Each channel was calibrated with a standard curve before the dissolution assay. Estimated Sapp was used together with chromophore strength to select dip-probe path length. Compounds with high solubility and/or strong chromophores required

the use of a short-path length while a longer one was used for compounds with weak chromophore and/or low Sapp. Before the experiments, an approximately twofold excess of drug powder compared to the estimated Sapp was weighed into the vials. Preheated media (15 mL, 37 °C) were added to the vials at the start of the experiment and the temperature was held constant at 37 ± 0.5 °C. The vials were sealed using parafilm to avoid evaporation and stirred at 100 rpm using magnetic stirrers. The experiment was terminated after a stable plateau representing the Sapp was reached but not before the

2 h #inhibitors randurls[1|1|,|CHEM1|]# period recommended by the FDA for ethanol sensitivity testing. Interference from solid particles of the excess powder in the vials was avoided by using the second derivative signal from collected absorbance spectra. The resulting dissolution profiles were analyzed with GraphPad Prism (GraphPad Software, CA) and a nonlinear, two-phase association equation was used to obtain the Sapp-value from the plateau. The results are presented as mean and standard deviations (n = 3). Lipid solubilization and the ethanol effect on Sapp at pH 2.5 were calculated as a fold increase (the ratio) of Sapp in FaSSGF or NaClpH2.520%Ethanol over NaClpH2.5. Ethanol PD-0332991 chemical structure effects in FaSSGF were calculated as the ratio of Sapp in FaSSGF20%Ethanol over FaSSGF. Standard errors (SE) for the mean fold-increase (FI) ratios were calculated according to SEFI=σA2A2+σB2B2where A and B are mean Sapp in two media and σA and σB represent Sitaxentan the corresponding standard deviation. In silico simulations were performed with the absorption simulation software GI-Sim that has been thoroughly described elsewhere ( Sjögren et al., 2013). Briefly, GI-Sim deploys a compartmental physiological structure of the underlying intestinal physiology with nine gastrointestinal (GI)

compartments coupled in series: the stomach (1), the small intestine (2–7) and the colon (8–9) ( Yu and Amidon, 1998, Yu and Amidon, 1999 and Yu et al., 1996). To describe the plasma concentration–time profile, the GI model is linked to a pharmacokinetic model with up to three compartments. Physiological parameters for the GI compartments previously described were used, except that the gastric pH was somewhat elevated and set to 2.5 in analogy with in vitro solubility measurements ( Sjögren et al., 2013). In GI-Sim, undissolved particles and dissolved molecules flow from one GI compartment into the next. The particles may either dissolve or grow; dissolved material may partition into the bile salt micelles or is absorbed through the intestinal wall. Intestinal solubility, represented by previously reported Sapp in phosphate buffer pH 6.5 and FaSSIF ( Fagerberg et al., 2012 and Fagerberg et al.