(M1130-02-09) Combining the Dynamic Gastric Model (DGM) with the Biorelevant Gastrointestinal Transfer (BioGIT) System to Evaluate the Performance of Three Nurofen® Ibuprofen Products

Purpose: Complex in vitro models of the upper gastro-intestinal (GI) tract that mimic the dynamic GI environment are of high value for the development and understanding of new oral pharmaceutical products as they may be capable of providing a similar or better predictive ability than animal models. The dynamic gastric model (DGM) is one such model that simulate the hydrodynamics, pH and emptying profile of the fed or fasted stomach (1). Through combination with the biorelevant gastrointestinal transfer (BioGIT) system, the DGM-BioGIT can be used to simulate the upper GI performance of three marketed Nurofen^® ibuprofen (IBU) products reported in a previously published clinical study (2). Simple convolution of the duodenal/jejunal dissolution data was performed in order to establish a correlation to in vivo data (3).

Methods: Two Nurofen^® tablets (corresponding to 400 mg IBU) was administered to the DGM along with 240 mL of tap water, which contained 35 mL of gastric acid solution. During the experiment, gastric acid solution and gastric enzyme solution were added at dynamic rates simulating the fasted state depending on pH and stomach content, respectively. The processing time was 35 min over which 7 samples of approx. 45 mL were ejected every 5 min. The samples ejected from the DGM were pumped at 9 mL/min into a 100 mL thermostated jacketed glass vessel (duodenal compartment) equilibrated to 37 °C under stirring along with 1 mL/min of concentrated (x10) fasted state simulated intestinal fluid (FaSSIF). After 5 minutes, a third pump transferred 10 mL/min from the duodenal compartment into a 600 mL thermostated jacketed glass vessel (jejunal compartment) equilibrated to 37 °C under stirring (yielding a constant volume in the duodenal compartment of 50 mL). In the duodenal compartment, the pH was monitored continuously and in the jejunal compartment, the pH was continuously adjusted to 6.5 through addition of 1M NaOH using a 902 Titrando from Metrohm (Herisau, Switzerland). Samples of 1 mL were withdrawn from the duodenal and jejunal compartments every 5 min. The samples were centrifuged at 13,300 rpm for 10 min, and the supernatant was diluted with methanol and analyzed for IBU concentration using HPLC-UV (230 nm).

Results: The IBU dissolution profiles of the samples from the duodenal compartment (0-40 min) and jejunal compartment (45-120 min) are shown in Figure 1 along with the predicted plasma profile and PK data (2). The predicted plasma profiles were obtained by simple convolution of the duodenal/jejunal dissolution data using an oral bioavailability of 100%, plasma half-life of 1.5 h and a volume of distribution of 8 L (3). As can be seen, the release of IBU from Lysine is both faster and to a larger extent than both Sodium and Crystal in the duodenal compartment (0-40 min). The release of IBU from Crystal is initially (0-15 min) faster than from Sodium, but after the initial lag (most likely due to tablet disintegration), the release of IBU from Sodium overtakes that from Crystal. As IBU is a weak acid, the rate and extent of dissolution from the formulations are pH dependent. In this regard it is interesting to note that the pH of the duodenal compartment is not controlled and therefore, the formulation (excipients) may have a significant impact on IBU release especially if they contain (alkaline) pH modifiers. This is in accordance with the pH profiles recorded for the three formulations where the average pH in the duodenal compartment was 6.3±0.3, 6.0±0.3, and 5.7±0.2 for Lysine, Sodium and Crystal, respectively. Upon simple convolution of the duodenal dissolution data (3), the plasma concentration-time profiles were predicted. As can be seen, the convoluted data seem to be very predictive of the human plasma concentration-time profiles with regards to both maximum plasma concentration (Cmax), time to reach Cmax (Tmax), area under the curve (AUC) for all three formulations as well as the general curve trends such as the intersection of the profiles after around 2 hours. Thus, the trends observed in the clinical trial was also demonstrated using the DGM-BioGIT system. This highlights the biorelevant nature of the DGM-BioGIT system and its potential to provide highly valuable information about the gastrointestinal behavior of oral formulations.

Conclusion: This study showed that the DGM-BioGIT system combined with simple convolution is able to predict the human plasma concentration-time profiles of three Nurofen® IBU products with great precision in simulated fasted state conditions. This suggests that the system can be used to predict human in vivo behavior, which could circumvent the need for expensive and time-consuming clinical studies.

References: 1. Wickham, M.J.S., Faulks, R.M., Mann, J., & Mandalari, G. The design, operation, and application of a dynamic gastric model. Dissolution Technology, 19(3), 15-22 (2010).
2. Miles, L., Hall, J., Jenner, B., Addis, R., & Hutchings, S. Predicting rapid analgesic onset of ibuprofen salts compared with ibuprofen acid. Current Medical Research and Opinion, 34(8), 1483-1490 (2018).
3. Qureshi, S.A. In vitro-in vivo correlation (IVIVC) and determining drug concentrations in blood from dissolution testing – a simple and practical approach. The Open Drug Delivery Journal, 4(1), 38-47 (2010).

Figure 1: Intestinal dissolution and (predicted) plasma profiles of IBU from Nurofen® Lysine (blue), Sodium (red) and Crystal (green) during fasted state conditions in the DGM-BioGIT system (solid line) and in vivo in humans (dashed line).