Prof. Jonathan GIBBINS
University of Reading
Biomedical Sciences
Programm
"The pathway to personalising anti-platelet therapy"
For decades, antiplatelet therapy, specifically aspirin and ADP receptor antagonists, has been used successfully for the prevention of thrombosis, although many patients still suffer thrombosis, while others experience serious bleeding side effects. Indeed, recent clinical trials have indicated that for the primary prevention of thrombosis (i.e., the prevention of thrombosis in patients without established cardiovascular disease), including those with multiple cardiovascular disease risk factors, the potential benefits are outweighed by the risk of bleeding. Due to this, guidelines have been recently changed, and antiplatelet drugs for primary prevention purposes are no longer recommended. At the heart of this problem is a ‘one size fits all’ approach to anti-thrombotic therapy.
We know platelet responsiveness to a range of activators is variable in the population, and responsiveness in an individual is a stable phenomenon. The question of which patients may benefit, and which may be harmed by antiplatelet therapy, however, is rarely considered. The reason for this is largely technical. The techniques used to assess platelet function in the clinic either lack the reproducibility and sensitivity (e.g. Born aggregometry) or depth of information (often single concentration responses to agonists – e.g. Multiplate or VerifyNow) that would allow variability in platelet response to be determined and interpreted. Additionally, platelets are challenging to prepare and work with, leading to pre-analytical issues.
In this seminar, I will explore the recent evolution of new approaches that enable more robust, detailed yet simple analysis of platelet function variability. This has led to the development of Platelet Phenomics Analysis (PPA). This flow cytometry-based system enables high-throughput analysis of platelet activation status and the determination of platelet sensitivity and capacity parameters, which can be utilised with machine-learning algorithms to cluster patients into phenotype groups. Indeed, platelet function phenotype groups cluster established cardiovascular disease risk factors, suggesting that this approach could be used for patient stratification. We find that patients with conditions such as ischaemic heart disease and immune thrombocytopenia exhibit distinctive and more variable PPA profiles, further supporting the use of platelet function to stratify patients for therapy. One of the most useful times to determine a patient’s platelet function is, unfortunately, at a time of crisis, during a thrombotic event. In these situations, haemostatic function is perturbed; therefore, an alternative approach is required. Using a PPA profiling and a biomarker discovery approach, we have overcome this limitation through the design of a stable test that successfully predicts platelet function parameters.
A question to consider is whether these approaches be made sufficiently quick and straightforward to allow personalised anti-platelet therapy? If so, then this may enable improved efficacy by targeting patients with very active platelets and identifying and treating those at risk of bleeding conservatively.
Host: Alice ASSINGER
Contact for questions: Helmut KUBISTA