By Jon Gibbins and Chris Jones

Over the past six decades, anti-thrombotic drug therapies have undergone a revolution, leading to major improvements in outcomes for cardiovascular disease (CVD) patients. In the UK, for example, CVD death rates have dropped by 75% during this period. However, CVD-related mortality and morbidity remain stubbornly high, with the death rate recently plateauing and possibly showing early signs of an increase.

Despite our progress, CVDs still account for about one-third of all deaths worldwide, totalling around 20 million deaths each year and affecting over 500 million people globally. Healthcare costs are enormous, with global spending expected to reach $1tn by 2030. Notably, low- and middle-income countries are disproportionately impacted by high rates of CVD mortality.

After all, we have effective drugs. The answer lies in the complex nature of platelets – tiny, highly reactive blood cells that prevent bleeding and protect us after injury, but also contribute to the formation of blood clots that block blood vessels (thrombosis), leading to heart attacks and strokes. Numerous mechanisms and pathways regulate platelet function. The influence of genetic diversity and environmental factors on these systems result in significant variation in platelet activity across the population.  Importantly, this is not reflected in current therapeutic strategies, where a one-size-fits-all approach remains in use.

This approach, combined with the variability in platelet function, means that while antiplatelet drugs are effective in some patients, they are ineffective in others and, even worse, they can cause catastrophic bleeding in a significant proportion of patients.

‘CVDs still account for about one-third of all deaths worldwide, totalling around 20 million deaths each year’

Without knowing which patients will benefit or encounter serious side effects, the effectiveness of antiplatelet drugs is therefore limited. The rationale for personalising antiplatelet treatments to improve patient outcomes has been evident for some time. What has been missing is the ability to effectively assess platelet function in clinical settings, allowing for better patient stratification. We are now at a turning point, with advanced new technologies supporting detailed cell-based analyses that will be essential for optimising current and future anti-platelet therapies.

In this second article, we describe how biomarker-based prediction of an individual’s platelet function characteristics can guide antiplatelet therapy. This first step towards the personalisation of antiplatelet therapy promises to revolutionise the prevention of thrombosis without the need for new drugs.

In the arterial circulation, platelets respond to factors that are exposed (eg, collagen in the extracellular matrix), secreted (eg, ADP) or generated by activated platelets (eg, Thromboxane (TxA2) at sites of injury, and become activated. The platelet ‘plug’ or thrombus that forms is stabilised by thrombin formed on the surface of platelets and the consequent generation of polymerised fibrin.

Arterial thrombosis often occurs because platelets cannot distinguish injury signals from those present in diseased vessels (ie, vessels with atherosclerotic lesions and unstable plaque rupture), resulting in an occlusive thrombus and downstream tissue damage. In coronary arteries, this causes myocardial infarction; in cerebral vessels, ischaemic stroke.

As key instigators of thrombosis, platelets are targeted with drugs to suppress their function. The archetypal example is aspirin – the frontline drug – which inhibits platelet cyclo-oxygenase, and disrupts the auto/paracrine actions of TxA2 and reduces thrombus growth. Aspirin is often used alongside other medications (dual antiplatelet therapy (DAPT)) such as ADP receptor (P2Y12) antagonists, including clopidogrel, prasugrel and ticagrelor, which similarly diminish the auto/paracrine actions of ADP, secreted by activated platelets.

These medications have been shown to prevent thrombosis in numerous clinical trials, although some patients still experience myocardial infarction or stroke while on treatment. Furthermore, inhibiting haemostatic function carries a bleeding risk, which can be life-threatening (eg, haemorrhagic stroke or gastrointestinal bleeds). Landmark 2018 studies found that the benefits of antiplatelet medication for primary prevention did not outweigh the risks, even for patients with multiple CVD risk factors.  Consequently, the widespread use of aspirin for primary prevention has ended, and pharmacological options for high-risk, but otherwise healthy, patients remain limited.

