The following thesis presents a computational framework that can capture inherently non-linear and emergent biocomplex phenomena. The main motivation behind the investigations undertaken was the absence of a suitable platform that can simulate, both the continuous features as well as the discrete, interaction-based dynamics of a given biological system, or in short, dynamic reciprocity. In order to determine the most powerful approach to achieve this, the efficacy of two modelling paradigms, transport phenomena as well as agent-based, was evaluated and eventually combined. Computational Fluid Dynamics (CFD) was utilised to investigate optimal boundary conditions, in terms of meeting cellular glucose consumption requirements and exposure to physiologically relevant shear fields, that would support mesenchymal stem cell growth in a 3-dimensional culture maintained in a commercially available bioreactor. In addition to validating the default bioreactor configuration and operational parameter ranges as suitable towards sustaining stem cell growth, the investigation underscored the effectiveness of CFD as a design tool. However, due to the homogeneity assumption, an untenable assumption for most biological systems, CFD often encounters difficulties in simulating the interaction-reliant evolution of cellular systems. Therefore, the efficacy of the agent-based approach was evaluated by simulating a morphogenetic event: development of in vitro osteogenic nodule. The novel model replicated most aspects observed in vitro, which included: spatial arrangement of relevant players inside the nodule, interaction-based development of the osteogenic nodules, and the dependence of nodule growth on its size. The model was subsequently applied to interrogate the various competing hypotheses on this process and identify the one that best captures transformation of osteoblasts into osteocytes, a subject of great conjecture. The results from this investigation annulled one of the competing hypotheses, which purported the slow-down in the rate of matrix deposition by certain osteoblasts, and also suggested the acquisition of polarity to be a non-random event. The agent-based model, however, due to being inherently computationally expensive, cannot be recommended to model bulk phenomena. Therefore, the two approaches were integrated to create a modelling platform that was utilised to capture dynamic reciprocity in a bioreactor. As a part of this investigation, an amended definition of dynamic reciprocity and its computational analogue, dynamic assimilation, were proposed. The multi-paradigm platform was validated by conducting melanoma chemotaxis under foetal bovine serum gradient. Due to its CFD and agent-based modalities, the platform can be employed as both a design optimisation as well as hypothesis testing tool.