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  3. [2023-10-09] A high-quality prediction computer tool is developed within Mistra SafeChem
News | 2023-10-09
Two screenshots of a computer with the logo for Mistra SafeChem.

Graphical user interface of the software (pilot version, might be changed in the formal version).

A high-quality prediction computer tool is developed within Mistra SafeChem

Mistra SafeChem researchers Ulf Norinder, Swapnil Chavan and Ziye Zheng have developed three sets of computational models which can identify hazardous compounds.

In 2021, a news article External link. from the Mistra SafeChem programme described the ambition to build a high-quality prediction in silico tool for identifying compounds that may have hazardous properties, e.g. toxicity, persistence, endocrine activity, and organ toxicity.

Another news article External link., published this year, described the development of a similar tool more specifically tailored for the Cytiva corporation.

Both these efforts contribute to the ambition of building a high-quality prediction computer tool.

Started with one set of models

In early 2021 only one set of models primarily existed for all of the application areas including targets such as endocrine (hormone) disruptors, carcinogenicity, mutagenicity as well as biodegradability.

These models were developed using traditional machine learning and chemical compound characterization (descriptor) methods such as Random Forest and physicochemical descriptors, respectively.

Deep Learning methods are used

Today three sets of models exist, developed within Mistra SafeChem by Swapnil Chavan, Unit of Chemical and Pharmaceutical Toxicology at RISE, Ulf Norinder, Dept of Computer and Systems Sciences at Stockholm University, and Ziye Zheng, Cytiva.

These models span both the traditional machine learning methods and state-of-the-art methods from the rapidly developing artificial intelligence field called Deep Learning. In addition, they contain procedures for defining the uncertainty associated with each prediction, making them more useful for decision-making by the end-users.

A new graphical user interface

– To integrate the prediction outcomes from all three types of models into an overarching decision along with estimated uncertainty in those predictions, we have developed a standalone graphical user interface application, Ulf Norinder explains.

The constructed software will be disseminated to all Mistra SafeChem partners along with a guidance document. Workshops will also be held to train and educate users of this software.

More to read in scientific journals