medical records -EMR-, paper doesn’t work).
    • Natural Language Processing, because 80% of the variables and outcomes are going to be in the clinical narratives’ free text.

This system is exactly what we created.

This system is exactly what we created.

And how, is in practice, getting the information through this methodology better?


  • The key is in our team helping researchers selecting which fragments of meaningful data in order to satisfy the objectives of the investigation.
  • In fact, because we had to signify how much deeper we get into data compared to anyone else, thanks to AI (true AI, not buzzword AI), we called the result of this methodology Deep Real World Evidence.
  • As you have probably suffered in the past, current databases exist to collect clinical data, but with considerable gaps due to recording limitations in the current methods.
  • Deep Real World Evidence from EMR offers a much (not a bit but a much) greater insight into the routine clinical care of patients throughout all stages of the disease.
  • Combining free text with other data sources (e.g. laboratory data, pathology, genomics, etc.), an insilico registry gets generated to describe the patient population with the defined disease, their associated clinical conditions and treatments, and develop predictive models.

Deep data layers analysis:

Deep data layers analysis:

If we do our job well, there is no need for:

  • Observational studies.
  • Traditional registries.
  • Classical disease databases.

Drug discovery: beyond EMR and into genomics.

Once we have facilitated the most difficult part, which is extracting variables from free text (clinical characteristics, comorbidities, signs and symptoms, adverse events or outcomes), we can also combine all this unstructured information with other structured data layers (genomics, transcriptomics, proteomics and imaging) which can be sourced both from our worldwide network of hospitals and from clinical trial databases.

Savana works with its premium partners in order to offer a combined proposal:

You need to know that we did this before… many times


We invested millions and years in developing a methodology by which we can infer the variables from the EMR, keeping quality and controlling bias. The consequence is a methodology which results are replicable, thus generalizable.

We collaborate with a network of 200 hospitals across Western Europe and the Americas.

And yes, we are absolutely the only ones who do this at multilingual level!

And yes, we are absolutely the only ones who do this at multilingual level!

Learn how
to obtain high-quality and robust
AI-enabled real world evidence.

Get daily advice about the use of AI in clinical research:

I don't want to subscribe, I want to read the blog

By the way, if you register you will receive our masterclass about AI in healthcare:

  • 54 min of content.
  • An astonishing simple explanation about what AI and machine learning are.
  • Specific and tangible examples of its application in healthcare.
  • The exact steps to follow in order to start a project in AI.
  • How to critically read the projects of others.
  • A tip to distinguish bullshit from truth when buying AI.
  • A gift: a compelling newsletter which you subscribe to in order to be continually updated, providing you with a quick 5 minute overview just once a week. 
  • Another gift: the best more extensive course to follow providing you with an insightful deeper dive into AI applications in healthcare.

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