“On November 18 and 19, 2019, the National Academies of Sciences, Engineering, and Medicine hosted a public workshop in Washington, DC, titled Sharing Clinical Trial Data: Challenges and a Way Forward. The workshop followed the release of the 2015 Institute of Medicine (IOM) consensus study report Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk, and was designed to examine the current state of clinical trial data sharing and reuse and to consider ways in which policy, technology, incentives, and governance could be leveraged to further encourage and enhance data sharing. This publication summarizes the presentations and discussions from the workshop.”
• Performing clinical trial registry searches for grey literature can decrease publication bias imputed into systematic reviews.
• 88.7% of critical care systematic reviews did not conduct clinical trial registry searches.
• 56% of systematic reviews that did not perform a trial registry search had at least 1 potentially relevant trial that was not included in their analysis….”
Abstract: The COVID-19 pandemic has unleashed a deluge of publications. For this cross-sectional study we compared the amount and reporting characteristics of COVID-19-related academic articles and preprints and the number of ongoing clinical trials and systematic reviews. To do this, we searched the PubMed database of citations and abstracts for published life science journals by using appropriate combinations of medical subject headings (MeSH terms), and the COVID-19 section of the MedRxiv and BioRxiv archives up to 20 May 2020 (21 weeks). In addition, we searched Clinicaltrial.gov, Chinese Clinical Trial Registry, EU Clinical Trials Register, and 15 other trial registers, as well as PROSPERO, the international prospective register of systematic reviews. The characteristics of each publication were extracted. Regression analyses and Z tests were used to detect publication trends and their relative proportions. A total of 3635 academic publications and 3805 preprints were retrieved. Only 8.6% (n = 329) of the preprints were already published in indexed journals. The number of academic and preprint publications increased significantly over time (p<0.001). Case reports (6% academic vs 0.9% preprints; p<0.001) and letters (17.4% academic vs 0.5% preprints; p<0.001) accounted for a greater share of academic compared to preprint publications. Differently, randomized controlled trials (0.22% vs 0.63%; p<0.001) and systematic reviews (0.08% vs 5%) made up a greater share of the preprints. The relative proportion of clinical studies registered at Clinicaltrials.gov, Chinese Clinical Trial Registry, and EU Clinical Trials Register was 57.9%, 49.5%, and 98.9%, respectively, most of which were still “recruiting”. PROSPERO listed 962 systematic review protocols. Preprints were slightly more prevalent than academic articles but both were increasing in number. The void left by the lack of primary studies was filled by an outpour of immediate opinions (i.e., letters to the editor) published in PubMed-indexed journals. Summarizing, preprints have gained traction as a publishing response to the demand for prompt access to empirical, albeit not peer-reviewed, findings during the present pandemic.
“A week or so ago, the head of the US Patent and Trademark Office, Andrei Iancu, who has been an extreme patent maximalist over the years, insisted that there was simply no evidence that patents hold back COVID treatments. This is a debate we’ve been having over the past few months. We’ve seen some aggressive actions by patent holders, and the usual crew of patent system supporters claiming, without evidence that no one would create a vaccine without much longer patent terms….
But just to highlight how ridiculous Iancu’s statements were, just days later, Pfizer, Regeneron, and BioNTech — all working on COVID treatments (including the antibody cocktail that President Trump took from Regeneron) — were all sued for patent infringement for their COVID treatments….
So, it certainly appears that patents are getting in the way of some COVID-19 treatments….”
“Moderna’s statement on intellectual property matters during the COVID-19 pandemic is very good, and should be matched by every manufacturer of a therapeutic, vaccine or diagnostic test. We also encourage Moderna to engage with the WHO COVID-19 Technology Access Pool (C-TAP) and the Medicines Patent Pool. Every manufacturer of a vaccine, drug or diagnostic should follow suit and publish the patents relevant to the technology, waive or license rights in those patents, and provide constructive transfer of manufacturing know-how and access to cell lines and data when necessary.
It is notable that Moderna has addressed both the pandemic and the post pandemic period, stating “to eliminate any perceived IP barriers to vaccine development during the pandemic period, upon request we are also willing to license our intellectual property for COVID-19 vaccines to others for the post pandemic period.” …”
Abstract: It is essential for the advancement of science that researchers share, reuse and reproduce each other’s workflows and protocols. The FAIR principles are a set of guidelines that aim to maximize the value and usefulness of research data, and emphasize the importance of making digital objects findable and reusable by others. The question of how to apply these principles not just to data but also to the workflows and protocols that consume and produce them is still under debate and poses a number of challenges. In this paper we describe a two-fold approach of simultaneously applying the FAIR principles to scientific workflows as well as the involved data. We apply and evaluate our approach on the case of the PREDICT workflow, a highly cited drug repurposing workflow. This includes FAIRification of the involved datasets, as well as applying semantic technologies to represent and store data about the detailed versions of the general protocol, of the concrete workflow instructions, and of their execution traces. We propose a semantic model to address these specific requirements and was evaluated by answering competency questions. This semantic model consists of classes and relations from a number of existing ontologies, including Workflow4ever, PROV, EDAM, and BPMN. This allowed us then to formulate and answer new kinds of competency questions. Our evaluation shows the high degree to which our FAIRified OpenPREDICT workflow now adheres to the FAIR principles and the practicality and usefulness of being able to answer our new competency questions.
Abstract: The present manuscript discussed some relevant aspects related to private sponsored clinical trials in dentistry. For decades, the academy has been the major responsible for research in Brazil. Distant from the trade sector, academic research has not always provided clear benefits to society. A key aspect of making benefits clearer is the process of scientific knowledge transference to decision-makers, which is, in fact, the ground of evidence-based dentistry. Although private sponsoring of clinical research seems to be part of the research progress of the business rates, investment in Brazil is lower than those observed in other countries. It is particularly important to understand that instead of creating its own rules, dentistry imported the high-quality standards originally designed for pharmaceutical studies. Therefore, it is critical to understand the original rules and how dental items are classified by regulatory agencies. In fact, knowledge about international and local regulation is a basic assumption in industry-sponsored research. Despite globalization, the identification of industry-sponsored studies through open access databases is still very hard and time-demanding. A common concern when conducting industry-sponsored trials is study biases. Fortunately, many relevant organizations, academic and industry groups, have been working seriously against that. Finally, for less experienced researchers, many aspects related to industry-sponsored studies – such as confidentiality, authorship, budget – are deeply discussed until a final version of the trial agreement can be written and signed, protecting all sides. In short, the scenario should be improved, but it already represents a nice opportunity for dental research.
“Hundreds of drug companies, medical device manufacturers, and universities owe the public a decade’s worth of missing data from clinical trials, federal officials warned last week.
New rules issued last week in the wake of a federal court ruling in February instructed clinical trial sponsors to submit missing data for trials conducted between 2007 and 2017 “as soon as possible.” For years, many trials conducted during that span have largely been exempted from reporting their data to ClinicalTrials.gov, a public database, meaning a decade of data about approved drugs and medical devices has never been made public.
The court’s ruling, and the federal government’s decision not to appeal it and instead to urge trial sponsors to submit the missing information, represent a major win for transparency advocates, who for years have fought to recover the decadelong gap in publicly available clinical trial data. …
The court ruling, and the resulting change in federal policy, come after years of reporting that has detailed how federal research agencies routinely fail to enforce their own rules regarding clinical trial transparency — which advocates say is critical for the public’s understanding of a given medicines’s safety and efficacy. …”