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Anaxomics' TPMS technology enables the analysis of real world data with the aim of extracting novel conclusions and providing the molecular mechanisms underlying the obtained results

Anaxomics brings the power of systems biology to Real World Evidence studies.

Real-world data are a valuable source of information about are data related to medical issues. With the increasing amount of available data, the key for successful studies is not only to find the evidence, but to unveil the mechanisms explaining the results.

What does Anaxomics offer?

ANAXOMICS’ Real World Data Studies offer valuable evidence and insights into the molecular mechanisms behind obtained results. In order to identify the best classifiers, Anaxomics follows a Data Science protocol, which explores different algorithms to select those fitting better with the training data. This includes analyzing data through a selected strategy combining Association rule learning process with different types of Neural Networks, enabling to identify hidden relationships that are not detectable by using the classical and most commonly used lineal classifiers. Potential markers that can discriminate studied cohorts are then identified and the relationships are measured in terms of accuracy and of generalization capability using techniques like k- Fold Cross Validation to confirm the candidates with the maximum statistical robustness. This process results in a list of classifiers and combinations of classifiers. Last, but not least, the TPMS technology is applied to gain insight into mechanistic understanding of the obtained results.

Anaxomics’ proprietary technology, Therapeutic Performance Mapping System (TPMS), integrates biological, pharmaceutical and medical data into systems biology models can go a step further. Not only we can propose the evidence, our mathematical models can uncover molecular bases behind it.

Real World Evidence


To learn more about Anaxomics strategy for RWE, here you can find a full description of our approach. doi: 10.1002/acr.25048. Epub 2022 Dec 9.

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