Stroke biomarkers for hyperacute phase (<6 hrs after stroke onset), including pre-hospital when a patient arrives at the emergency department, as well as the in-hospital acute phase (6-72 hrs after stroke onset), are extremely relevant. We are focused on biomarkers for severe malignant edema (SE) and hemorrhagic transformation (HT) post-mechanical thrombectomy (MT), which is performed within 3-24 hours after the procedure.

There are opportunities for developing biomarkers to better guide the treatment in the intensive phase of stroke. We have access to proteomics, genomics and machine learning tools to develop biomarkers that are guiding the development of in-vitro diagnostic and therapy for stroke patients with emergent large vessel occlusion (ELVO).

Novel Rat Model (Transient occlusion for 5 hrs. matches human ischemic stroke)

Better translation to stroke IVD & adjuvant therapy

(Thrombus and blood from the infarct site)

A key barrier to progress in stroke research has been a lack of translatable surrogates (e.g. in vitro cell culture, animal models) to estimate, extrapolate, and model molecular events occurring within the human brain. No study to date has been able to produce a molecular view into the neurovascular signaling and immune responses in the human condition as stroke occurs. The Center for Advanced Translational Stroke Science at the University of Kentucky (UK) developed the Blood and Clot Thrombectomy Registry and Collaboration (BACTRAC; NCT03153683).

Through the standard thrombectomy process, we isolate distal blood within the artery immediately downstream from the clot prior to its removal; peripheral blood just proximal to the clot; and the thrombus itself upon removal from the human subject. BACTRAC has provided a window into acute processes of ischemia unfolding at the time of thrombectomy.

An animal model has be developed that closely mimics an ischemic stroke, and subsequent clinical thrombectomy procedure and drug delivery system. This rat model expresses key cytokines and chemokines, in the blood after stroke in a similar manner as the human stroke patient as confirmed by analysis of BACTRAC samples. This translatable animal model can be used to test adjuvant therapeutics for thrombectomy, which would provide significant benefit in ischemic stroke patients. Machine learning can be used to both determine molecular predictors from ischemic blood and repurpose pharmaceutical agents to fast track the clinical process to develop an adjuvant therapy for thrombectomy to ultimately improve recovery of stroke patients.