ongoing

ZeBYTE - Platform to predict the effect of drugs based on the use of zebrafish and artificial intelligence

ZeBYTE aims at using artificial intelligence technologies along the whole target discovery process.

Start – End dates: 01/01/2022 – 31/06/2023

Project reference: 2020/0720/00099157

Total budget: 382,032€

Co-financed by: Red.es & Ministerio de asuntos económicos y transformación digital, Spain

This project has received funding from Red.es with co-funding from FEDER “Fondo Europeo de Desarrollo Regional” within the “Plan Acelera PYME” programme.

Summary:

The development of new drugs is a long and complex process. As such, it implies a high amount of investment and fails more often than not. In this context, the discovery of appropriate therapeutic targets stands as one of the most important aspects to accelerate drug development and increase its chances of success. To tackle this issue, and based on the high biological translatability of the zebrafish model, ZeClinics will develop an innovative platform – ZeBYTE – that combines data extracted from relevant zebrafish disease models with artificial intelligence tools. As such, ZeBYTE aims at using artificial intelligence technologies along the whole target discovery process. First, we will use Deep learning algorithms to automate and extract more meaningful information from experimental outputs. Second, we will build heterogenous networks, based on our own experimental data – phenotypic and omic –and other data sources – clinical, interactome, etc. Third, we will exploit such a network, by using Deep and Machine learning tools, to extract a list of potential therapeutic targets for a selected indication. And fourth, we will validate the best positioned targets, through the exploitation of experimental technologies and disease models already validated in our wet lab. To address the capabilities and advantages of this strategy, we will make a proof of concept on Parkinson’s Disease, a devastating disorder from which we have validated several disease models. The present project is part of Pharma 4.0 for the digital transformation of the pharmacological industry, which pretends to implement new digital solutions to increase the efficiency, quality, and productivity in every stage of the value chain.

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