Moratorium on research intended to create novel potential pandemic pathogens

Future pandemics and the urge to 'do something'

Research with enhanced potential pandemic pathogens (ePPP) makes pathogens substantially more lethal, communicable, immunosuppressive or otherwise capable of triggering a pandemic. We briefly relay an existing argument that the benefits of ePPP research do not outweigh its risks and then consider why proponents of these arguments continue to confidently endorse them. We argue that these endorsements may well be the product of common cognitive biases-in which case they would provide no challenge to the argument against ePPP research. If the case against ePPP research is strong, the views of professional experts do little to move the needle in favour of ePPP research.

Reconsidering the need for gain-of-function research on enhanced potential pandemic pathogens in the post-COVID-19 era

The dual-use risk of infectious disease research using enhanced potential pandemic pathogens (ePPP), particularly gain-of-function (GOF) research, has been debated since 2011. As of now, research is supported on the condition that the research plan is reviewed and the actual experiment is supervised. However, the kinds of research conducted and what benefits they have brought to our society have not been adequately verified. Nevertheless, due to the COVID-19 pandemic that began at the end of 2019 and caused numerous deaths and wide economic disruption, the importance of infectious disease control from an international perspective has been recognized. Although complete control of the pandemic is still far off, positive signs include generating epidemiological trends based on genome analysis, therapeutic drug and vaccine development, clinical patient management, and public health policy interventions. In this context, the time has come to reconsider the true significance of GOF research on ePPP and the state of research governance in the post-COVID-19 era. In particular, the risks of such research are clearer than before, whereas its benefits seem less apparent. In this paper, we summarize the history of discussions on such GOF research, its significance in the light of the current COVID-19 pandemic, and the direction we shall take in the future.

Reconciling Regulation with Scientific Autonomy in Dual-Use Research

In debates over the regulation of communication related to dual-use research, the risks that such communication creates must be weighed against against the value of scientific autonomy. The censorship of such communication seems justifiable in certain cases, given the potentially catastrophic applications of some dual-use research. This conclusion however, gives rise to another kind of danger: that regulators will use overly simplistic cost-benefit analysis to rationalize excessive regulation of scientific research. In response to this, we show how institutional design principles and normative frameworks from free speech theory can be used to help extend the argument for regulating dangerous dual-use research beyond overly simplistic cost-benefit reasoning, but without reverting to an implausibly absolutist view of scientific autonomy.

Deep learning-based real-time detection of novel pathogens during sequencing

Novel pathogens evolve quickly and may emerge rapidly, causing dangerous outbreaks or even global pandemics. Next-generation sequencing is the state of the art in open-view pathogen detection, and one of the few methods available at the earliest stages of an epidemic, even when the biological threat is unknown. Analyzing the samples as the sequencer is running can greatly reduce the turnaround time, but existing tools rely on close matches to lists of known pathogens and perform poorly on novel species. Machine learning approaches can predict if single reads originate from more distant, unknown pathogens but require relatively long input sequences and processed data from a finished sequencing run. Incomplete sequences contain less information, leading to a trade-off between sequencing time and detection accuracy. Using a workflow for real-time pathogenic potential prediction, we investigate which subsequences already allow accurate inference. We train deep neural networks to classify Illumina and Nanopore reads and integrate the models with HiLive2, a real-time Illumina mapper. This approach outperforms alternatives based on machine learning and sequence alignment on simulated and real data, including SARS-CoV-2 sequencing runs. After just 50 Illumina cycles, we observe an 80-fold sensitivity increase compared to real-time mapping. The first 250 bp of Nanopore reads, corresponding to 0.5 s of sequencing time, are enough to yield predictions more accurate than mapping the finished long reads. The approach could also be used for screening synthetic sequences against biosecurity threats.

Animal Models for Influenza Research: Strengths and Weaknesses

Influenza remains one of the most significant public health threats due to its ability to cause high morbidity and mortality worldwide. Although understanding of influenza viruses has greatly increased in recent years, shortcomings remain. Additionally, the continuous mutation of influenza viruses through genetic reassortment and selection of variants that escape host immune responses can render current influenza vaccines ineffective at controlling seasonal epidemics and potential pandemics. Thus, there is a knowledge gap in the understanding of influenza viruses and a corresponding need to develop novel universal vaccines and therapeutic treatments. Investigation of viral pathogenesis, transmission mechanisms, and efficacy of influenza vaccine candidates requires animal models that can recapitulate the disease. Furthermore, the choice of animal model for each research question is crucial in order for researchers to acquire a better knowledge of influenza viruses. Herein, we reviewed the advantages and limitations of each animal model-including mice, ferrets, guinea pigs, swine, felines, canines, and non-human primates-for elucidating influenza viral pathogenesis and transmission and for evaluating therapeutic agents and vaccine efficacy.

