Precision medicine and adverse drug reactions related to cardiovascular drugs

Cardiovascular disease remains the leading global cause of death. Early intervention, with lifestyle advice alongside appropriate medical therapies, is fundamental to reduce patient mortality among high-risk individuals. For those who live with the daily challenges of cardiovascular disease, pharmacological management aims to relieve symptoms and prevent disease progression. Despite best efforts, prescription drugs are not without their adverse effects, which can cause significant patient morbidity and consequential economic burden for healthcare systems. Patients with cardiovascular diseases are often among the most vulnerable to adverse drug reactions due to multiple co-morbidities and advanced age. Examining a patient’s genome to assess for variants that may alter drug efficacy and susceptibility to adverse reactions underpins pharmacogenomics. This strategy is increasingly being implemented in clinical cardiology to tailor patient therapies. The identification of specific variants associated with adverse drug effects aims to predict those at greatest risk of harm, allowing alternative therapies to be given. This review will explore current guidance available for pharmacogenomic-based prescribing as well as exploring the potential implementation of genetic risk scores to tailor treatment. The benefits of large databases and electronic health records will be discussed to help facilitate the integration of pharmacogenomics into primary care, the heartland of prescribing

Approval of New Pharmacogenomic Tests: Is the Canadian Regulatory Process Adequate?

In the first part of our analysis, we will examine the impact which pharmacogenomics is expected to have on drug research and development, on the drug approval process and on post-marketing surveillance and clinical practice. This will allow us to show how pharmacogenomic testing could be beneficial to drug companies, regulatory bodies, and patients. The second part of our analysis will focus on the regulatory framework applicable to the approval of pharmacoge- nomic tests in Canada, although we are aware of the fact that most manufacturers decide to approve their tests outside of Canada. As mentioned, the applicable regu- lations will depend on the way the test is marketed; the federal and provincial re- quirements will both be covered in detail. It is interesting to note that very few pharmacogenomic test developers currently choose to get their tests approved by Health Canada. Most often they will commercialize their product in the United States first and go through the provincial approval route when seeking approbation in Canada.7 The review of the expected benefits and of the Canadian regulatory framework governing pharmacogenomic tests will then allow us to evaluate if the latter is ap- propriate considering the positive impact pharmacogenomics could have on phar- maceutical development and the health care system. We will discuss the question of whether it should be changed and simplified so that manufacturers could obtain faster (or simplified) approval for their tests in order to commercialize them more rapidly

Harnessing Openness to Transform American Health Care

The Digital Connections Council (DCC) of the Committee for Economic Development (CED) has been developing the concept of openness in a series of reports. It has analyzed information and processes to determine their openness based on qualities of "accessibility" and "responsiveness." If information is not available or available only under restrictive conditions it is less accessible and therefore less "open." If information can be modified, repurposed, and redistributed freely it is more responsive, and therefore more "open." This report looks at how "openness" is being or might usefully be employed in the healthcare arena. This area, which now constitutes approximately 16-17 percent of GDP, has long frustrated policymakers, practitioners, and patients. Bringing greater openness to different parts of the healthcare production chain can lead to substantial benefits by stimulating innovation, lowering costs, reducing errors, and closing the gap between discovery and treatment delivery. The report is not exhaustive; it focuses on biomedical research and the disclosure of research findings, processes of evaluating drugs and devices, the emergence of electronic health records, the development and implementation of treatment regimes by caregivers and patients, and the interdependence of the global public health system and data sharing and worldwide collaboration

The Inclusion of Health Data Standards in the Implementation of Pharmacogenomics Systems: A Scoping Review

Background: Despite potential benefits, the practice of incorporating pharmacogenomics (PGx) results in clinical decisions has yet to diffusewidely. In this study,we conducted a review of recent discussions on data standards and interoperability with a focus on sharing PGx test results among health systems. Materials & methods:We conducted a literature search for PGx clinical decision support systems between 1 January 2012 and 31 January 2020. Thirty-two out of 727 articles were included for the final review. Results: Nine of the 32 articles mentioned data standards and only four of the 32 articles provided solutions for the lack of interoperability. Discussions: Although PGx interoperability is essential for widespread implementation, a lack of focus on standardized data creates a formidable challenge for health information exchange. Conclusion: Standardization of PGx data is essential to improve health information exchange and the sharing of PGx results between disparate systems. However, PGx data standards and interoperability are often not addressed in the system-level implementation

Knowledge-Based Matching of nn-ary Tuples

An increasing number of data and knowledge sources are accessible by human and software agents in the expanding Semantic Web. Sources may differ in granularity or completeness, and thus be complementary. Consequently, they should be reconciled in order to unlock the full potential of their conjoint knowledge. In particular, units should be matched within and across sources, and their level of relatedness should be classified into equivalent, more specific, or similar. This task is challenging since knowledge units can be heterogeneously represented in sources (e.g., in terms of vocabularies). In this paper, we focus on matching n-ary tuples in a knowledge base with a rule-based methodology. To alleviate heterogeneity issues, we rely on domain knowledge expressed by ontologies. We tested our method on the biomedical domain of pharmacogenomics by searching alignments among 50,435 n-ary tuples from four different real-world sources. Results highlight noteworthy agreements and particularities within and across sources