This study evaluates the potential of immobilized artificial membrane (IAM) chromatography, in combination with other physicochemical descriptors for high-throughput absorption profiling during lead optimization. An IAM chromatographic method was developed and validated. Absorption profiles of 32 structurally diverse compounds (acidic, basic, neutral and amphoteric) were then evaluated based on their IAM retention factor (log k'IAM), molecular weight (MW), calculated log P (C log P), polar surface area (PSA), hydrogen bonding capacity (HBD and HBA) and calculated Caco-2 permeability (QPCaco). Using regression and stepwise regression analysis, experimental Caco-2 permeability was correlated against log k'IAM and a combination of various physicochemical variables for quantitative structural-permeability relationship (QSPR) study. For the 32 structurally diverse compounds, log k'IAM correlated poorly with Caco-2 permeability values (R2 = 0.227). Stepwise regression analysis confirmed that Clog, PSA, HBD and HBA parameters are not statistically significant and can be eliminated. Correlation between Caco-2 cell uptake and log k'IAM was enhanced when molecular size factor (MW) was included (R2 = 0.555). The exclusion of 11 compounds (paracellularly and actively transported, Pgp substrates and blocker, and molecules with MW lesser than 200 and greater than 800) improved the correlation between Caco-2 permeability, IAM and MW factors to R2 value of 0.84. The results showed that IAM chromatography can only profile the passive absorption of drug molecules. Finally, it was confirmed in this study that the IAM model can accurately identify the Caco-2 permeability of nontransported Pgp substrates, such as verapamil and ketoconazole, through passive permeation because of their high permeability. IAM chromatography, combined with molecular size factor (MW), is useful for elucidating biopartitioning mechanism of drugs.