Interpretable detection of novel human viruses from genome sequencing data

Viruses evolve extremely quickly, so reliable methods for viral host prediction are necessary to safeguard biosecurity and biosafety alike. Novel human-infecting viruses are difficult to detect with standard bioinformatics workflows. Here, we predict whether a virus can infect humans directly from next-generation sequencing reads. We show that deep neural architectures significantly outperform both shallow machine learning and standard, homology-based algorithms, cutting the error rates in half and generalizing to taxonomic units distant from those presented during training. Further, we develop a suite of interpretability tools and show that it can be applied also to other models beyond the host prediction task. We propose a new approach for convolutional filter visualization to disentangle the information content of each nucleotide from its contribution to the final classification decision. Nucleotide-resolution maps of the learned associations between pathogen genomes and the infectious phenotype can be used to detect regions of interest in novel agents, for example, the SARS-CoV-2 coronavirus, unknown before it caused a COVID-19 pandemic in 2020. All methods presented here are implemented as easy-to-install packages not only enabling analysis of NGS datasets without requiring any deep learning skills, but also allowing advanced users to easily train and explain new models for genomics.

The Social Risks of Science

Many instances of scientific research impose risks, not just on participants and scientists but also on third parties. This class of social risks unifies a range of problems previously treated as distinct phenomena, including so-called bystander risks, biosafety concerns arising from gain-of-function research, the misuse of the results of dual-use research, and the harm caused by inductive risks. The standard approach to these problems has been to extend two familiar principles from human subjects research regulations-a favorable risk-benefit ratio and informed consent. We argue, however, that these moral principles will be difficult to satisfy in the context of widely distributed social risks about which affected parties may reasonably disagree. We propose that framing these risks as political rather than moral problems may offer another way. By borrowing lessons from political philosophy, we propose a framework that unifies our discussion of social risks and the possible solutions to them.

The biosecurity benefits of genetic engineering attribution

Biology can be misused, and the risk of this causing widespread harm increases in step with the rapid march of technological progress. A key security challenge involves attribution: determining, in the wake of a human-caused biological event, who was responsible. Recent scientific developments have demonstrated a capability for detecting whether an organism involved in such an event has been genetically modified and, if modified, to infer from its genetic sequence its likely lab of origin. We believe this technique could be developed into powerful forensic tools to aid the attribution of outbreaks caused by genetically engineered pathogens, and thus protect against the potential misuse of synthetic biology.

Application of a Biologically Contained Reporter System To Study Gain-of-Function H5N1 Influenza A Viruses with Pandemic Potential

Understanding how animal influenza viruses can adapt to spread in humans is critical to prepare for, and prevent, new pandemics. However, working safely with pathogens that have pandemic potential requires tight regulation and the use of high-level physical and biological risk mitigation strategies to stop accidental loss of containment. Here, we used a biological containment system for influenza viruses to study strains with pandemic potential. The system relies on deletion of the essential HA gene from the viral genome and its provision by a genetically modified cell line, to which virus propagation is therefore restricted. We show that this method permits safe handling of these pathogens, including gain-of-function variants, without the risk of generating fully infectious viruses. Furthermore, we demonstrate that this system can be used to assess virus sensitivity to both approved and experimental drugs, as well as the antigenic profile of viruses, important considerations for evaluating prepandemic vaccine and antiviral strategies.

