Gull in Sunset. Rovinj, Croatia. 
pCEL-X Overview and Unbound-Drug Brain Exposure (PowerPoint slides)
Examples of pCEL-X type application in papers 58, 62, 68-70, 72-83, 85, 87, 89, 91, 92, 95, 98-101, 103-106 in the Publications page.
pCEL-XTM v4.0 is a computer program (launched in 2006) which can be used to model the various factors controlling transport of drug-like molecules across biological membranes (cell-based or artificial) in permeability measurement. Newer features include (a) the prediction of unbound-drug exposure in the brain using the Kalvass-Maurer-Pollack (2007) Brain Penetration Classification (BPC) scheme, and (b) the prediction of human intestinal permeability (based on Lennernäs-Amidon Peff measurements). The factors controlling transport which can be modeled include:
- passive (uncharged molecule)
- passive (charged molecule)
- paracellular (Renkin sieving function; electrostatic potential model)
- aqueous boundary layer (ABL, four models)
- carrier-mediated (model for acids, e.g., salicylic acid, indomethacin)
- active uptake (simple additive)
- efflux (simple subtractive)
There are two major, somewhat independent, sides to pCEL-X:
PREDICTION of BBB, Caco-2/MDCK, and PAMPA PERMEABILITY from 2-D STRUCTURE
Internal databases of Caco-2/MDCK, PAMPA-BBB, and Double-SinkTM PAMPA-GIT measurements are used to calculate permeability coefficients as a function of pH, using 2-D structural information (sdf format) and some in silico descriptors based on Abraham's LFER model. The simulation part of pCEL-X is useful for scrutinizing results reported in the publications, for planning optimal assay conditions, for testing new ideas concerning the mechanisms of transport, and for predicting transport properties of molecules not yet synthesized.
TRANSPORT MODEL REFINEMENT BASED on MEASURED BBB, Caco-2/MDCK, or PAMPA DATA
Measured permeability vs. pH data (BBB, Caco-2/MDCK, or PAMPA) can be processed by pCEL-X to determine mechanisms of transport likely to be indicated by the test compounds. Weighted nonlinear regression analysis is at the core of the program. In the case of cellular models, methods to separate active from passive components of transport have been tested (Avdeef, A., Artursson, P., Neuhoff, S., Lazarova, L., Gråsjö, J., Tavelin, S., 2005. Caco-2 Permeability of Weakly Basic Drugs Predicted with the Double-Sink PAMPA pKaflux Method. Eur. J. Pharm. Sci., 24, 333-349).
pCEL-XTM is a trademark of in-ADME Research. Double-SinkTM is a trademark of pION INC.