Biosecurity in an age of open science

Smith, James; Sandbrink, Jonas B.

doi:10.1371/journal.pbio.3001600

Cited by 33 publications

(19 citation statements)

References 67 publications

(69 reference statements)

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“…(87) Possible coordination among preprint servers for screening research and opportunities to work with funding organisations and researchers to increase their longer-term functionality. (18,94) There is acceptance that preprints offer a way to present early findings of research into the public domain, openly and transparently. The role of preprints is merely part of the process to reaching a peer reviewed publication.…”

Section: Discussionmentioning

confidence: 99%

The use and acceptability of preprints in health and social care settings: a scoping review

Blatch-Jones¹,

Saucedo²,

Giddins³

2023

Preprint

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Background: Preprints are open and accessible scientific manuscript or report that has not been submitted to a peer reviewed journal. The value and importance of preprints has grown since its contribution during the public health emergency of the COVID-19 pandemic. Funders and publishers are establishing their position on the use of preprints, in grant applications and publishing models. However, the evidence supporting the use and acceptability of preprints varies across funders, publishers, and researchers. The purpose of this scoping review was to explore the current evidence on the use and acceptability of preprints by publishers, funders, and the research community throughout the research lifecycle.Methods: A scoping review was undertaken with no study or language limits. The search strategy was limited to the last five years (2017-2022) to capture changes influenced by COVID-19 (e.g., accelerated use and role of preprints in research). The review included international literature, including grey literature, and two databases were searched: Scopus and Web of Science (24 August 2022). Results: 379 titles and abstracts and 193 full text articles were assessed for eligibility. Ninety-eight articles met eligibility criteria and were included for full extraction. For barriers and challenges, 26 statements were grouped under four main themes (e.g., volume/growth of publications, quality assurance/trustworthiness, risks associated to credibility, and validation). For benefits and value, 34 statements were grouped under six themes (e.g., openness/transparency, increased visibility/credibility, open review process, open research, democratic process/systems, increased productivity/opportunities).Conclusions: Preprints provide opportunities for rapid dissemination but there is a need for clear policies and guidance from journals, publishers, and funders. Cautionary measures are needed to maintain the quality and value of preprints, paying particular attention to how findings are translated to the public. More research is needed to address some of the uncertainties addressed in this review.

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Section: Discussionmentioning

confidence: 99%

The use and acceptability of preprints in health and social care settings: a scoping review

Blatch-Jones¹,

Saucedo²,

Giddins³

2023

Preprint

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“…It should be noted, however, that by releasing all methodological details and data in research fields such as viral engineering, where a dual use cannot be excluded, open science could increase biosecurity risk. Implementing access-controlled repositories, application programming interfaces, and a biosecurity risk assessment in the planning phase (i.e., by preregistration) could mitigate this threat [ 114 ].…”

Section: Discussionmentioning

confidence: 99%

A guide to open science practices for animal research

et al. 2022

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Translational biomedical research relies on animal experiments and provides the underlying proof of practice for clinical trials, which places an increased duty of care on translational researchers to derive the maximum possible output from every experiment performed. The implementation of open science practices has the potential to initiate a change in research culture that could improve the transparency and quality of translational research in general, as well as increasing the audience and scientific reach of published research. However, open science has become a buzzword in the scientific community that can often miss mark when it comes to practical implementation. In this Essay, we provide a guide to open science practices that can be applied throughout the research process, from study design, through data collection and analysis, to publication and dissemination, to help scientists improve the transparency and quality of their work. As open science practices continue to evolve, we also provide an online toolbox of resources that we will update continually.

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“…While this is not an issue affecting all types of patient data equally, it would also be an error not to consider edge cases (e.g., data on infective agents) given the potential risks entailed. 114 Similarly, a lack of quality control or unknown biases in public data may lead to undetected, undesirable issues in models built using these datasets. Problems have often emerged after external auditing, which may not be easily detectable from researchers with less domain-specific knowledge (e.g., ML researchers using public imaging data).…”

Section: Must Have Qualitiesmentioning

confidence: 99%

“…This issue variably affects preprint servers because of different policies employed, but these may not be well known to the general public accessing the papers. 114 …”

Section: Must Have Qualitiesmentioning

confidence: 99%

Must-have Qualities of Clinical Research on Artificial Intelligence and Machine Learning

Koçak¹,

Cuocolo²,

Santos³

et al. 2023

Balkan Med J

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In the field of computer science, known as artificial intelligence, algorithms imitate reasoning tasks that are typically performed by humans. The techniques that allow machines to learn and get better at tasks such as recognition and prediction, which form the basis of clinical practice, are referred to as machine learning, which is a subfield of artificial intelligence. The number of artificial intelligence-and machine learnings-related publications in clinical journals has grown exponentially, driven by recent developments in computation and the accessibility of simple tools. However, clinicians are often not included in data science teams, which may limit the clinical relevance, explanability, workflow compatibility, and quality improvement of artificial intelligence solutions. Thus, this results in the language barrier between clinicians and artificial intelligence developers. Healthcare practitioners sometimes lack a basic understanding of artificial intelligence research because the approach is difficult for non-specialists to understand. Furthermore, many editors and reviewers of medical publications might not be familiar with the fundamental ideas behind these technologies, which may prevent journals from publishing high-quality artificial intelligence studies or, worse still, could allow for the publication of low-quality works. In this review, we aim to improve readers’ artificial intelligence literacy and critical thinking. As a result, we concentrated on what we consider the 10 most important qualities of artificial intelligence research: valid scientific purpose, high-quality data set, robust reference standard, robust input, no information leakage, optimal bias-variance tradeoff, proper model evaluation, proven clinical utility, transparent reporting, and open science. Before designing a study, one should have defined a sound scientific purpose. Then, it should be backed by a high-quality data set, robust input, and a solid reference standard. The artificial intelligence development pipeline should prevent information leakage. For the models, optimal bias-variance tradeoff should be achieved, and generalizability assessment must be adequately performed. The clinical value of the final models must also be established. After the study, thought should be given to transparency in publishing the process and results as well as open science for sharing data, code, and models. We hope this work may improve the artificial intelligence literacy and mindset of the readers.

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Biosecurity in an age of open science

Cited by 33 publications

References 67 publications

The use and acceptability of preprints in health and social care settings: a scoping review

The use and acceptability of preprints in health and social care settings: a scoping review

A guide to open science practices for animal research

Must-have Qualities of Clinical Research on Artificial Intelligence and Machine Learning

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