Increased molecular knowledge makes it possible to consider not only genetic defects but also expression profiles for precision medicine in advanced prostate cancer. Several prognostic and treatment-predictive classifiers for prostate cancer have been described, such as Prolaris, OncotypeDx, Decipher, Prostatype, PAM50, PCS1-2, and MetA-C, which all build upon transcript profiles. In research studies, the MetA-C classifier has shown clear prognostic information for patients with metastatic disease, in relation to outcome after androgen receptor targeting therapies, and so has immunohistochemical evaluation of tumor cell proliferation (Ki67) and PSA expression. Unfortunately, methods within clinical routine today do not allow molecular subclassification of prostate cancer. To enable comparison of the most promising treatment-predictive biomarkers and to evaluate the health economic value of implementing such precision medicine for prostate cancer, a prospective study is being planned as a joint initiative in Sweden that aims to evaluate and validate biomarkers and to establish a study platform for adaptive biomarker-driven clinical trials (sprintr.se).