Physiologically based pharmacokinetic modelling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions.

By T. Rodgers, M. Rowland. Journal of Pharmacy and Science, 2006

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PBPK models for the prediction of in vivo performance of oral dosage forms. (2014, methodology): “…tissue–plasma-partition coefficients using five different approaches (PK-Sim standard (PK-Sim , 2012), Rodgers and Rowland (Rodgers et al., 2005a,b; Rodgers and Rowland, 2006, 2007), Schmitt (Schmitt, 2008), Poulin and Theil (Poulin et al., 2001; Poulin and Theil, 2000, 2002a,b), and…”
Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model (2016, background): “to electrostatic interactions at physiological pH.(45,46) These include binding of ionized and unionized drugs to acidic phospholipids and neutral lipids, respectively.”
Coexistence of passive and carrier-mediated processes in drug transport (2010, background): “6), lansoprazole (85), lincomycin (28), mannitol (16–26), metaproterenol (44), metformin (86), methotrexate (20), methylprednisolone (82), metolazone (64), metoprolol (95), nadolol (35–57), naltrexone (96), naproxen (99–100), nicotinic acid (88), norfloxacin (71), olsalazine (2), oxacillin (30–35), ”
A framework for assessing inter-individual variability in pharmacokinetics using virtual human populations and integrating general knowledge of physical chemistry, biology, anatomy, physiology and genetics: A tale of 'bottom-up' vs 'top-down' recognition of covariates. (2009, methodology): “105,106,142) give the ability to separate drug attributes from those of the system and to incorporate times have removed this restriction.”