Pistoia Alliance | Collaborate to Innovate Life Science R&D

“We are a global, not-for-profit members’ organization working to lower barriers to innovation in life science and healthcare R&D through pre-competitive collaboration….

The Pistoia Alliance is a global, not-for-profit members’ organization conceived in 2007 and incorporated in 2009 by representatives of AstraZeneca, GSK, Novartis and Pfizer who met at a conference in Pistoia, Italy. This group shared the opinion that life science R&D was changing beyond recognition, and that organizations could not afford to ‘go it alone’ in order to integrate emerging technologies and continue to deliver life-changing therapies to patients. The Pistoia Alliance’s projects help to overcome common obstacles to innovation and to transform R&D – whether identifying the root causes of inefficiencies, working with regulators to adopt new standards, or helping researchers implement AI effectively. There are currently more than 100 member companies – ranging from global organisations, to medium enterprises, to start-ups, to individuals – collaborating as equals on projects that generate value for the worldwide life sciences community….”

Europe hints at patent grab from Big Pharma – POLITICO

“Ever so softly, European politicians are beginning to voice a once unthinkable threat by suggesting they could snatch patents from drug companies to make up for massive shortfalls in the supply of coronavirus vaccines.

Big Pharma businesses have for many years regarded EU countries as unquestioningly loyal allies over intellectual property rights in the international trade arena. The EU could always be relied upon to defend U.S., Japanese and European drugmakers from poor nations in Africa and South Asia that have long wanted the recipe of critical medicines to be handed over to generic manufacturers.

But fury over the inability of companies to deliver on contracts amid the COVID-19 pandemic means that now even European politicians, from the Italian parliament to German Economy Minister Peter Altmaier, are arguing, albeit cautiously, that patents may no longer be as sacrosanct as they once were….”

Full article: Pharmaceutical industry-authored preprints: scientific and social media impact

Abstract

Aim: Non–peer-reviewed manuscripts posted as preprints can be cited in peer-reviewed articles which has both merits and demerits. International Committee of Medical Journal Editors guidelines mandate authors to declare preprints at the time of manuscript submission. We evaluated the trends in pharma-authored research published as preprints and their scientific and social media impact by analyzing citation rates and altmetrics.

Research design and methods: We searched EuroPMC, PrePubMed bioRxiv and MedRxiv for preprints submitted by authors affiliated with the top 50 pharmaceutical companies from inception till June 15, 2020. Data were extracted and analyzed from the search results. The number of citations for the preprint and peer-reviewed versions (if available) were compiled using the Publish or Perish software (version 1.7). Altmetric score was calculated using the “Altmetric it” online tool. Statistical significance was analyzed by Wilcoxon rank-sum test.

Results: A total of 498 preprints were identified across bioRxiv (83%), PeerJ (5%), F1000Research (6%), Nature Proceedings (3%), Preprint.org (3%), Wellcome Open Research preprint (0.2%) and MedRxiv (0.2%) servers. Roche, Sanofi and Novartis contributed 56% of the retrieved preprints. The median number of citations for the included preprints was 0 (IQR =1, Min-Max =0-45). The median number of citations for the published preprints and unpublished preprints was 0 for both (IQR =1, Min-Max =0-25 and IQR =1, Min-Max =0-45, respectively; P?=?.091). The median Altmetric score of the preprints was 4 (IQR =10.5, Min-Max =0-160).

Conclusion: Pharma-authored research is being increasingly published as preprints and is also being cited in other peer-reviewed publications and discussed in social media.

Ten principles for data sharing and commercialization | Journal of the American Medical Informatics Association | Oxford Academic

Abstract:  Digital medical records have enabled us to employ clinical data in many new and innovative ways. However, these advances have brought with them a complex set of demands for healthcare institutions regarding data sharing with topics such as data ownership, the loss of privacy, and the protection of the intellectual property. The lack of clear guidance from government entities often creates conflicting messages about data policy, leaving institutions to develop guidelines themselves. Through discussions with multiple stakeholders at various institutions, we have generated a set of guidelines with 10 key principles to guide the responsible and appropriate use and sharing of clinical data for the purposes of care and discovery. Industry, universities, and healthcare institutions can build upon these guidelines toward creating a responsible, ethical, and practical response to data sharing.

 

Open Call Webinar – Peer Learning Network for Data Collaborations | Register – Contact information

“The Open Data Institute has partnered with Microsoft to launch its Open Data Campaign, which aims to address the data divide and help organisations of all sizes to realise the benefits of data and the new technologies it powers. 

 

As part of the campaign, we’re launching a peer learning network that will convene organisations collaborating around data, providing them with financial and other support from the ODI and Microsoft. Ultimately this will enable them to more effectively address the challenges they face. 

 

On Thursday 29 October 2020, 9:00am PDT/ 4:00pm GMT / 5:00pm CET, join us for a live webinar to learn more about the peer learning network opportunity. We will go over the open call for applications in more detail and provide an opportunity for attendees to ask any related questions before the application deadline (17 November 2020 at 11:59pm PST / 18 November 7:59am GMT (8:59am CET). …”

Microsoft and the Open Data Institute join together to launch a Peer Learning Network for Data Collaborations – Microsoft on the Issues

“Today, in partnership with the Open Data Institute (ODI), we are delighted to announce an open call for participation in a new Peer Learning Network for Data Collaborations. Peer learning networks are an important tool to foster the exchange of knowledge and help participants learn from one another so they can more effectively address the challenges they face.

