siRFINDER, algorithms to identify target molecules

Grupo AIA has developed siRFINDER, a Machine Learning based software of siRNA molecules which has been successfully implanted by Sylentis, subsidiary of group Pharmarmar.

This software, co-financed by CDTI, is aimed at strengthening drug development based on RNA interference therapy. This tool developed by different Machine Learning algorithms is designed to generate thousands of specific compounds for disease treatment taking advantage of the ARN Interference technology (ARNi). This biomolecular technology enables silencing genes responsible for producing protein associated to specific diseases. Through this ARN interference technology, it is possible to prevent genes from developing as disease.

In a first phase of the project, the algorithms were performed for the selection of the best candidates in terms of their thermodynamic properties, possible body immune response, possible negative effects on the genes and possible modifications or mutations of the target gene. Consequently, we would know which molecules from all the siRNA molecules are the most effective for specific pathologies.

Reducing the number of molecules for further research and development, the time required is reduced by half, which enables Sylentis to develop innovative drugs in a shorter time and lower cost for the pharmaceutical company.

Among the main benefits for Sylentis is that siRFINDER maintains confidentiality of the targets and flow of information during the whole process, because the algorithms collect, clean and reinterpret the data generated by Sylentis describing the expected metrics the siRNA candidates must meet.

Grupo AIA and Sylentis will continue with the following phase of the siRFINDER Project which consists on developing an autolearning system designed to adapt it to the type of tissue it is addressed to.


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