By shifting to electronic systems such as a robotic cloud lab’s platform, researchers would have a way of tracking the fine-grained details and providing them later on. Even if they could be found, many kept records in nonelectronic lab books and weren’t able to provide details. Often academic researchers had moved on from the original lab and were difficult to contact. Iorns described the difficulty that researchers working on the Reproducibility Project in cancer biology have had in tracking down the details of materials and methods in original studies. This record and precision makes it easier for protocols to be shared so experiments may be retested. Beyond making lab work more precise and efficient, researchers and lab founders alike believe that the automation could make their experiments more easily reproducible. And more recently “robotic cloud labs” have gone even further by offering a service in which researchers can send their protocols directly to a robot to carry out their experiment. And what better way to capture precise information than by using robots? Biomedical research has been shifting to using robots in labs for decades, particularly for experiments that require the same steps to be carried out many times over with precision (one example is a polymerase chain reaction, a technique used to multiply a piece of DNA into many copies.) Research labs can either purchase the robotic machines that do this themselves, or they can outsource to contract research organizations that have the machines. But there are smaller steps we can take to chip away at the causes of irreproducibility-for instance, by capturing more precise information about how experiments are conducted so they can be more easily reproduced. Resolving all the issues around reproducibility will likely require us to grapple with fundamental challenges in how we conduct scientific research. Iorns is also one of several team members working on the Reproducibility Project in cancer biology. What’s to blame for this huge problem? Causes range from the difficulty of recreating experiments that were never described in close detail to a scientific system that incentivizes researchers to cherry-pick results for publication, says Elizabeth Iorns, co-founder of Science Exchange, a platform that enables researchers to order experiments at contract labs. Recently, in an editorial in Science Translational Medicine, the executive vice president and chief medical officer at the pharmaceutical company Merck detailed and lamented the huge costs of relying on such a “shaky platform.” A study published by scientists at the biotechnology company Amgen in 2012 claimed that of 53 landmark preclinical research studies, only six could be successfully reproduced. The data outlining the problem is compelling: In 2015, the Reproducibility Project, an undertaking led by the Center for Open Science, conducted a study with hundreds of psychologists and found that fewer than half of 100 studies from high-ranking psychology journals could be reproduced (see a critical comment and reply for more). This makes it difficult to know which results we can confidently rely on, and which are spurious. Can experiments be repeated (or “reproduced”) to arrive at the same result? Evidence is piling up that the answer, all too often, is no. In recent years, there’s been increasing awareness of a problem across many scientific fields-the problem of reproducibility.
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