@article{Silva_Duque_Davies_Löbenberg_Ferraz_2018, title={Application of in Silico Tools in Clinical Practice using Ketoconazole as a Model Drug}, volume={21}, url={https://journals.library.ualberta.ca/jpps/index.php/JPPS/article/view/30227}, DOI={10.18433/jpps30227}, abstractNote={Hypochlorhydria is a condition where the production of hydrochloric acid in the stomach is decreased. As a result, the intragastric pH is elevated. This condition can be due to a series of causes, such as disease (gastric mucosal infection caused by <em>Helicobacter pylori</em> and is prominent in AIDS patients), ethnicity, age and also the use of antisecretory agents. This may significantly impact the absorption of other drugs that have pH-dependent solubility, such as ketoconazole, a weak base. Within this context, the purpose of this study was to demonstrate how GastroPlus<sup>TM</sup> – a physiological based software program- can be used to predict clinical pharmacokinetics of ketoconazole in a normal physiological state vs. elevated gastric pH. A simple physiologically based pharmacokinetic model was built and validated to explore the impact that different physiologic conditions in the stomach (hypochlorhydria, drug administered with water and Coca Cola®) had on ketoconazole’s bioavailability. The developed model was able to accurately predict the impact of increased pH and beverage co-administration on dissolution and absorption of the drug, and confirmed that complete gastric dissolution is essential. Particle size only mattered in hypochlorhydric conditions due to the incomplete gastric dissolution, as its absorption would depend on intestinal dissolution, which corroborates with previous studies. Therefore, in silico approaches are a potential tool to assess a pharmaceutical product’s performance and efficacy under different physiological and pathophysiological states supporting the assessment of different dosing strategies in clinical practice.}, number={1s}, journal={Journal of Pharmacy & Pharmaceutical Sciences}, author={Silva, Daniela Amaral and Duque, Marcelo Dutra and Davies, Neal M and Löbenberg, Raimar and Ferraz, Humberto Gomes}, year={2018}, month={Oct.}, pages={242s-253s} }