Modern drug developments have had a particular focus on so-called ‘large molecule’ biotheraputics comprising of large protein molecules. Typically, biotheraputics cannot be consumed orally, and they often require formulations of high volumes and viscosities which are delivered in a subcutaneous injection format, compared with traditional ‘small molecule’ drugs which can normally be consumed orally. Until recently it has been typical to inject volumes in the range of 1-2ml subcutaneously, with viscosities in the 1-5cP range. Modern large molecule drug programs contain fast injection of volumes up to 5ml, and slow injections of up to 20ml. As an alternative to large volumes some drug development programs have increased the concentrations resulting in higher viscosities, some as high as 1000cP have been investigated for slow release drugs where drug ‘depots’ are created in the subcutaneous space. The ambition of the current work was to use a Finite Element Modelling (FEM) approach to create a digital twin of the subcutaneous tissue space, so that the distribution of drugs in the subcutaneous space when moving toward large volumes and viscosities can be better understood relative to their impact on uptake by the body (pharmacokinetics). Risks of these new large volume and viscosity therapies include pain, tissue damage, leakage and absorption variability. These risks influence the design of injection devices, and optimisation opportunities arise from developing a physics-based understanding of the injection mechanics. Accurate computational modelling can provide insights that are not feasible to test experimentally. We present cutting edge digital models for the evaluation of subcutaneous injection device performance across a range of diverse digital patients. There is a current trend to develop the ‘digital human’, although the current work focused on developing a digital twin for the closest animal representation for the subcutaneous human tissue space, Aachen minipigs. The model has been developed using Abaqus and user defined elements to accurately represent the subcutaneous adipose tissue structure of fat lobules held together with collagen septa. This has been achieved by combining classic element types with new user defined elements into a novel FEM approach. Furthermore, a recent experimental campaign using micro Computational Tomography (CT) collected subcutaneous adipose tissue variability to create a biological tissue library, which was subsequently overlaid onto the Abaqus model so that spread of the drug under the skin would progress organically. The tissue library also permits a more realistic statistical approach rather than a single output from the modelling approach. The current model allows for variation of properties such as injection depth, injection flow rate, injected volume, and fluid viscosity. The modelling approach is presented along with a comparison with experimental data used for validation in the form of tissue back-pressure during injection, and the spread of the drug through the tissue compared against CT data.