Natural adaptation of an antigenically novel avian influenza A virus (IAV) to be transmitted efficiently in humans has the potential to trigger a devastating pandemic. Understanding viral genetic determinants underlying adaptation is therefore critical for pandemic preparedness, as the knowledge gained enhances surveillance and eradication efforts, prepandemic vaccine design, and efficacy assessment of antivirals. However, this work has risks, as making gain-of-function substitutions in fully infectious IAVs may create a pathogen with pandemic potential. Thus, such experiments must be tightly controlled through physical and biological risk mitigation strategies. Here, we applied a previously described biological containment system for IAVs to a 2009 pandemic H1N1 strain and a highly pathogenic H5N1 strain. The system relies on deletion of the essential viral hemagglutinin (HA) gene, which is instead provided in trans, thereby restricting multicycle virus replication to genetically modified HA-complementing cells. In place of HA, a Renilla luciferase gene is inserted within the viral genome, and a live-cell luciferase substrate allows real-time quantitative monitoring of viral replication kinetics with a high dynamic range. We demonstrate that biologically contained IAV-like particles exhibit wild-type sensitivities to approved antivirals, including oseltamivir, zanamivir, and baloxavir. Furthermore, the inability of these IAV-like particles to genetically acquire the host-encoded HA allowed us to introduce gain-of-function substitutions in the H5 HA gene that promote mammalian transmissibility. Biologically contained “transmissible” H5N1 IAV-like particles exhibited wild-type sensitivities to approved antivirals, to the fusion inhibitor S20, and to neutralization by existing H5 monoclonal and polyclonal sera. This work represents a proof of principle that biologically contained IAV systems can be used to safely conduct selected gain-of-function experiments.

IMPORTANCE Understanding how animal influenza viruses can adapt to spread in humans is critical to prepare for, and prevent, new pandemics. However, working safely with pathogens that have pandemic potential requires tight regulation and the use of high-level physical and biological risk mitigation strategies to stop accidental loss of containment. Here, we used a biological containment system for influenza viruses to study strains with pandemic potential. The system relies on deletion of the essential HA gene from the viral genome and its provision by a genetically modified cell line, to which virus propagation is therefore restricted. We show that this method permits safe handling of these pathogens, including gain-of-function variants, without the risk of generating fully infectious viruses. Furthermore, we demonstrate that this system can be used to assess virus sensitivity to both approved and experimental drugs, as well as the antigenic profile of viruses, important considerations for evaluating prepandemic vaccine and antiviral strategies.

Rethinking Gain-of-Function Experiments in the Context of the COVID-19 Pandemic

Proponents of the use of gain-of-function (GOF) experiments with pathogens with pandemic potential (PPP) have argued that such experiments are necessary because they reveal important facets of pathogenesis and can be performed safely. Opponents of GOF experiments with PPP have argued that the risks outweigh the knowledge gained. The COVID-19 pandemic demonstrates the vulnerability of human societies to a new PPP, while also validating some arguments of both camps, questioning others, and suggesting the need to rethink how we approach this class of experiments.

Proponents of the use of gain-of-function (GOF) experiments with pathogens with pandemic potential (PPP) have argued that such experiments are necessary because they reveal important facets of pathogenesis and can be performed safely. Opponents of GOF experiments with PPP have argued that the risks outweigh the knowledge gained. The COVID-19 pandemic demonstrates the vulnerability of human societies to a new PPP, while also validating some arguments of both camps, questioning others, and suggesting the need to rethink how we approach this class of experiments.

The Silver Lining in Gain-of-Function Experiments with Pathogens of Pandemic Potential

Half a decade after the contentious "gain-of-function" (GOF) debate of 2012 that followed experimentation showing that highly pathogenic avian influenza virus could become mammalian transmissible, it is possible to reflect on the arguments for and against this type of research. In this essay we argue that GOF-type experiments have already produced important information not available from any other source while also providing information on pathogenesis and the requirements for optimizing strains for vaccine production. We analyze the moral arguments against GOF and find them less compelling for a variety of reasons ranging from the uncertainty of risk-benefit analysis to the reduced likelihood of accidents given the enhanced biosafety and biosecurity protocols currently in place. In our view the most important consequence of the GOF debate is that it brought renewed attention to biosafety protocols and ushered innovation in answering the relevant biological questions with greater safety. We conclude that GOF experiments should go forward provided that necessary biosafety and biosecurity conditions are in place.

