Strontium release from Sr2+-loaded bone cements and dispersion in healthy and osteoporotic rat bone

Abstract Drug functionalization of biomaterials is a modern and popular approach in biomaterials research. Amongst others this concept is used for the functionalization of bone implants to locally stimulate the bone healing process. For example strontium ions (Sr 2+ ) are administered in osteoporosis therapy to stimulate bone growth and have recently been integrated into bone cements. Based on results of different analytical experiments we developed a two-phase model for the transport of therapeutically active Sr 2+ -ions in bone in combination with Korsmeyer-Peppas kinetics for the Sr 2+ release from bone cement. Data of cement dissolution experiments into water in combination with inductively coupled plasma mass spectrometry (ICP-MS) analysis account for dissolution kinetics following Noyes-Whitney rule. For dissolution in α-MEM cell culture media the process is kinetically hindered and can be described by Korsmeyer-Peppas kinetics. Time of flight secondary ion mass spectrometry (ToF-SIMS) was used to determine the Sr 2+ diffusion coefficient in healthy and osteoporotic trabecular rat bone. Therefore, bone sections were dipped in aqueous Sr 2+ -solution by one side and the Sr 2+ -profile was measured by classical SIMS depth profiling. The Sr 2+ mobility can be described by a simple diffusion model and we obtained diffusion coefficients of (2.28 ± 2.97) ⋅ 10 − 12  cm 2 /s for healthy and of (1.55 ± 0.93) ⋅ 10 − 10  cm 2 /s for osteoporotic bone. This finding can be explained by a different bone nanostructure, which was observed by focused ion beam scanning electron microscopy (FIB-SEM) and transmission electron microscopy (TEM). Finally, the time and spatially resolved drug transport was calculated by finite element method for the femur of healthy and osteoporotic rats. The obtained results were compared to mass images that were obtained from sections of in vivo experiments by ToF-SIMS. The simulated data fits quite well to experimental results. The successfully applied model for the description of drug dispersion can help to reduce the number of animal experiments in the future.