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Table 2 Predictive physicochemical profile of vincristine

From: Evaluation of the anticancer potential of CD44 targeted vincristine nanoformulation in prostate cancer xenograft model: a multi-dynamic approach for advanced pharmacokinetic evaluation

Parameters

Predictive value

Explanation

MlogP

1.036009

Moriguchi estimation of log P. RMSE/MAE = 0.93/0.70

Permeation cornea

124.5494

Permeability through the rabbit cornea (cm/s × 107). RMSE/MAE = 0.40/0.32 log units

S + logP

3.300752

Simulations Plus model of log P. RMSE/MAE = 0.30/0.23

S + Acidic_pKa

11.39

Predicted macroscopic pKa that appear to be dominated by acidic functional groups. RMSE/MAE = 0.57/0.41

S + Basic pKa

7.69; 6.37

Predicted macroscopic pKa that appear to be dominated by basic functional groups. RMSE/MAE = 0.57/0.41

Solution factor

871.3152

Universal salt solubility factor based on S + Sw model

Vd

5.856062 L/Kg

Volume of distribution (L/kg) in human at steady state. RMSE/MAE = 0.40/0.30 log units (2D and 3D)

Diffusion coefficient

0.421147

Hayduk–Laudie infinite dilution diffusion coefficient (cm^2/s × 10^5) of nonelectrolytes in water

S + MDCK-LE permeability assay

Low

Apparent MDCK Transwell permeability (cm/s × 107). RMSE/MAE = 0.47/0.48 (2D and 3D) log units

S + logD

2.80345

Simulations Plus model of log P. RMSE/MAE = 0.30/0.23

BBB filter

Low (97%)

Predicts whether or not a compound can penetrate the blood brain barrier. Overall accuracy = 92%