In Silico Clinical Trials for Osteoporosis Treatments: Effect of Bone Loss on the Hip Fracture Incidence

Osteoporosis (OP) is a skeletal disorder, most common in postmenopausal women, characterised by reduced bone mineral density (BMD) and increased risk of hip fracture. Current OP treatments have limited efficacy, and the development of new drugs is associated with significant costs and time-to-market. Computational approaches are emerging as an alternative to improve the development process of new treatments. This study was focused on the development of an In Silico trial methodology to assess OP treatments. In particular, the effect of BMD loss on predicted hip fracture incidence was quantified. The placebo arm of a concluded clinical trial was replicated In Silico and used to validate the model. A cohort of 1000 virtual patients was generated, replicating the baseline BMD reported in the reference study. OP progression was simulated with a reduction of BMD over time at three different rates, including inter-subject variability. A multiscale model was used to estimate the load transmitted to the femur during a side fall. The femur failure load was obtained with finite element models. A patient was considered fractured when the impact load exceeded the femur strength. Fracture incidence obtained for the three cohorts (1.5%, 1.6% and 1.7% respectively) was partially overestimated compared to the clinical data (1.2%), and no significant differences were obtained between the three cohorts. Future developments will be focused on further sensitivity analyses on relevant model parameters, the refinement of their definition, and the introduction and validation of OP treatment models. This In Silico trial methodology can be applied in the future for the development and assessment of OP treatments.