Spatially offset Raman spectroscopy (SORS) can accurately, fast, and non-destructively obtain the characteristic spectral information from multi-layer turbid media samples. In this work, we developed and introduced a modular inverse SORS device realizing two different spectral detection modes of inverses SORS and conventional backscattering Raman spectroscopy. The deep-layer Raman spectral information from the two/ three-layer tissue model was detected and analyzed with different spatial offset value (Δs). Meanwhile, by the geometrical optics theory and the principle of projection measurement, the quantitative relationship between Δs and the axicon lens position is addressed, which supports precise controlling of the spectral detection conditions. In order to verify the system performance, a two-layer model composed of sheep scapula/paracetamol and a three-layer model composed of pig skin/silicone rubber/paracetamol were used to obtain the mixed spectra containing the constitution information of samples surface and deep layers under different spatial offsets. By performing area-under-curve normalization on the mixed spectra, it was observed that the Raman contribution of the sample surface decreases with the increase Δs value, while the Raman contribution of the second or third layers gradually increases. Moreover, for better understanding the dependence of the relative Raman intensity on the spatial offset and thickness, the relative Raman intensity is calculated by selecting the characteristic peaks of each layer in the model. The relative Raman intensity ratio increases with the increase of Δs, which exhibits an enhanced pattern of the Raman intensity. However, with the same spatial offset condition, the relative Raman intensity induces as the thickness of the first layer increases. The above experimental results testified that our developed modular inverse SORS device could obtain spectral information from a biological model with a depth of 8 mm, and manifest the application potentialities of our inverse SORS system in transcutaneous non-destructive detection.