A lot of effort has been made in times to improve the understanding and functioning of the human gastrointestinal tract and to engineer novel in-vitro models with greater biomechanical and biochemical relevance (Boulby et al. 1999; Faas et al. 2002; Kunz et al. 2005; Goetze et al. 2007, 2009; Kwiatek et al. 2006; Marciani et al. 2001a, 2007, 2012; Marciani 2011; Schwizer et al. 2002, 2006; Steingoetter et al. 2005; Treier et al. 2006; Mackie et al. 2013).Without physical models that can closely represent digestion “near real”, in-vitro to in-vivo correlation will leave a gap that will cloud the true understanding of the digestion processes. In-vitro digestion studies are highly desired because of their uses in food and nutrition (Frei et al., 2003; Hur et al., 2011; Guerra et al., 2012) and highly advantageous in saving time and cost, and have demonstrated some levels of reproducibility when compared to clinical studies (in-vivo) in (Kong and Singh 2008a, 2008b; Kong and Singh 2010). Performing in-vitro digestion can take the path of either a static or dynamic simulation (Guerra et al., 2012 and Alegria et al., 2015). The static approach is very simple, and do not simulate the physical processes of digestion (Alegria et al., 2015) such as, shearing, mixing, hydration and peristalsis (Fernandez-Garcia et al, 2009 and Wickham et al., 2009), whereas the dynamic simulation does. More recent, there are strong approaches to standardized (Minekus et al., 2014) and harmonize (Egger et al., 2016) in-vitro digestion using static models, where the main task is to improve comparing results across research teams. As such, proposal has been made to address on static digestion in-vitro models to remove barriers such as using enzymes from different origins, food bolus to secretion ratios (intestinal fluids) and variations in pH. However, even with this effort, dynamic digestion models are still favored, because of the ability to closely mimic digestion to model the gastrointestinal complexities that will aid in better interpretation of results (Hur et al., 2011; Guerra et al., 2012). Absorption of nutrients are critical for health and sustain functionality of cells and human wellbeing (Borgström et al., 1957; Guyton and Hall, 2015). This phenomenon takes place in the small intestine where as little as 10% of the total micro-nutrients from bulk digest escapes the absorption process (Guerra et al., 2012). The mechanisms removing up to 9/10ths of the nutrient content from bulk across the epithelium border during digestion in the body are not clearly understood. The challenge to global health is clear, and absorption of any nutrient in less or large amounts can be detrimental to health, leading to diet-related diseases, such as diabetes (Jenkins et al., 2002) and obesity (WHO, 2000). However, in order to optimize foods for health benefits, knowledge underlying digestion on the molecular scale is needed to understand how foods are degraded (Norton, 2007) to mobilise nutrients for absorption (bio-accessible and bioavailable) during the digestion process in the bowels (Jenkins et al., 1981; Englyst et al., 1996). A lot of in-vitro procedures simulate intestinal digestion by simply mixing food and intestinal fluids using an over-head mixer (Oomen and others 2003), a shaking bath (Muir and O’Dea 1992), or magnetic stirrer (De Boever and others 2001). Clearly, these procedures oversimplify the mixing process, and will not reproduce the fluid mechanics and the mechanical forces that the digesta would face in the small intestine resulting from contractions of the gut wall. Evidence strongly supports that, the environment brought about from fluid-mechanical events during digestion have a crucial function on the material response to making nutrient becoming biologically available (Dikeman et al. 2006; Lentle and Janssen, 2010). Similarly, until recently, most dynamic models which were used to perform bowel digestions, had rarely account for the interaction effects of segmentation and peristaltic forces on the food digestibility and nutrient transport (Guerra et al., 2012; Gouseti et al., 2014; Tharakan et al., 2010), when reporting product transportation and intestinal absorption. Some of these complex dynamic models able to simulate aspects of intestinal digestion include the TIM, a gastro intestinal model, simulating peristalsis and absorption (Minekus et al., 1995 and Kheadr et al., 2010), the soft tubular bio-inspired reactor model, which simulate peristalsis frequency and amplitude to understand mass transfer and mixing (Deng et al., 2016), and the human duodenum model (HDM), which mimics the geometry of the human duodenum, consisting of ascending and descending regions capable of irregular segmenting patterns to understand transit rate (Wright et al., 2016). These models clearly simulate one or two aspects of intestinal digestion, but not all or almost real. A small intestine model (SIM), developed by Tharakan (2010) was improved by Gouseti (2014) (the Dynamic Duo) which was further improved to the dynamic duodenal model (DDM). It has enhanced features and is able to simulate most aspects of small intestinal digestion in-vitro (Tharakan et al., 2010 and Gouseti et al., 2014). Longland (1991) has stated that an effective in-vitro model should incorporate the following: sequential and physiological relevant use of enzymes; appropriate pH and simulated GI fluids; the elimination of the digested product; suitable biological transit times and mixing at each compartment for each step of digestion. The improved dynamic duodenal model was designed with these functionalities. If the digested contents were to simply propel through the small intestine, then the digestion and absorption processes would have been poorly performed, as admix of enzymes to digesta would be partial, and bulk digesta would rarely come in contact with epithelium cells for absorption to take place (Hall., 2015; Ganong and Ganong, 1995). Mixing is crucial to the digestion process in the small intestine bowel, facilitating these reactions and transportation (Dikeman et al. 2006; Lentle and Janssen, 2010). Mixing is facilitated by two main processes, a combination of segmentation or peristalsis or either (Hall., 2015). However, segmentation is known to have a more powerful effect on mixing (Stoll et all, 2000; Ganong and Ganong, 1995 and Barrett et al., 2010) than do peristalsis, and is often overlook in most dynamic in-vitro models (Gouseti et al., 2014). This research explores these effects on these contributions on digestibility and absorption while varying the digest’s viscosity. Manipulating the luminal content’s viscosity may affect digestibility, and has shown to alter physiologic responses (Dikeman et al., 2007; Dorota et al., 2012; Edmund et al., 2014; Pernille et al., 2013). The soft tubular material of the dynamic duodenal model vessel allows the walls and inner lumen to be actively engaging in the mixing and reactions and simulated mass transfer during digestion. It also has at pancreatic duct positioned to release intestinal fluids onto the incoming pyloric outflow. Overall the model was developed, and the new tool attempts to create a realistic environment to perform intestinal digestion. To date, the dynamic duodenal model has been used to investigate digestibility changes experienced by different food products during digestion, and also to study the effect of intestinal motility on the outcomes of the digestion processes, such as glycaemic indices.