In April, with the launch of Microsoft’s Open Data Campaign, we committed to putting open and shared data into practice by addressing specific challenges through data collaborations. For a data collaboration to achieve its goals, there are many factors that must come together successfully. Oftentimes, this process can be incredibly challenging. From aligning on key outcomes and data use agreements to preparing datasets for use and analysis, these considerations require time and extensive coordination….

Awardees will have the opportunity to:

receive up to £20,000 for their time over the six months of the peer learning network
learn about and receive guidance from the ODI and Microsoft on different technical approaches, governance mechanisms, and other means for managing data collaborations
connect with peers also working on these challenges

For the purpose of the Peer Learning Network, data collaborations are defined as:

involving a collaboration of companies, research institutions, non-profits, and/or government entities
addressing a clear societal or business-related challenge
are working to make their data as open as possible in the context of the collaboration (collaborations working with restrictions related to privacy or commercial sensitivity are encouraged to apply)
ultimately demonstrate increased access to, and/or meaningful use of, data in reaching the specific goal …”

Clinical trials sponsored by industry and other private organizations

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.

 

Industry Report Reveals Challenges among Researchers and Research Office Leaders during COVID-19

“Ex Libris, a ProQuest company, is pleased to announce the publication of its annual study on the challenges that academic researchers face, the priorities of research office leaders, and key opportunities for research offices and libraries to support scholarship at institutions of higher education.

The study was commissioned by Ex Libris and conducted by Alterline, an independent research agency. The report presents findings from a survey of 314 researchers across a range of disciplines and 101 senior members of research offices in the United States, the United Kingdom, and Australia….

Senior members of research offices want to strengthen relationships with the library. The top areas of collaboration between the research office and the library consist of open-access compliance (noted by 64% of respondents), the tracking of publications by the institution’s researchers (46%), and the updating of researcher profiles (32%).
Researchers’ support for open access is growing. Before COVID-19, 72% of researchers viewed open access favorably, and 18% now report that they view open access more positively since the onset of COVID-19….”

Support Centre for Data Sharing

“The?“Support Centre for Data Sharing” (SCDS)?is a new initiative funded by the European Commission to further support the development of the?Digital Single Market. Our objective is to facilitate data sharing, i.e. transactions in which data held by public sector or private sector are made available to other organisations (public or private) for use and re-use. Data sharing can happen in exchange for payment (or other reward) or for free. Success of data sharing depends on practices, technology, cultural elements and legal frameworks that are relevant to sharing any kind of information digitally, between individuals or organisations. …”

Computational social science: Obstacles and opportunities | Science

“An alternative has been to use proprietary data collected for market research (e.g., Comscore, Nielsen), with methods that are sometimes opaque and a pricing structure that is prohibitive to most researchers.

We believe that this approach is no longer acceptable as the mainstay of CSS, as pragmatic as it might seem in light of the apparent abundance of such data and limited resources available to a research community in its infancy. We have two broad concerns about data availability and access.

First, many companies have been steadily cutting back data that can be pulled from their platforms (5). This is sometimes for good reasons—regulatory mandates (e.g., the European Union General Data Protection Regulation), corporate scandal (Cambridge Analytica and Facebook)—however, a side effect is often to shut down avenues of potentially valuable research. The susceptibility of data availability to arbitrary and unpredictable changes by private actors, whose cooperation with scientists is strictly voluntary, renders this system intrinsically unreliable and potentially biased in the science it produces.

Second, data generated by consumer products and platforms are imperfectly suited for research purposes (6). Users of online platforms and services may be unrepresentative of the general population, and their behavior may be biased in unknown ways. Because the platforms were never designed to answer research questions, the data of greatest relevance may not have been collected (e.g., researchers interested in information diffusion count retweets because that is what is recorded), or may be collected in a way that is confounded by other elements of the system (e.g., inferences about user preferences are confounded by the influence of the company’s ranking and recommendation algorithms). The design, features, data recording, and data access strategy of platforms may change at any time because platform owners are not incentivized to maintain instrumentation consistency for the benefit of research.

For these reasons, research derived from such “found” data is inevitably subject to concerns about its internal and external validity, and platform-based data, in particular, may suffer from rapid depreciation as those platforms change (7). Moreover, the raw data are often unavailable to the research community owing to privacy and intellectual property concerns, or may become unavailable in the future, thereby impeding the reproducibility and replication of results….

Despite the limitations noted above, data collected by private companies are too important, too expensive to collect by any other means, and too pervasive to remain inaccessible to the public and unavailable for publicly funded research (8). Rather than eschewing collaboration with industry, the research community should develop enforceable guidelines around research ethics, transparency, researcher autonomy, and replicability. We anticipate that many approaches will emerge in coming years that will be incentive compatible for involved stakeholders….

Privacy-preserving, shared data infrastructures, designed to support scientific research on societally important challenges, could collect scientifically motivated digital traces from diverse populations in their natural environments, as well as enroll massive panels of individuals to participate in designed experiments in large-scale virtual labs. These infrastructures could be driven by citizen contributions of their data and/or their time to support the public good, or in exchange for explicit compensation. These infrastructures should use state-of-the-art security, with an escalation checklist of security measures depending on the sensitivity of the data. These efforts need to occur at both the university and cross-university levels. Finally, these infrastructures should capture and document the metadata that describe the data collection process and incorporate sound ethical principles for data collection and use….”