Search

The primary goal of genomic medicine is to make use of an individual’s genomic information to support the clinical decision-making process. At present, several international organizations and research consortia exist, which aim to support the translation of genomic research into clinical practice so that genomic medicine can ultimately be used to benefit the global community. The Genomic Medicine Alliance (http://www.genomicmedicinealliance.org/) is a global academic research network that seeks to establish and strengthen collaborative ties between different genomic medicine stakeholders. Its focus lies firmly with the translation of scientific research findings into clinical practice. To this end, it brings together experts from various disciplines including genome informatics, pharmacogenomics, and public health genomics, as well as experts on ethical, legal, and social issues in the sphere of genomics/health economics. These multidisciplinary activities are supervised by a 15-member International Scientific Advisory Committee. Its official journal, Public Health Genomics, offers members a highly respected publication forum for reviews, original research findings, and policy in this field. In the short-to-medium term, the Genomic Medicine Alliance aims to promote research collaborations between developed and developing countries and to organize educational activities in the field of genomic medicine. In the longer term, it aspires to become a focal point for global collaboration in the field of genomic medicine while helping to pave the way for a smoother transition from genomics research to genomic medicine.

The primary goal of genomic medicine is to make use of an individual’s genomic information to support the clinical decision-making process. At present, several international organizations and research consortia exist, which aim to support the translation of genomic research into clinical practice so that genomic medicine can ultimately be used to benefit the global community. The Genomic Medicine Alliance (http://www.genomicmedicinealliance.org/) is a global academic research network that seeks to establish and strengthen collaborative ties between different genomic medicine stakeholders. Its focus lies firmly with the translation of scientific research findings into clinical practice. To this end, it brings together experts from various disciplines including genome informatics, pharmacogenomics, and public health genomics, as well as experts on ethical, legal, and social issues in the sphere of genomics/health economics. These multidisciplinary activities are supervised by a 15-member International Scientific Advisory Committee. Its official journal, Public Health Genomics, offers members a highly respected publication forum for reviews, original research findings, and policy in this field. In the short-to-medium term, the Genomic Medicine Alliance aims to promote research collaborations between developed and developing countries and to organize educational activities in the field of genomic medicine. In the longer term, it aspires to become a focal point for global collaboration in the field of genomic medicine while helping to pave the way for a smoother transition from genomics research to genomic medicine.

Trust is a ubiquitous term used in emerging technology (e.g., Big Data, precision medicine), innovation policy, and governance literatures in particular. But what exactly is trust? Even though trust is considered a critical requirement for the successful deployment of precision medicine initiatives, nonetheless, there is a need for further conceptualization with regard to what qualifies as trust, and what factors might establish and sustain trust in precision medicine, predictive analytics, and large-scale biology. These new fields of 21st century medicine and health often deal with the “futures” and hence, trust gains a temporal and ever-present quality for both the present and the futures anticipated by new technologies and predictive analytics. We address these conceptual gaps that have important practical implications in the way we govern risk and unknowns associated with emerging technologies in biology, medicine, and health broadly. We provide an in-depth conceptual analysis and an operative definition of trust dynamics in precision medicine. In addition, we identify three main types of “trust facilitators”: (1) technical, (2) ethical, and (3) institutional. This three-dimensional framework on trust is necessary to building and maintaining trust in 21st century knowledge-based innovations that governments and publics invest for progressive societal change, development, and sustainable prosperity. Importantly, we analyze, identify, and deliberate on the dimensions of precision medicine and large-scale biology that have carved out trust as a pertinent tool to its success. Moving forward, we propose a “points to consider” on how best to enhance trust in precision medicine and predictive analytics. ISSN:1536-2310 ISSN:1557-8100

Emerging trends in pervasive computing and medical informatics are creating the possibility for large-scale collection, sharing, aggregation and analysis of unprecedented volumes of data, a phenomenon commonly known as big data. In this contribution, we review the existing scientific literature on big data approaches to dementia, as well as commercially available mobile-based applications in this domain. Our analysis suggests that big data approaches to dementia research and care hold promise for improving current preventive and predictive models, casting light on the etiology of the disease, enabling earlier diagnosis, optimizing resource allocation, and delivering more tailored treatments to patients with specific disease trajectories. Such promissory outlook, however, has not materialized yet, and raises a number of technical, scientific, ethical, and regulatory challenges. This paper provides an assessment of these challenges and charts the route ahead for research, ethics, and policy., Frontiers in Medicine, 5, ISSN:2296-858X

This opionion paper is published on Elephant in the lab – a blog journal on science policy. It is part of a series of articles analysing the meaning and future of scientific impact. Follow the blog: http://www.elephantinthelab.org/ – Twitter: @EITL_blog

Aims: This study reports on the attitudes of 179 Italian Medical Students to direct-to-consumer genetic test and to participation in research practices. Methods: Data were collected using a self-completion online questionnaire sent to 380 medical students at the faculty of Medicine of the Università Cattolica del Sacro Cuore in Rome, Italy. Questions pertained issues related to awareness and attitudes towards genetic testing, reactions to hypothetical results, and views about contributing to scientific research. Results: The response rate was 47.1%. Less than 50% of students were aware of DTC genetic test. Seventy-four percent of the sample were interested in undergoing DTC genetic test, and the main reason was being aware on genetic predisposition to diseases. Among those who were not willing to undergo a genetic test, the main reason was the lack of confidence in the results. In the hypothetical situations of an increased disease risk after undergoing DTC genetic testing, respondents would take actions to reduce that risk, while in the opposite scenario they would feel unaffected because of the probabilistic nature of the test. Conclusions: We reported a good level of awareness about DTC genetic test and a high interest in undergoing DTC genetic test in our sample. Nevertheless, opinions and reactions are strongly dependent by the hypothetical good or bad result that the test could provide and by the context whereby a genetic test could be performed. Respondents seem to be exposed to the risk of psychological harms, and a strong regulation regarding their use is required.

Digital epidemiology, also referred to as digital disease detection (DDD), is motivated by the same objectives as traditional epidemiology. However, DDD focuses on electronic data sources that emerged with the advent of information technology [1–3]. It draws on developments such as the widespread availability of Internet access, the explosive growth in mobile devices, and online sharing platforms, which constantly generate vast amounts of data containing health-related information, even though they are not always collected with public health as an objective. Furthermore, this novel approach builds on the idea that information relevant to public health is now increasingly generated directly by the population through their use of online services, without their necessarily having engaged with the health care system [4, 5]. By utilizing global real-time data, DDD promises accelerated disease outbreak detection, and examples of this enhanced timeliness in detection have already been reported in the literature. The most recent example is the 2014 Ebola virus outbreak in West Africa [6]. Reports of the emerging outbreak were detected by digital surveillance channels in advance of official reports. Furthermore, information gleaned by the various datasets can be used for several epidemiological purposes beyond early detection of disease outbreaks [7, 8], such as the assessment of health behavior and attitudes [4] and pharmacovigilance [9].