A New Approach to Evaluating the Risk-Benefit Equation for Dual-Use and Gain-of-Function Research of Concern

In the twenty-first century, biology faces a problem that has previously vexed other disciplines such as physics, namely the prospect that its knowledge domain could be used to generate biological agents with altered properties that enhanced their weapon potential. Biological weapons bring the additional dimension that these could be self-replicating, easy to manufacture and synthesized with commonly available expertise. This resulted in increasing concern about the type of research done and communicated, despite the fact that such research often has direct societal benefits, bringing the dual-use dilemma to biology. The conundrum of dual use research of concern was crystallized by the so-called "gain-of-function" type of experiments in which avian influenza viruses were endowed with new properties in the laboratory such as increased virulence and the capacity for mammalian transmission. After more than a decade of intensive discussion and controversy involving biological experiments with dual-use potential, there is no consensus on the issue except for the need to carry out such experiments in the safest conditions possible. In this essay, we review the topic with the hindsight of several years and suggest that instead of prescribing prohibitions and experimental limitations the focus should be on the importance of scientific questions at hand. We posit that the importance of a scientific question for medical and scientific progress provides a benchmark to determine the acceptable level of risk in biological experimentation.

Ethical and Philosophical Considerations for Gain-of-Function Policy: The Importance of Alternate Experiments

The Department of Health and Human Services Framework for Guiding Funding Decisions about Proposed Research Involving Enhanced Potential Pandemic Pathogens (PPPs) contains a series of principles for governing the funding and conduct of gain-of-function (GOF) research resulting in the creation of PPPs. In this article, I address one of these principles, governing the replacement of GOF research with alternate experiments. I argue that the principle fails to address the way that different experiments can promote the same values as those promoted by GOF research resulting in PPPs. I then address some objections to this claim, and provide policy recommendations moving forward.

Why Do Exceptionally Dangerous Gain-of-Function Experiments in Influenza?

This chapter makes the case against performing exceptionally dangerous gain-of-function experiments that are designed to create potentially pandemic and novel strains of influenza, for example, by enhancing the airborne transmissibility in mammals of highly virulent avian influenza strains. This is a question of intense debate over the last 5 years, though the history of such experiments goes back at least to the synthesis of viable influenza A H1N1 (1918) based on material preserved from the 1918 pandemic. This chapter makes the case that experiments to create potential pandemic pathogens (PPPs) are nearly unique in that they present biosafety risks that extend well beyond the experimenter or laboratory performing them; an accidental release could, as the name suggests, lead to global spread of a virulent virus, a biosafety incident on a scale never before seen. In such cases, biosafety considerations should be uppermost in the consideration of alternative approaches to experimental objectives and design, rather than being settled after the fact, as is appropriately done for most research involving pathogens. The extensive recent discussion of the magnitude of risks from such experiments is briefly reviewed. The chapter argues that, while there are indisputably certain questions that can be answered only by gain-of-function experiments in highly pathogenic strains, these questions are narrow and unlikely to meaningfully advance public health goals such as vaccine production and pandemic prediction. Alternative approaches to experimental influenza virology and characterization of existing strains are in general completely safe, higher throughput, more generalizable, and less costly than creation of PPP in the laboratory and can thereby better inform public health. Indeed, virtually every finding of recent PPP experiments that has been cited for its public health value was predated by similar findings using safe methodologies. The chapter concludes that the unique scientific and public health value of PPP experiments is inadequate to justify the unique risks they entail and that researchers would be well-advised to turn their talents to other methodologies that will be safe and more rewarding scientifically.

Existential Risk and Cost-Effective Biosecurity

In the decades to come, advanced bioweapons could threaten human existence. Although the probability of human extinction from bioweapons may be low, the expected value of reducing the risk could still be large, since such risks jeopardize the existence of all future generations. We provide an overview of biotechnological extinction risk, make some rough initial estimates for how severe the risks might be, and compare the cost-effectiveness of reducing these extinction-level risks with existing biosecurity work. We find that reducing human extinction risk can be more cost-effective than reducing smaller-scale risks, even when using conservative estimates. This suggests that the risks are not low enough to ignore and that more ought to be done to prevent the worst-case scenarios.

