Table 1 The details of the previous QSAR/QSAAR models employed as case studies for the present work

Case study 1

Pesticides

MLR technique

[20]

 pLC₅₀ (O. mykiss) = 0.27 + 0.17 Log P + 0.67 pEC₅₀ (D. magna)

 n_T = 254; R² = 0.813; RMSE_C = 0.65; F = 545.77; p < 0.00

 n_V = 64; RMSE_P = 0.68; Q²_F1 = 0.817; Q²_F2 = 0.817; Q²_F3 = 0. 794; CCC = 0.894

Case study 2

Pesticides

MLR technique

[20]

 pLC₅₀ (L. macrochirus) = 0.09 + 0.18 Log P + 0.67 pEC₅₀ (D. magna)

 n_T = 235; R² = 0.831; RMSE_C = 0.65; F = 570.92; p < 0.00

 n_V = 59; RMSE_P = 0.68; Q²_F1 = 0.831; Q²_F2 = 0.831; Q²_F3 = 0. 818; CCC = 0.900

Case study 3

Pharmaceuticals and personal care products (PPCPs)

MLR technique

[21]

 pEC₅₀ (O. mykiss) = 1.31 + 1.24 pEC₅₀ (D. magna) – 0.36 GATS1e

 n_T = 35; R² = 0.91; RMSE_C = 0.45; Q²_LOO = 0.89;

 n_V = 15; Q²_Ext = 0.77–0.77; RMSE_P = 0.71; CCC = 0.89

Case study 4

Substituted phenols

LR technique

[22]

 pT (C. vulgaris) = 0.72 pT (T. pyriformis) + 0.25

 n_T = 31; R² = 0.75; Q²_LOO = 0.72; RMSE_C = 0.32

 n_V = 10; Q²_Ext = 0.81–0.82; RMSE_P = 0.28

Case study 5

Organic chemicals

kNN technique

[23]

 pLC₅₀ (P. promelas) = f(MLOGP; CIC0; SM1_Dz(Z); GATS1i; NdsCH; NdssC)

 n_T = 726; k = 6; R² = 0.62; RMSE_C = 0.879; Q²_CV = 0.61; RMSE_CV = 0.878;

 n_V = 182; Q²_EXT = 0.61; RMSE_EXT = 0.888