Pesticides groundwater modelling relies on input data characterised by a high intrinsic variability: Is the resulting risk for groundwater credible?

In the framework of Regulation (EC) 1107/2009, concerning the placing of plant protection products (PPP) on the market, FOCUS models are used to predict active substances concentration in groundwater. The predicted environmental concentration in groundwater (PECGW) are influenced by active substance specific parameters, namely DT50, KOM and Freundlich coefficient (1/n), whose minimal variation in certain combinations of intervals significantly affects PECGW output. Considering that minimal variation are intrinsic in all laboratory studies, this approach may lead to not acceptable variations in the results for regulatory purposes. In the present article, PECGW were calculated for all maize crop scenarios, using 808 dummy active substances with different combinations of DT50, KOM and 1/n values, in order to quantify the influence of each single parameter on the final result of PEARL and PELMO models. The results obtained were used to create a classification system for the input parameters KOM and DT50 in order to minimise the input uncertainty effects. Even if this approach is scientifically viable yet, due to its conservative nature, it cannot be considered suitable in the regulatory framework, where acceptability of an active substance is strictly related to the limit value of 0.1 µg/L. Nevertheless, this classification system could represent an important screening or preliminary assessment to plan pesticide monitoring programmes. Based on the results of this analysis, it is believed that the assessment of pesticide leaching into groundwater should be revised to take into account this variability. Considering that both PEARL and PELMO FOCUS models deal with interaction between a chemical and a complex system like soil and weather, the selection of input data cannot pretend to rely on single specific number. Considering that intrinsic uncertainty cannot be eliminated from experimental work, a revision of the criteria used to identify the proper input data and a thorough revision of the actual groundwater modelling is recommended.

Antiproliferative Pt(IV) complexes: synthesis, biological activity, and quantitative structure-activity relationship modeling.

Several Pt(IV) complexes of the general formula [Pt(L)2(L')2(L'')2] [axial ligands L are Cl-, RCOO-, or OH-; equatorial ligands L' are two am(m)ine or one diamine; and equatorial ligands L'' are Cl- or glycolato] were rationally designed and synthesized in the attempt to develop a predictive quantitative structure-activity relationship (QSAR) model. Numerous theoretical molecular descriptors were used alongside physicochemical data (i.e., reduction peak potential, Ep, and partition coefficient, log Po/w) to obtain a validated QSAR between in vitro cytotoxicity (half maximal inhibitory concentrations, IC50, on A2780 ovarian and HCT116 colon carcinoma cell lines) and some features of Pt(IV) complexes. In the resulting best models, a lipophilic descriptor (log Po/w or the number of secondary sp3 carbon atoms) plus an electronic descriptor (Ep, the number of oxygen atoms, or the topological polar surface area expressed as the N,O polar contribution) is necessary for modeling, supporting the general finding that the biological behavior of Pt(IV) complexes can be rationalized on the basis of their cellular uptake, the Pt(IV)-->Pt(II) reduction, and the structure of the corresponding Pt(II) metabolites. Novel compounds were synthesized on the basis of their predicted cytotoxicity in the preliminary QSAR model, and were experimentally tested. A final QSAR model, based solely on theoretical molecular descriptors to ensure its general applicability, is proposed.