Pricing Externalities to Balance Public Risks and Benefits of Research

How should scientific funders evaluate research with public health risks? Some risky work is valuable, but accepting too much risk may be ethically neglectful. Recent controversy over H5N1 influenza experiments has highlighted the difficulty of this problem. Advocates of the research claim the work is needed to understand pandemics, while opponents claim that accidents or misuse could release the very pandemic the work is meant to prevent. In an attempt to resolve the debate, the US government sponsored an independent evaluation that successfully produced a quantitative estimate of the risks involved, but only a qualitative estimate of the benefits. Given the difficulties of this “apples-to-oranges” risk-benefit analysis, what is the best way forward? Here we outline a general approach for balancing risks and benefits of research with public risks. Instead of directly comparing risks and benefits, our approach requires only an estimate of risk, which is then translated into a financial price. This estimate can be obtained either through a centrally commissioned risk assessment or by mandating liability insurance, which allows private markets to estimate the financial burden of risky research. The resulting price can then be included in the cost of the research, enabling funders to evaluate grants as usual—comparing the scientific merits of a project against its full cost to society. This approach has the advantage of aligning incentives by assigning costs to those responsible for risks. It also keeps scientific funding decisions in the hands of scientists, while involving the public on questions of values and risk experts on risk evaluation.

How should scientific funders evaluate research with public health risks? Some risky work is valuable, but accepting too much risk may be ethically neglectful. Recent controversy over H5N1 influenza experiments has highlighted the difficulty of this problem. The authors outline a general approach for balancing risks and benefits of research with public risks.

Does influenza pandemic preparedness and mitigation require gain-of-function research?

The risk and benefits of gain‐of‐function studies on influenza A have been widely debated since 2012 when the methods to create two respiratory transmissible H5N1 mutant isolates were published. Opponents of gain‐of‐function studies argue the biosecurity risk is unacceptable, while proponents cite potential uses for pandemic surveillance, preparedness and mitigation. In this commentary, we provide an overview of the background and applications of gain‐of‐function research and argue that the anticipated benefits have yet to materialize while the significant risks remain.

Underprotection of Unpredictable Statistical Lives Compared to Predictable Ones

Existing ethical discussion considers the differences in care for identified versus statistical lives. However, there has been little attention to the different degrees of care that are taken for different kinds of statistical lives. Here we argue that for a given number of statistical lives at stake, there will sometimes be different, and usually greater, care taken to protect predictable statistical lives, in which the number of lives that will be lost can be predicted fairly accurately, than for unpredictable statistical lives, where the lives are at stake because of a low-probability event, such that most likely no one will be affected by the decision but with low probability some lives will be at stake. One reason for this difference is the statistical challenge of estimating low probabilities, and in particular the tendency of common approaches to underestimate these probabilities. Another is the existence of rational incentives to treat unpredictable risks as if the probabilities were lower than they are. Some of these factors apply outside the pure economic context, to institutions, individuals, and governments. We argue that there is no ethical reason to treat unpredictable statistical lives differently from predictable statistical lives. Moreover, lives that are unpredictable from the perspective of an individual agent may become predictable when aggregated to the level of a societal decision. Underprotection of unpredictable statistical lives is a form of market failure that may need to be corrected by altering regulation, introducing compulsory liability insurance, or other social policies.

Viral factors in influenza pandemic risk assessment

The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk.

Gain-of-Function Research: Ethical Analysis

Gain-of-function (GOF) research involves experimentation that aims or is expected to (and/or, perhaps, actually does) increase the transmissibility and/or virulence of pathogens. Such research, when conducted by responsible scientists, usually aims to improve understanding of disease causing agents, their interaction with human hosts, and/or their potential to cause pandemics. The ultimate objective of such research is to better inform public health and preparedness efforts and/or development of medical countermeasures. Despite these important potential benefits, GOF research (GOFR) can pose risks regarding biosecurity and biosafety. In 2014 the administration of US President Barack Obama called for a "pause" on funding (and relevant research with existing US Government funding) of GOF experiments involving influenza, SARS, and MERS viruses in particular. With announcement of this pause, the US Government launched a "deliberative process" regarding risks and benefits of GOFR to inform future funding decisions-and the US National Science Advisory Board for Biosecurity (NSABB) was tasked with making recommendations to the US Government on this matter. As part of this deliberative process the National Institutes of Health commissioned this Ethical Analysis White Paper, requesting that it provide (1) review and summary of ethical literature on GOFR, (2) identification and analysis of existing ethical and decision-making frameworks relevant to (i) the evaluation of risks and benefits of GOFR, (ii) decision-making about the conduct of GOF studies, and (iii) the development of US policy regarding GOFR (especially with respect to funding of GOFR), and (3) development of an ethical and decision-making framework that may be considered by NSABB when analyzing information provided by GOFR risk-benefit assessment, and when crafting its final recommendations (especially regarding policy decisions about funding of GOFR in particular). The ethical and decision-making framework ultimately developed is based on the idea that there are numerous ethically relevant dimensions upon which any given case of GOFR can fare better or worse (as opposed to there being necessary conditions that are either satisfied or not satisfied, where all must be satisfied in order for a given case of GOFR to be considered ethically acceptable): research imperative, proportionality, minimization of risks, manageability of risks, justice, good governance (i.e., democracy), evidence, and international outlook and engagement. Rather than drawing a sharp bright line between GOFR studies that are ethically acceptable and those that are ethically unacceptable, this framework is designed to indicate where any given study would fall on an ethical spectrum-where imaginable cases of GOFR might range from those that are most ethically acceptable (perhaps even ethically praiseworthy or ethically obligatory), at one end of the spectrum, to those that are most ethically problematic or unacceptable (and thus should not be funded, or conducted), at the other. The aim should be that any GOFR pursued (and/or funded) should be as far as possible towards the former end of the spectrum.

