In this thesis a computational framework was developed to prole the musculoskeletal loading during exercise in hypogravity and to model muscular adaptations to disuse. The aims were i) to create a Biomechanical Handbook of normative internal musculoskeletal loading proles when exercising in hypogravity, and ii) to assess how muscular adaptations to unloading can be replicated with a Hill-type muscle model. A direct collocation framework was used to estimate muscle and joint reaction forces, validated against the Knee Grand Challenge dataset. The framework was then used to estimate lower-limb joint reaction forces during single-leg hopping at ve hypogravity levels, and predict exercise volume to avoid detrimental adaptations. Joint reaction forces were estimated within 0.62 - 0.85 BW relative to the Knee Grand Challenge data, with a peak error of 1.24 0.17 BW. The framework was also able to detect the increase in peak joint reaction force as walking speed increased. The hypogravity case-study revealed an increased quadriceps muscle forces and a shift in rectus femoris force as gravity approached 1 g. When quadriceps muscle forces were input into a muscle adaption model, predicted exercise volumes needed to combat muscle adaptations decreased substantially with gravity. The framework allows for the comparison between dierent movements and gravity levels needed to create a Biomechanical Handbook. An experimental protocol, which expands on the handbook vision, is presented to provide a blueprint for the analysis of a catalogue of gait and jumping exercises in hypogravity to provide reference values to the handbook. Finally, a Monte Carlo sampling technique was used to perturb Hill-type muscle model parameters during an isokinetic knee extension task. The results highlighted the Hill-type muscle model can replicate muscular adaptations to unloading as long as optimal bre length is adjusted appropriately. This information is key for future research to adjust musculoskeletal models to achieve appropriate simulation results, which will improve application of simulation methods to space science contexts.