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Machine Learning and Mass Spectrometry for Structural Elucidation of Novel Toxic Chemicals

CORDIS · observation · Publication date unknown

Machine Learning and Mass Spectrometry for Structural Elucidation of Novel Toxic Chemicals Nearly half a million known chemicals have been deemed relevant for exposure studies and an even larger number of their transformation products are likely to co-occur in the environment. This mind-blowing number of possible chemical structures makes it impossible to in-silico generate all these structures, let alone synthesise and analytically confirm them, thereby limiting the discovery of novel chemicals. Today, the structural elucidation of chemicals detected with high resolution mass spectrometry relies on databases and machine learning models trained on the known chemical space. Both are fundamentally ill-suited for discovering novel chemical structures. As a result, only a few percent of the toxic activity of the environmental samples is explained by the currently known and monitored chemical

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award

status

SIGNED

region

EU

value

1867187

unit

EUR