Sjoerd van Hagen

Project Manager / Big Data Architect

@TheHyveNL

The world of clinical trials can be overwhelming. More and more clinical trials are conducted, and each of them is getting more complex. Multi-arm trials have several advantages over traditional two arm trials. Testing multiple treatments at once:

  • increases your chance of finding an effective treatment
  • reduces your costs
  • makes it easier to recruit patients

This comes at a cost, however: describing a multi-arm clinical trial is more difficult than a classical two-arm trial. Therefore, when, as an oncologist, you need to find the right trial for your patient, such complex trials are more difficult to search through.

In addition, we collect more and more data for each patient, and we would like to use all data to select patients that have a higher probability of responding to a treatment. For instance, if we have a treatment targeting a BRAF V600E mutation, it does not make sense to include patients without this mutation.

So we have patients that have a more complex description and trials that have a more complex description than before. How do we deal with this?

Our joint answer with Dana Farber Cancer Institute (DFCI) is MatchMiner. MatchMiner is the first fully open source platform for algorithmically matching clinical trials to the patient information. The two main use cases that are covered by the system are described below.

A patient walks into a cancer center and sadly there is no cure available. The oncologist suggests enlisting in a trial, so the question is: which trial would give this patient the best chance of survival? MatchMiner will allow the oncologist to find all clinical trials the patient is eligible for based on both the genetic profile and the clinical data of the patient, simply by adding the patient’s data into the MatchMiner application.

The other main use case is when a clinical trial investigator would like to start a new clinical trial or wants to add new patients to an ongoing trial. To find all patients eligible for a trial, he only needs to describe the trial in a structured way using the Clinical Trial Markup Language (CTML) that is developed for MatchMiner by DFCI.

If you want to know more about MatchMiner or have any questions, please have a look at this review or contact us!

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Sjoerd van Hagen

Project Manager / Big Data Architect

@TheHyveNL