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Regulators and payers have contrasting priorities that can lead to divergent decisions and delays in patient access to new treatments. Those involved in coverage decisions have not routinely been integrated in the drug development process. Theoretically, inclusion of payer representatives early in development could help discern discordance among stakeholder priorities; facilitate cooperation to align objectives; foster agreement on the evidence required for approval and reimbursement; improve transparency, accountability, and consistency of payer decision making; and ideally, minimize delays in patient access to new therapies. However, early participation by payers may not provide these expected benefits if payers' decision-making processes are not evidence based or cannot be reliably predicted. This paper describes current interactions among regulatory agencies, payers, sponsors, and investigators and proposes collaboration among all stakeholders earlier in the development process. The premise that a priori discussions might facilitate the delivery of advances in cardiovascular care is a hypothesis worth testing. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity, and knowledge storage. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enable cost-effectiveness, and reduce readmission and mortality rates. Over the past decade, several machine-learning techniques have been used for cardiovascular disease diagnosis and prediction. Each problem requires some degree of understanding of the problem, in terms of cardiovascular medicine and statistics, to apply the optimal machine-learning algorithm. In the near future, AI will result in a paradigm shift toward precision cardiovascular medicine. The potential of AI in cardiovascular medicine is tremendous; however, ignorance of the challenges may overshadow its potential clinical impact. This paper gives a glimpse of AI's application in cardiovascular clinical care and discusses its potential role in facilitating precision cardiovascular medicine. [ABSTRACT FROM AUTHOR]

Despite the global burden of cardiovascular disease, investment in cardiovascular drug development has stagnated over the past 2 decades, with relative underinvestment compared with other therapeutic areas. The reasons for this trend are multifactorial, but of primary concern is the high cost of conducting cardiovascular outcome trials in the current regulatory environment that demands a direct assessment of risks and benefits, using clinically-evident cardiovascular endpoints. To work toward consensus on improving the environment for cardiovascular drug development, stakeholders from academia, industry, regulatory bodies, and government agencies convened for a think tank meeting in July 2014 in Washington, DC. This paper summarizes the proceedings of the meeting and aims to delineate the current adverse trends in cardiovascular drug development, understand the key issues that underlie these trends within the context of a recognized need for a rigorous regulatory review process, and provide potential solutions to the problems identified. [ABSTRACT FROM AUTHOR]

Thrombosis is the most important underlying mechanism of coronary artery disease and embolic stroke. Hence, antithrombotic therapy is widely used in these scenarios. However, not all patients achieve the same degree of benefit from antithrombotic agents, and a considerable number of treated patients will continue to experience a new thrombotic event. Such lack of clinical benefit may be related to a wide variability of responses to antithrombotic treatment among individuals (i.e., interindividual heterogeneity). Several factors have been identified in this interindividual heterogeneity in response to antithrombotic treatment. Pharmacogenetics has emerged as a field that identifies specific gene variants able to explain the variability in patient response to a given drug. Polymorphisms affecting the disposition, metabolism, transporters, or targets of a drug all can be implicated in the modification of an individual''s antithrombotic drug response and therefore the safety and efficacy of the aforementioned drug. The present paper reviews the modulating role of different polymorphisms on individuals'' responses to antithrombotic drugs commonly used in clinical practice. [Copyright &y& Elsevier]

Antiplatelet therapy is the cornerstone of treatment for patients with acute coronary syndromes and/or undergoing percutaneous coronary interventions. Clopidogrel, in combination with aspirin, is currently the antiplatelet treatment of choice for prevention of stent thrombosis, and clinical trials have shown that, in high-risk patients, prolonged dual antiplatelet treatment is more effective than aspirin alone in preventing major cardiovascular events. However, despite the use of clopidogrel, a considerable number of patients continue to have cardiovascular events. Numerous in vitro studies have shown that individual responsiveness to clopidogrel is not uniform in all patients and is subject to inter- and intraindividual variability. Notably, there is a growing degree of evidence that recurrence of ischemic complications may be attributed to poor response to clopidogrel. The mechanisms leading to poor clopidogrel effects are not fully elucidated and are likely multifactorial. Although the gold standard definition to assess antiplatelet drug response has not been fully established, there is sufficient evidence to support that persistence of enhanced platelet reactivity despite the use of clopidogrel is a clinically relevant entity. This paper reviews the impact of individual response variability to clopidogrel on clinical outcomes and current and future directions for its management. [Copyright &y& Elsevier]