Expert systems are a rational integration of several models that generally aim to exploit their advantages and overcome their drawbacks. This work is founded on our previously published Quantitative Structure-Activity Relationship (QSAR) classification scheme, which detects compounds whose Bioconcentration Factor (BCF) is (1) well predicted by the octanol-water partition coefficient (KOW), (2) underestimated by KOW or (3) overestimated by KOW. The classification scheme served as the starting point to identify and combine the best BCF model for each class among three VEGA models and one KOW-based equation. The rationalized model integration showed stability and surprising performance on unknown data when compared with benchmark BCF models. Model simplicity, transparency and mechanistic interpretation were fostered in order to allow for its application and acceptance within the REACH framework.

Grisoni, F., Consonni, V., Vighi, M., Villa, S., Todeschini, R. (2016). Expert QSAR system for predicting the bioconcentration factor under the REACH regulation. ENVIRONMENTAL RESEARCH, 148, 507-512 [10.1016/j.envres.2016.04.032].

Expert QSAR system for predicting the bioconcentration factor under the REACH regulation

GRISONI, FRANCESCA
Primo
;
CONSONNI, VIVIANA
Secondo
;
VIGHI, MARCO;Villa, S
Penultimo
;
TODESCHINI, ROBERTO
Ultimo
2016

Abstract

Expert systems are a rational integration of several models that generally aim to exploit their advantages and overcome their drawbacks. This work is founded on our previously published Quantitative Structure-Activity Relationship (QSAR) classification scheme, which detects compounds whose Bioconcentration Factor (BCF) is (1) well predicted by the octanol-water partition coefficient (KOW), (2) underestimated by KOW or (3) overestimated by KOW. The classification scheme served as the starting point to identify and combine the best BCF model for each class among three VEGA models and one KOW-based equation. The rationalized model integration showed stability and surprising performance on unknown data when compared with benchmark BCF models. Model simplicity, transparency and mechanistic interpretation were fostered in order to allow for its application and acceptance within the REACH framework.
Articolo in rivista - Articolo scientifico
BCF; Bioaccumulation; Expert system; QSAR; TGD; VEGA;
BCF; Bioaccumulation; Expert system; QSAR; TGD; VEGA;
BCF; Bioaccumulation; Expert system; QSAR; TGD; VEGA
English
2016
148
507
512
none
Grisoni, F., Consonni, V., Vighi, M., Villa, S., Todeschini, R. (2016). Expert QSAR system for predicting the bioconcentration factor under the REACH regulation. ENVIRONMENTAL RESEARCH, 148, 507-512 [10.1016/j.envres.2016.04.032].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/116951
Citazioni
  • Scopus 22
  • ???jsp.display-item.citation.isi??? 20
Social impact