The ethics of biosafety considerations in gain-of-function research resulting in the creation of potential pandemic pathogens

This paper proposes an ethical framework for evaluating biosafety risks of gain-of-function (GOF) experiments that create novel strains of influenza expected to be virulent and transmissible in humans, so-called potential pandemic pathogens (PPPs). Such research raises ethical concerns because of the risk that accidental release from a laboratory could lead to extensive or even global spread of a virulent pathogen. Biomedical research ethics has focused largely on human subjects research, while biosafety concerns about accidental infections, seen largely as a problem of occupational health, have been ignored. GOF/PPP research is an example of a small but important class of research where biosafety risks threaten public health, well beyond the small number of persons conducting the research.We argue that bioethical principles that ordinarily apply only to human subjects research should also apply to research that threatens public health, even if, as in GOF/PPP studies, the research involves no human subjects. Specifically we highlight the Nuremberg Code's requirements of 'fruitful results for the good of society, unprocurable by other methods', and proportionality of risk and humanitarian benefit, as broad ethical principles that recur in later documents on research ethics and should also apply to certain types of research not involving human subjects. We address several potential objections to this view, and conclude with recommendations for bringing these ethical considerations into policy development.

Biopreparedness in the Age of Genetically Engineered Pathogens and Open Access Science: An Urgent Need for a Paradigm Shift

Our systems, thinking, training, legislation, and policies are lagging far behind momentous changes in science, and leaving us vulnerable in biosecurity. Synthetic viruses and genetic engineering of pathogens are a reality, with a rapid acceleration of dual-use science. The public availability of methods for dual-use genetic engineering, coupled with the insider threat, poses an unprecedented risk for biosecurity. Case studies including the 1984 Rajneesh salmonella bioterrorism attack and the controversy over engineered transmissible H5N1 influenza are analyzed. Simple probability analysis shows that the risks of dual-use research are likely to outweigh potential benefits, yet this type of analysis has not been done to date. Many bioterrorism agents may also occur naturally. Distinguishing natural from unnatural epidemics is far more difficult than other types of terrorism. Public health systems do not have mechanisms for routinely considering bioterrorism, and an organizational culture that is reluctant to consider it. A collaborative model for flagging aberrant outbreak patterns and referral from the health to security sectors is proposed. Vulnerabilities in current approaches to biosecurity need to be reviewed and strengthened collaboratively by all stakeholders. New systems, legislation, collaborative operational models, and ways of thinking are required to effectively address the threat to global biosecurity.

Public engagement and the governance of gain-of-function research

The White House recently called for a "robust and broad deliberative process" to assess the risks and benefits of select gain-of-function studies, pausing current experiments and further grants until new federal policy on research funding and oversight is developed. At issue is whether and under what conditions laboratory studies that enhance the transmissibility and/or virulence of potential pandemic pathogens such as the H5N1 avian influenza virus should go forward. To date, professionals from medicine, public health, and the life sciences have dominated the debate, and each side of the controversy has cited the public's well-being as the principal motivator for their position. A major stakeholder, the general public, has not yet actively and systematically weighed in on the matter. This commentary considers in what form and with what benefit public participation may materialize in the current debate regarding the governance of gain-of-function research.