Information-Derived Mechanistic Hypotheses for Structural Cardiotoxicity

Adverse events resulting from drug therapy can be a cause of drug withdrawal, reduced and or restricted clinical use, as well as a major economic burden for society. To increase the safety of new drugs, there is a need to better understand the mechanisms causing the adverse events. One way to derive new mechanistic hypotheses is by linking data on drug adverse events with the drugs’ biological targets. In this study, we have used data mining techniques and mutual information statistical approaches to find associations between reported adverse events collected from the FDA Adverse Event Reporting System and assay outcomes from ToxCast, with the aim to generate mechanistic hypotheses related to structural cardiotoxicity (morphological damage to cardiomyocytes and/or loss of viability). Our workflow identified 22 adverse event-assay outcome associations. From these associations, 10 implicated targets could be substantiated with evidence from previous studies reported in the literature. For two of the identified targets, we also describe a more detailed mechanism, forming putative adverse outcome pathways associated with structural cardiotoxicity. Our study also highlights the difficulties deriving these type of associations from the very limited amount of data available

Open Data for Global Science

The global science system stands at a critical juncture. On the one hand, it is overwhelmed by a hidden avalanche of ephemeral bits that are central components of modern research and of the emerging ‘cyberinfrastructure’4 for e-Science.5 The rational management and exploitation of this cascade of digital assets offers boundless opportunities for research and applications. On the other hand, the ability to access and use this rising flood of data seems to lag behind, despite the rapidly growing capabilities of information and communication technologies (ICTs) to make much more effective use of those data. As long as the attention for data policies and data management by researchers, their organisations and their funders does not catch up with the rapidly changing research environment, the research policy and funding entities in many cases will perpetuate the systemic inefficiencies, and the resulting loss or underutilisation of valuable data resources derived from public investments. There is thus an urgent need for rationalised national strategies and more coherent international arrangements for sustainable access to public research data, both to data produced directly by government entities and to data generated in academic and not-for-profit institutions with public funding. In this chapter, we examine some of the implications of the ‘data driven’ research and possible ways to overcome existing barriers to accessibility of public research data. Our perspective is framed in the context of the predominantly publicly funded global science system. We begin by reviewing the growing role of digital data in research and outlining the roles of stakeholders in the research community in developing data access regimes. We then discuss the hidden costs of closed data systems, the benefits and limitations of openness as the default principle for data access, and the emerging open access models that are beginning to form digitally networked commons. We conclude by examining the rationale and requirements for developing overarching international principles from the top down, as well as flexible, common-use contractual templates from the bottom up, to establish data access regimes founded on a presumption of openness, with the goal of better capturing the benefits from the existing and future scientific data assets. The ‘Principles and Guidelines for Access to Research Data from Public Funding’ from the Organisation for Economic Cooperation and Development (OECD), reported on in another article by Pilat and Fukasaku,6 are the most important recent example of the high-level (inter)governmental approach. The common-use licenses promoted by the Science Commons are a leading example of flexible arrangements originating within the community. Finally, we should emphasise that we focus almost exclusively on the policy—the institutional, socioeconomic, and legal aspects of data access—rather than on the technical and management practicalities that are also important, but beyond the scope of this article

Screening out irrelevant cell-based models of disease

The common and persistent failures to translate promising preclinical drug candidates into clinical success highlight the limited effectiveness of disease models currently used in drug discovery. An apparent reluctance to explore and adopt alternative cell-and tissue-based model systems, coupled with a detachment from clinical practice during assay validation, contributes to ineffective translational research. To help address these issues and stimulate debate, here we propose a set of principles to facilitate the definition and development of disease-relevant assays, and we discuss new opportunities for exploiting the latest advances in cell-based assay technologies in drug discovery, including induced pluripotent stem cells, three-dimensional (3D) co-culture and organ-on-a-chip systems, complemented by advances in single-cell imaging and gene editing technologies. Funding to support precompetitive, multidisciplinary collaborations to develop novel preclinical models and cell-based screening technologies could have a key role in improving their clinical relevance, and ultimately increase clinical success rates

Geography of HFE C282Y and H63D mutations.

Hereditary hemochromatosis (HH) is a common autosomal recessive disorder causing inappropriate dietary iron absorption that affects North Europeans. HH is associated with the C282Y mutation of the HFE gene, and the H63D mutation to a lesser degree. Both mutations are abundant in Europe, with H63D also appearing in North Africa, the Middle East, and Asia. Emigration from Europe over the past 500 years has introduced C282Y and H63D to America, Australia, New Zealand, and South Africa in an essentially predictable fashion. The distinctive characteristics of the population genetics of HH are the confined racial distribution and high frequency in North European peoples. C282Y frequencies in North Europeans are typically between 5% and 10%, with homozygotes accounting for between 1/100 and 1/400 of these populations. The scarcity of the C282Y mutation in other populations accounts for the lack of HH in non-Europeans

Assessment of organoleptic postmortem inspection techniques for bovine offal

Objective: To evaluate organoleptic postmortem inspec-tion techniques for bovine livers and kidneys. Study design: At Australian export abattoirs, bovine liver and kidneys are assessed and graded by qualified meat inspectors during normal operations. Over a 12-month period at a large abattoir in eastern Australia during 1997 and 1998, a sample of these organs was reassessed independently using a range of pathological and microbiological methods. Agreement between routine inspection and independent assessment was evaluated using methods of inter-rater agreement. Results: A total of 944 livers and 1374 kidneys were included in the study. All of these organs had been classified during routine inspection. The authors examined 363 livers and 329 kidneys both grossly and histologically, including 36 livers and 14 kidneys that were also subjected to microbiological examination. All other organs were only examined grossly. There was only a moderate level of agreement between the routine and independent assessment methods. For livers, the percentage agreement was 80.2%, McNemar's test of symmetry 55.2 (3 degrees of freedom, P < 0.001) and kappa 0.63. For kidneys, the percentage agreement was 67.8%, McNemar's test of symmetry 9.9 (1df, P = 0.002) and kappa 0.35. Conclusions: The results reinforce concerns from a number of authors about organoleptic postmortem inspection. Risk assessment methodologies offer the opportunity to modify inspection techniques in a manner that is most relevant to current public health concerns