Patients who have recently had a myocardial infarction or ischaemic stroke are at high risk of recurrent events, making them suitable candidates for DAPT, typically prescribed during periods of greatest risk. In the UK, NICE guidelines recommend assessing bleeding risk before starting DAPT; however, no current risk scores incorporate platelet function measurements, despite platelet function being crucial to the efficacy of antiplatelet medication. In addition, some patients also develop secondary thrombosis despite DAPT, indicating that thrombosis and bleeding risks vary between patients.

Alongside anti-thrombotic drugs, one of the major advances in cardiovascular health has been the development and widespread use of antihypertensive medications, and the management of plasma lipid levels through statins. Consider how these drugs are prescribed and monitored. Before their prescription, blood pressure or cholesterol levels are measured; we would find it absurd if they weren’t. The effects of these drugs are easily assessed by doctors, enabling dosage adjustments or the use of alternative medications. Conversely, when patients are prescribed antiplatelet medication, platelet function isn’t measured before or after treatment. It’s assumed that platelet function and responses are the same for all patients. Herein lies a problem.

Platelet function is actually highly variable. The first large-scale analysis of this in healthy donors was published in 2009. This revealed remarkable variability and the presence of very high and very low responders in the population. Recall studies conducted in the following months and years revealed that these features were stable and personal. This showed, for the first time, that understanding an individual’s platelet reactivity might affect the likelihood of success or failure of antiplatelet therapy.

Doctors are faced daily with difficult medication decisions. Should they use DAPT and risk bleeding side effects, or aspirin alone and risk limiting efficacy?

Gross defects in platelet function can be detected through platelet function testing; however, the techniques used are not well-suited for refined analysis of reactivity. Point-of-care platelet function tests, for example, are available to assess haemostatic potential during surgery; however, they do not provide the detailed information on platelet function variation that is needed to stratify antiplatelet medication use.

Measuring a patient’s platelet function is further complicated during a heart attack or stroke because haematological parameters, including platelet function, change during a thrombotic event.

HaemAnalytica approached this question differently, by asking whether stable cell-based biomarkers could predict, rather than measure, a patient’s platelet function. To answer this, platelet function in healthy individuals was analysed using the PLANA Platelet Phenomics Analysis platform, alongside biochemical and anthropomorphic measurements. Statistical modelling identified three biomarkers that together predict platelet function. Based on these, HaemAnalytica developed TRIPLEcheck, a flow cytometry test requiring only a few microlitres of blood.

TRIPLEcheck has been validated in healthy volunteers and patient cohorts. Patients predicted to have high platelet activity showed increased function and thrombus formation. Critically, these high-responders were insensitive to aspirin alone, but their platelets responded to a second agent, supporting dual therapy (DAPT).

This comes at a time when advances in pharmacogenomics promise to further inform drug choices. Notably, commonly used antiplatelet drugs such as clopidogrel and prasugrel are prodrugs with well-characterised metabolic activation pathways impacted by common CYP2C19 alleles. This suggests that, following cell function-based patient stratification with TRIPLEcheck, pharmacogenomics analysis may further guide specific drug selection.

While the concept of personalised medicine can be traced back to Hippocrates, its application in modern medicine is limited by the quality of the data used to inform clinical decisions and by our ability to interpret biological differences. The measurement of platelet function provides an accurate, personalised readout of the genomic, proteomic and cellular environments that combine to produce physiological diversity.

We are at a pivotal moment. With clinical studies underway, HaemAnalytica is poised to test the impact of TRIPLEcheck on treatment efficacy. The use of reliable, appropriate cellular biomarkers to measure platelet function, coupled with pharmacogenomics, will provide doctors with greater clarity when prescribing antiplatelet medication, thereby improving efficacy, reducing heart attacks and strokes, and lowering bleeding risks, while leading to better patient outcomes and reduced costs. This could even mark the resurgence of antiplatelet drugs for primary prevention, and another significant reduction in CVD-related mortality and morbidity.