The scientific community is bustling with projects to make published results more reliable. Efforts are under way to establish checklists, to revamp training in experimental design, and even to fund disinterested scientists to replicate others' experiments. A more efficient strategy would be to rework current incentives to put less emphasis on high-impact publications, but those systems are entrenched, and public funders and universities are ill-prepared for that scale of change. To catalyse change, industry must step up to the plate. I have learned this first hand, as head of the Structural Genomics Consortium (SGC), a research charity funded by business, government and other charities. If more companies contributed funds and expertise to efforts such as ours, I believe it would create a system that rewards science that is both cutting-edge and reproducible.
Researchers on social media ask at what point replication efforts go from useful to wasteful. The problem of irreproducibility in science has gained widespread attention, but one aspect that is discussed less often is how to find the right balance between replicating findings and moving a field forward from well-established ones.
The 2016 GBSI Summit—"Research Reproducibility: Innovative Solutions to Drive Quality" welcomed premiere life science thought leaders, including Arizona State University biomarker researcher Joshua LaBaer, MD, PhD, and science correspondent and moderator Richard Harris (currently on leave from National Public Radio as a visiting scholar this spring at Arizona State University), to explore the driving forces and profound impacts behind the issues.
Finding a relevant reporting guideline for a study can be very difficult. Here we introduce a pilot experiment starting for some of the BMC-series journals which aims to overcome this issue.
Elemental Machines, which develops smart laboratory technology, launched a new suite of tools that that measure environmental variables such as temperature and humidity—both of which are not traditionally accounted for in scientific experiments. By “debugging” the lab environment, the company believes it can improve experimental reproducibility, therefore reducing the time and cost of marketing new drugs and therapies. Elemental Machines recently raised $2.5 million in seed capital to support the development of the new suite of tools, which is called the EM Suite.
Mistakes in peer-reviewed papers are easy to find but hard to fix, report David B. Allison and colleagues: "In the course of assembling weekly lists of articles in our field, we began noticing more peer-reviewed articles containing what we call substantial or invalidating errors. These involve factual mistakes or veer substantially from clearly accepted procedures in ways that, if corrected, might alter a paper's conclusions."