Abstract
Trade in high-value-added toxins for therapeutic and biological use is expanding. These toxins are generally derived from microalgae belonging to the dinoflagellate family. Due to the difficulties to grow these sensitive planktonic species and to the complexity of methods used to synthesize these molecules, which are generally complex chemical structures, biotoxin manufacturers called on artificial intelligence technologies. Manufacturing processes have been greatly improved through the development of specific learning neural networks, applied to each phases of biotoxin production: photo-bioreactors operating at optimal yied; new chemical synthesis research processes; toxin biosynthetic research pathways offering short-cut possibilities.
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Acknowledgements
Thanks to Planktovie S.A for helpful discussions. Aix Marseille University (France) and A. Le Bivic and L. Kodjabachian, IBDM–CNRS Marseille directors, are greatly acknowledged for facilities offered.
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Kraus, Jl. Artificial intelligence applied to the production of high-added-value dinoflagellates toxins. AI & Soc 35, 851–855 (2020). https://doi.org/10.1007/s00146-020-00959-3
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DOI: https://doi.org/10.1007/s00146-020-00959-3