Background

Syngenta is seeking organisations with capabilities, tools, data and/or platforms that enable the fluorine-efficient design of new agro-chemical products.

The key goal of this effort is to generate robust, predictive models built on high quality data to understand how per- and polyfluoroalkyl substances (PFAS) can be substituted in Syngenta’s product lines and research pipeline.

Fluorination is extensively used in both agrochemical and drug design because of the unique ability of fluorine atoms to modulate the biokinetic profile of bioactive molecules. Synthetic methodologies for installing fluorine into complex molecules have also become increasingly precise and affordable, facilitating the wide adoption of fluorinated groups to improve in vivo performance.

However, emerging regulatory trends have led to increased scrutiny of all fluorinated compounds, regardless of their demonstrated properties. For example, a class-based ban of all non-essential PFAS has been recently proposed in the EU, which would compromise the continued use of many fluorinated bioactive molecules.

Syngenta is seeking to better understand how fluorine substituents impact a molecule’s biokinetic profile and ultimately the in vivo translation. This will help us reduce and potentially eliminate the use of per-and poly-fluorinated functional groups in new agrochemical products. To do this end, we must better understand the fluorine effect on individual physicochemical and biokinetic parameters.