Abstract Osteoporosis is a multifactorial bone disease that causes bones to weaken and become more susceptible to fracture. The prevalence of this disease increases with age, and women are twice as likely to be diagnosed than men at comparable ages. Clinically, osteoporosis is diagnosed by measuring bone mineral density (BMD) through dual-energy X-ray absorptiometry. Additional metrics are needed to augment BMD in order to increase the sensitivity for fracture risk. Raman spectroscopy is an optical technique that measures molecule’s vibrational modes, yielding a biochemical signature of the sample. From this biochemical signature, relative changes within the bone mineralization and matrix are quantified and can aid in fracture risk assessment. By utilizing spatially offset Raman spectroscopy (SORS), bone specimens can be measured transcutaneously and noninvasively, however the measured signal will contain spectral peaks from the soft tissue and bone. Since both soft tissue and bone contain type I collagen causing overlapping spectral peaks, the soft tissue signal must be suppressed. To address this challenge, we have developed an intricate algorithm to remove the soft tissue spectra called “top-layer subtraction via simultaneous over-constrained library-based decomposition” (SOLD/TLS) to accurately characterize bone health. Our group has demonstrated that SORS can measure murine bones in vivo, and by implementing SOLD/TLS, the soft tissue signal was suppressed, and that we can accurately predict bone biomechanical properties. This proposal aims to validate our Raman spectroscopy techniques as a preclinical, bone assessment tool. Here, we will focus on translating our methodologies to human measurements. The aims of this project are: Aim 1) Determine optimal source-detector offsets to guide the design of a scaled up SORS optical fiber bundle for reproducible transcutaneous measurements of metacarpals in human cadaver hands and Aim 2) Demonstrate the potential of transcutaneous SORS measurements of metacarpal bones in diagnosing osteoporotic hand samples. By completing these Aims, we will determine Raman spectroscopy’s capability to serve as a preclinical tool for characterizing bone quality and health, to aid in fracture risk assessment.