Survey
* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project
GI transfer May 13 2014 Integration of the gastrointestinal transit into different in vitro models Evaluation of the gastrointestinal transit by using a non-absorbable marker GI Stomach Time Drug concentration Drug concentration Transfer Small Intestin Time Integration of the gastrointestinal transit into different in vitro models • Non-absorbable marker: – Paromomycin Sulfate: Gabbroral®: Antibiotic • Site of action: infections of the GI tract Not transported to the blood compartment (confirmed by Caco 2 experiment) Caco-2 Candidate compound to evaluate the GI transit 200 µM 150 100 50 0 Analysis: HPLC-FLUO – Derivatisation by Fluorenylmethyloxycarbonyl chloride (FMOC-Cl) to make it possible to detect Method validation Compound Mobile Phase Paromomycin Sulfate Detection Acn:H2O (87:13) FLUO Wavelength (Ex/Em) 260/315 INTRADAY 1400 Flow Rate (mL/min) 1 1200 1000 1000 µM 1300µM 500µM 600 800 1300µM µM 800 7,5 INTERDAY 1400 1200 Retention Time (minutes) 500µM 600 50µM 50µM 400 400 200 200 0 0 FaHIF FeHIF FaHGF FaHIF FeHIF FaHGF Setup Clinical Trial – 5 healthy volunteers: • Drinking 250mL of water, pre-dissolved with one tablet of Gabbroral® •A Aspirating i ti stomach t h&d duodenal d l fl fluids id Setup Clinical Trial – 4 different conditions: 1. Fasted State 2. Fed State 3. Fed State + Domperidon (Motilium®) (transit stimulating effect) 4. Fed State + Loperamide HCl (Imodium®) (transit inhibiting effect) Clinical Trial 10 pH • Results: 5 0 – Fasted State: 0 100 200 300 Time (min) Stomach Fasted State 900 1400 800 1200 paromomycin (µM) paromomycin (µM) Duodenum Fasted State 700 600 500 400 300 200 100 0 0.5 800 600 400 200 mean±SEM mean±SEM 0 1000 0 1 Time (h) Stomach Fasted State 1.5 2 0 0.5 1 Time (h) Duodenum Fasted State 1.5 2 Clinical Trial pH – Fed State: 8 6 4 2 0 0 100 200 300 Time (min) Stomach Fed State 400 800 Paromomycin (µM) Paromomycin (µM) 1000 600 400 200 Duodenum Fed State 200 mean±SEM mean±SEM 0 0 0 0.5 1 1.5 2 Time (h) Stomach Fed State 2.5 3 3.5 4 0 0.5 1 1.5 2 2.5 Time (h) Duodenum Fed State 3 3.5 4 Fed State + Domperidon pH 10 5 0 0 100 200 Time (min) Stomach Fed State+Motilium Duodenum Fed State+Motilium Paromomycin Cmax Duodenum (µM) 700 Volunteer 2 600 500 Volunteer 4 Volunteer 3 Volunteer 5 400 300 Volunteer 1 200 100 0 FED STATE FED STATE + DOMPERIDONE 300 Integration of the gastrointestinal transit into different in vitro models • Implementation to in vitro/ in silico: 1 Psachoulias et al. 2012 2 3 Tiny TIM and TIM-1 Integration of the gastrointestinal transit into different in vitro models • Implementation to in vitro/ in silico: 1 Psachoulias et al. 2012 2 3 Tiny TIM and TIM-1 Integration of the gastrointestinal transit into different in vitro models • Implementation to in vitro/ in silico: Psachoulias et al. 2012: Simulated duodenal concentration concentration-time time profiles of paromomycin, using the three-compartmental model in both the original mode (Psachoulias et al. 2012) (■) and the modified mode (Symillides et al. 2013) (---). Reference data is given by the mean (± SEM) in vivo duodenal concentration-time profile (▲). 1400 1200 Paromomycin (µM) 1 1000 800 600 400 200 0 0 0.5 1 Time (h) 1.5 2 Integration of the gastrointestinal transit into different in vitro models • Implementation to in vitro/ in silico: 1 2 3 Psachoulias et al. 2012 Tiny TIM and TIM-1 Integration of the gastrointestinal transit into different in vitro models • Implementation to in vitro/ in silico: 2 TNO Intestinal Model (TIM-1): TIM-1 fasted state experiment 1 & 2: Mean concentration-time concentration time profiles and pH profiles of the stomach (▲) and duodenum (●) compartment of TIM-1 compared with the mean concentrationtime profile of the in vivo duodenum (■) (n=3; mean ± SEM). The arrow indicates the difference between the gastric emptying time for the TIM-1 (0.55 hour) and the in vivo data (0.125 hour). Integration of the gastrointestinal transit into different in vitro models • Implementation to in vitro/ in silico: 1 2 3 Psachoulias et al. 2012 Tiny TIM and TIM-1 Integration of the gastrointestinal transit into different in vitro models • Implementation to in vitro/ in silico: Simcyp® Simulation model: Simulations of duodenal paromomycin i concentrations t ti using Simcyp® (varying gastric emptying time (GET), from 0.4 h to 0.101 h) in a “virtual population”. Mean duodenal concentrationtime profile in the fasted state in humans is also shown (mean ± SEM) (■). 1400 Paromomycin (µM)) 3 Mean HV 1200 1000 GET 0.4 h 800 600 GET 0.125 h 400 200 0 0 0.5 1 Time (h) 1.5 2 Conclusions In Vivo: o For drugs in solution, a fast transfer from stomach to small intestine (observed mean GET 0.125 h) results in a dilution of less than 1:2 in fasting conditions. o Delayed gastric emptying time in the fed state (observed mean GET 0.8 h) is not influenced by the administration of domperidone or loperamide, a transit-stimulating and d iinhibiting hibiti agent, t respectively. ti l In Vitro & In Silico: o Using the human data as reference, it was demonstrated that current in vitro and in silico tools tend to overestimate the gastric emptying time for drugs in solution. o Nevertheless, adaptation of model parameters allows for a better simulation of the in vivo situation.