Realtime Oncology
Treatment Calculator™

For Physicians

A knowledge engine to support every oncologist's daily work

Rule-based artificial intelligence is the next logical step in precision oncology to translate the results of molecular profiling, functional annotations and knowledge bases into clinical decisions.

Previously only 10-20 new drugs were approved in oncology in a decade. This has changed. Last year alone 14 novel targeted and immune therapies have been registered by the FDA and there are thousands in clinical trials. Who can keep up with this pace of development?

We are here to provide you relevance ordered compound recommendations based even on a combination of molecular tests, of any tests.

AEL to the rescue

Aggregated Evidence Level (AEL) (patent pending) is the output of the Realtime Oncology algorithm and represents a scoring system to aggregate and rank molecular evidence in precision oncology. AEL represents the number, scientific impact and clinical relevance of evidence relations in the system, connecting tumor types, molecular alterations, targets  and compounds. Individual evidence relation scores are normalized and weighted according to the degree of similarity of the parameters to the parameters of the given patient case. Compound AELs are obtained by aggregating all relevant associations (and AELs) between the specific compound, tumor type, drivers and targets.

Using AELs we can order molecular alterations, targets and compounds in an objective, reproducible way.

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