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Non-establishment or do-it-yourself (DIY) science involves individuals who may not have formal training conducting experiments outside of institutional settings. While prior scholarship has examined the motivations and values of those involved in the subset of DIY science known as "DIY biology," little research has addressed how these individuals navigate ethical issues in practice. The present study therefore aimed to understand how DIY biologists identify, approach, and resolve one particular ethical issue-biosafety-in their work. We conducted a digital ethnography of Just One Giant Lab (JOGL), the primary hub for DIY biology during the COVID-19 pandemic, and subsequently conducted interviews with individuals involved with JOGL. We found that JOGL was the first global DIY biology initiative to create a Biosafety Advisory Board and develop formal biosafety guidelines that applied to different groups in multiple locations. There was disagreement, however, regarding whether the Board should have an advisory role or provide mandatory oversight. We found that JOGL practiced ethical gatekeeping of projects that fell outside the limits defined by the Board. Our findings show that the DIY biology community recognized biosafety issues and tried to build infrastructure to facilitate the safe conduct of research. Supplementary Information: The online version contains supplementary material available at 10.1057/s41292-023-00301-2.
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A large and highly heterogeneous group of individuals conducts genetic and genomic research outside of traditional corporate and academic settings. They can be an important source of innovation, but their activities largely take place beyond the purview of existing regulatory systems for promoting safe and ethical practices. Historically the gene-targeting technology available for non-traditional genomic research has been limited, and therefore these activities have attracted little regulatory attention. New technologies such as CRISPR/Cas9, however, give nonconventional experimenters more extensive gene editing abilities at an unprecedented level of accessibility. The affordability and accessibility of these powerful technologies are raising questions about whether the current largely laissez-faire governance approach is adequate. This article recommends steps to enhance self-governance, including establishing umbrella organizations to represent community interests, creating a community IRB modelled on the DIYBio Ask a Safety Expert Service, and adopting an ethical obligation to report rogue experiments.
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As biomedical citizen science initiatives become more prevalent, the unique ethical issues that they raise are attracting policy attention. The ethical oversight of bottom-up biomedical citizen science projects that are designed and executed primarily or solely by members of the public is a significant concern because the federal rules that require ethical oversight of research by institutional review boards generally do not apply to such projects, creating what has been called an ethics gap. Working to close this gap, practitioners and scholars have considered new mechanisms of ethical oversight for biomedical citizen science. To date, however, participants' attitudes about ethics and oversight preferences have not been systematically examined. This information is useful to efforts to develop ethical oversight mechanisms because it provides a basis for evaluating the likely effectiveness of specific features of such mechanisms and their acceptability from the perspective of biomedical citizen scientists. Here, we report data from qualitative interviews with 35 stakeholders in bottom-up biomedical citizen science about their general ethics attitudes and preferences regarding ethical oversight. Interviewees described ten ethical priorities and endorsed oversight mechanisms that are voluntary, community-driven, and offer guidance. Conversely, interviewees rejected mechanisms that are mandatory, hierarchical, and inflexible. Applying these findings, we conclude that expert consultation and community review models appear to align well with ethical priorities and oversight preferences of many biomedical citizen scientists, although local conditions should guide the development and use of mechanisms in specific communities.
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The speed and scale of the COVID-19 pandemic has highlighted the limits of current health systems and the potential promise of non-establishment research such as "DIY" research. We consider one example of how DIY research is responding to the pandemic, discuss the challenges faced by DIY research more generally, and suggest that a "trust architecture" should be developed now to contribute to successful future DIY efforts.
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COVID-19/terapia , Difusión de Innovaciones , Autoeficacia , Apoyo Social , COVID-19/psicología , HumanosRESUMEN
OBJECTIVES: There is an association between the FcGRIIIa polymorphism and the development of rheumatoid arthritis (RA). Studies in non-Hodgkin lymphoma demonstrated a relationship between the FcGRIIIa polymorphism and response to anti-CD20 therapies. However, there are currently no published studies evaluating the relationship between this polymorphism and therapeutic response to treatment with anti-CD20 agents such as rituximab in RA. We conducted a study to identify if the FcGRIIIa polymorphism is associated with rituximab efficacy in patients with RA. METHODS: Subjects with RA treated with rituximab (cases, n=158) or TNF-α antagonist (controls, n=390) were recruited from the Consortium of Rheumatology Researchers of North America. The FcGRIIIa variant was genotyped for all subjects and longitudinal patient outcomes were assessed using the clinical disease activity index (CDAI). We used a linear regression random effects model to estimate CDAI scores over time with multiple time points nested within patient. RESULTS: Similar changes in CDAI were observed across the three FcGRIIIa genotypes for the rituximab treated group (VV [4.56, SD 14.5]), VF (7.44, SD 14.9) and FF (4.75, SD 10.8) (p >0.05)] and the TNF-α antagonist therapy treated group [VV (5.12, SD 14.6), VF (6.77, SD 15.9), and FF (4.36, SD 18.2) (p >0.05). Overall, there were similar changes in CDAI at 6 months for rituximab (-5.91, SD 14.1) and anti-TNFs (-5.77, SD 15.5) (p >0.05). The FcGRIIIa genotype was not significantly associated (p=0.86) with treatment response in rituximab treated RA patients compared with TNF-α antagonist therapy treated patients. Baseline CDAI and number of prior biologics were significant predictors of clinical response over time. CONCLUSIONS: Our finding emphasises the idea that determinants of response to treatment are complex and may be dependent upon genetic and phenotypic interactions. Future studies should analyse the interaction between the FcGRIIIa gene, other neighbouring polymorphisms and other phenotypic and environmental factors.
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Anticuerpos Monoclonales de Origen Murino/uso terapéutico , Antirreumáticos/uso terapéutico , Artritis Reumatoide/tratamiento farmacológico , Polimorfismo Genético , Receptores de IgG/genética , Factor de Necrosis Tumoral alfa/antagonistas & inhibidores , Anciano , Artritis Reumatoide/diagnóstico , Artritis Reumatoide/genética , Artritis Reumatoide/inmunología , Estudios de Casos y Controles , Femenino , Genotipo , Humanos , Modelos Lineales , Masculino , Persona de Mediana Edad , Farmacogenética , Fenotipo , Rituximab , Índice de Severidad de la Enfermedad , Factores de Tiempo , Resultado del TratamientoRESUMEN
Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease. As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention's Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.