Table 6.

Prediction of pICT₅₀ values of MLR models (equations 1 to 4) applied to the training set, experimental pICT₅₀ values, mean error and maximum and minimum values

Training set		Mono-parametric				Bi-parametric			Tri-parametric		Tetra-parametric
		Eq1		Δ1		Eq2		Δ2	Eq3	Δ3	Eq4	Δ4	pICT50
1 (Caffeine)		0.5766		-0.2578		0.7262		-0.4074	0.4432	-0.1244	0.6297	-0.3109	0.3188
2		0.5766		-0.2298		0.6572		-0.3104	0.3719	-0.0251	0.4043	-0.0575	0.3468
3		1.3737		0.6263		1.4393		0.5607	1.4357	0.5643	1.5200	0.4800	2.0000
4		1.3737		0.3253		1.4393		0.2597	1.3354	0.3636	1.3954	0.3036	1.6990
5		1.5730		-0.0501		1.6290		-0.1061	1.6014	-0.0785	1.6670	-0.1441	1.5229
6		1.5730		-0.0501		1.6060		-0.0831	1.4721	0.0508	1.5259	-0.0030	1.5229
7		1.7722		-0.2493		1.8188		-0.2959	1.7670	-0.2441	1.8140	-0.2911	1.5229
8		1.3737		0.0242		1.4163		-0.0184	1.3065	0.0914	1.3790	0.0189	1.3979
9		0.9752		0.3258		1.0597		0.2413	1.1043	0.1967	1.2260	0.0750	1.3010
10		0.9752		0.3258		1.0597		0.2413	1.1043	0.1967	1.2260	0.0750	1.3010
11		1.1744		0.1266		1.0885		0.2125	1.1408	0.1602	1.0561	0.2449	1.3010
12		1.1744		0.1266		1.1115		0.1895	1.2700	0.0310	1.1971	0.1039	1.3010
13		1.3737		-0.0727		1.3013		-0.0003	1.2352	0.0658	1.0949	0.2061	1.3010
14		1.1744		-0.1744		1.1115		-0.1115	1.1697	-0.1697	1.0725	-0.0725	1.0000
15		0.7759		0.1449		0.7320		0.1888	0.9386	-0.0178	0.9032	0.0176	0.9208
16		0.9752		-0.0891		0.9217		-0.0356	1.1043	-0.2182	1.0501	-0.1640	0.8861
17		1.1744		-0.2883		1.0885		-0.2024	1.1408	-0.2547	1.0561	-0.1700	0.8861
18		1.3737		-0.5498		1.3013		-0.4774	1.4357	-0.6118	1.3441	-0.5202	0.8239
19	0.7759		0.0200		0.7090		0.0869		0.7091	0.0868	0.6375	0.1584	0.7959
20	0.7759		-0.0769		0.7090		-0.0100		0.7091	-0.0101	0.6375	0.0615	0.6990
21	0.5766		0.0432		0.5422		0.0776		0.6727	-0.0529	0.6315	-0.0117	0.6198
*Mean error			0.1989				0.1960			0.1704		0.1662
*Max			0.6263				0.5607			0.6118		0.4800
*Min			0.0200				0.0003			0.0101		0.0030

* The module of the error values was considered for this determination.