Literature Review on Health Emigration in Rare Diseases-A Machine Learning Perspective

The article deals with one of the effects of health inequalities and gaps in access to treatments for rare diseases, namely health-driven emigration. The purpose of the paper is to systematize knowledge about the phenomenon of health emigration observed among families affected by rare diseases, for which reimbursed treatment is available, but only in selected countries. The topic proved to be niche; the issue of "health emigration in rare diseases" is an area for exploration. Therefore, the further analysis used text mining and machine learning methods based on a database selected based on keywords related to this issue. The results made it possible to systematize the guesses made by researchers in management and economic fields, to identify the most common keywords and thematic clusters around the perspective of the patient, drug manufacturer and treatment reimbursement decision-maker, and the perspective integrating all the others. Since the topic of health emigration was not directly addressed in the selected sources, the authors attempted to define the related concepts and discussed the importance of this phenomenon in managing the support system in rare diseases. Thus, they indicated directions for further research in this area.

Ethics approval in applications for open-access clinical trial data: An analysis of researcher statements to clinicalstudydatarequest.com

Although there are a number of online platforms for patient-level clinical trial data sharing from industry sponsors, they are not very harmonized regarding the role of local ethics approval in the research proposal review process. The first and largest of these platforms is ClinicalStudyDataRequest.com (CSDR), which includes over three thousand trials from thirteen sponsors including GlaxoSmithKline, Novartis, Roche, Sanofi, and Bayer. CSDR asks applicants to state whether they have received ethics approval for their research proposal, but in most cases does not require that they submit evidence of approval. However, the website does require that applicants without ethical approval state the reason it was not required. In order to examine the perspectives of researchers on this topic, we coded every response to that question received by CSDR between June 2014 and February 2017. Of 111 applicants who stated they were exempt from ethics approval, 63% mentioned de-identification, 57% mentioned the use of existing data, 33% referred to local or jurisdictional regulations, and 20% referred to the approvals obtained by the original study. We conclude by examining the experience of CSDR within the broader context of the access mechanisms and policies currently being used by other data sharing platforms, and discuss how our findings might be used to help clinical trial data providers design clear and informative access documents.

From promising molecules to orphan drugs: Early clinical drug development

Phase-1 (also known as "First-in-Man") clinical trials initiate the early clinical development of possible new medicines. Patient participation in this early phase of clinical trials is rather limited. After successful phase 1 trials, further phase 2 and phase 3 clinical trials in patients may lead to a marketing authorization. In the first 15 years of the European Union Orphan Drug Directive, 4.5% of the orphan drug applications were authorized. However, for many of these orphan drugs, no phase 1 studies were required, as these products were already well known pharmaceutical substances, with a clearly defined pharmacological profile. Furthermore, for 19 orphan drugs, already authorized by the European Medicines Agency (EMA), the original rare indication was extended to another rare disease and no phase 1 trials were needed. Phase 1 studies need to be performed in a sufficient number of volunteers even for medicinal products intended for a very limited number of patients.

Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff

Background

Significant efforts are underway within the biomedical research community to encourage sharing and reuse of research data in order to enhance research reproducibility and enable scientific discovery. While some technological challenges do exist, many of the barriers to sharing and reuse are social in nature, arising from researchers’ concerns about and attitudes toward sharing their data. In addition, clinical and basic science researchers face their own unique sets of challenges to sharing data within their communities. This study investigates these differences in experiences with and perceptions about sharing data, as well as barriers to sharing among clinical and basic science researchers.

Methods

Clinical and basic science researchers in the Intramural Research Program at the National Institutes of Health were surveyed about their attitudes toward and experiences with sharing and reusing research data. Of 190 respondents to the survey, the 135 respondents who identified themselves as clinical or basic science researchers were included in this analysis. Odds ratio and Fisher’s exact tests were the primary methods to examine potential relationships between variables. Worst-case scenario sensitivity tests were conducted when necessary.

Results and Discussion

While most respondents considered data sharing and reuse important to their work, they generally rated their expertise as low. Sharing data directly with other researchers was common, but most respondents did not have experience with uploading data to a repository. A number of significant differences exist between the attitudes and practices of clinical and basic science researchers, including their motivations for sharing, their reasons for not sharing, and the amount of work required to prepare their data.

Conclusions

Even within the scope of biomedical research, addressing the unique concerns of diverse research communities is important to encouraging researchers to share and reuse data. Efforts at promoting data sharing and reuse should be aimed at solving not only technological problems, but also addressing researchers’ concerns about sharing their data. Given the varied practices of individual researchers and research communities, standardizing data practices like data citation and repository upload could make sharing and reuse easier.