Suchergebnisse

There is growing concern about lack of scientific rigor and transparent reporting across many preclinical fields of biological research. Poor experimental design and lack of transparent reporting can result in conscious or unconscious experimental bias, producing results that are not replicable. The Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) public-private partnership with the U.S. Food and Drug Administration sponsored a consensus meeting of the Preclinical Pain Research Consortium for Investigating Safety and Efficacy (PPRECISE) Working Group. International participants from universities, funding agencies, government agencies, industry, and a patient advocacy organization attended. Reduction of publication bias, increasing the ability of others to faithfully repeat experimental methods, and increased transparency of data reporting were specifically discussed. Parameters deemed essential to increase confidence in the published literature were clear, specific reporting of an a priori hypothesis and definition of primary outcome measure. Power calculations and whether measurement of minimal meaningful effect size to determine these should be a core component of the preclinical research effort provoked considerable discussion, with many but not all agreeing. Greater transparency of reporting should be driven by scientists, journal editors, reviewers, and grant funders. The conduct of high-quality science that is fully reported should not preclude novelty and innovation in preclinical pain research, and indeed, any efforts that curtail such innovation would be misguided. We believe that to achieve the goal of finding effective new treatments for patients with pain, the pain field needs to deal with these challenging issues.

There is growing concern about lack of scientific rigor and transparent reporting across many preclinical fields of biological research. Poor experimental design and lack of transparent reporting can result in conscious or unconscious experimental bias, producing results that are not replicable. The Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) public-private partnership with the U.S. Food and Drug Administration sponsored a consensus meeting of the Preclinical Pain Research Consortium for Investigating Safety and Efficacy (PPRECISE) Working Group. International participants from universities, funding agencies, government agencies, industry, and a patient advocacy organization attended. Reduction of publication bias, increasing the ability of others to faithfully repeat experimental methods, and increased transparency of data reporting were specifically discussed. Parameters deemed essential to increase confidence in the published literature were clear, specific reporting of an a priori hypothesis and definition of primary outcome measure. Power calculations and whether measurement of minimal meaningful effect size to determine these should be a core component of the preclinical research effort provoked considerable discussion, with many but not all agreeing. Greater transparency of reporting should be driven by scientists, journal editors, reviewers, and grant funders. The conduct of high-quality science that is fully reported should not preclude novelty and innovation in preclinical pain research, and indeed, any efforts that curtail such innovation would be misguided. We believe that to achieve the goal of finding effective new treatments for patients with pain, the pain field needs to deal with these challenging issues.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.