Science is not done by isolated individuals – Fundamental science

by Kleber Neves

How to organize the way of doing research?

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The story goes that the physicist Richard Feyman adopted a strategy for his research: he enumerated a list of important and unsolved problems, and every time he heard about a new method or finding, he checked whether that novelty contributed to the advancement of one of these topics.

But he was a theoretical physicist, and following that strategy in experimental biology is more difficult. Even if a recent result indicates a new path, or a new technique seems useful, equipment is expensive and acquiring competence in the techniques, establishing protocols and learning the tricks takes months or years of practice.

This results in greater specialization, which narrows the range of techniques and models available to each experimental scientist. As a result, the lines of research are not as guided by a fundamental question as they could be, but rather by the techniques and models already available, which are not necessarily the best for answering the question. To be guided solely by the question requires a greater variety of approaches than can fit in a single research group.

In this same logic, it is difficult for a typical laboratory to describe any scientific finding in its entirety on its own. Before the scientific community takes the initial findings as robust, they must be confirmed with other techniques, models, populations and approaches that, again, go beyond what a laboratory can accommodate. From a laboratory that tests treatments on cell lines, it is not expected to also confirm the findings in animal models or organize clinical trials in humans — that’s the subject of a recent article we published in the journal Nature.

If answering big questions or getting more consistent results requires a collective effort that goes beyond the limits of an isolated laboratory, then we need ways to facilitate the articulation of several laboratories around a shared objective. Biology is increasingly collaborative, but these collaborations tend to be punctual, not supported by an explicit and broader plan that orchestrates activities.

Having a more comprehensive plan between laboratories requires the adoption of other governance models that not only can increase bureaucracy, but will also require a balance between, on the one hand, the common mission, and, on the other, the autonomy of individual research groups . And this is a delicate question: one of the reasons that lead people to be academic scientists is precisely the freedom to conduct their own line of research.

In any case, “big science” is an increasingly common way of organizing research. Examples such as the European Center for Nuclear Research (CERN) or the Human Genome Project show that it is possible to carry out large-scale scientific projects, coordinating several research groups around common goals. The Brazilian Reproducibility Initiative, of which I am a part, is an example of this type of project, as well as other recent initiatives —Many Primates, Many Babies, Psychological Science Accelerator— focused on carrying out multicentric experiments.

A particular model is that of the Defense Advanced Research Projects Agency, DARPA, of the USA, known for the risky bets that gave rise to great advances such as the Internet and GPS, which serves as inspiration for several other North American agencies. DARPA has program directors, specialists in the research topic, who do not carry out the research itself: they have an executive role, coordinating and distributing funds for research carried out externally, in various institutions.

Importantly, “small” science, financed from individual research groups, and “large” science, with coordinated projects among several groups, are not the only possible formats, nor are they exclusive. Rather, science as a whole benefits from a variety of fostering and organizing models. An important and unanswered question in “science funding science” is in which cases and for which scientific questions these “big” models work in biology.

If we are to find better ways to organize science, we need data about these different models. Even if an initiative in a new fostering format will fail, we will learn from it perhaps even more than if it had worked. Some institutional experimentation already exists in this regard: recently, the Wellcome Trust launched the Wellcome Leap, whose objective is to be the “DARPA of health”. Each program is coordinated by a person who recruits the efforts of a dozen laboratories around the world. The ambitious challenges of these programs include personalized psychiatry, laboratory organ development and a platform to anticipate the transition of cells to a cancerous state.

Science is not done by isolated individuals. A way of organizing the production of scientific knowledge that recognizes this can contribute not only to dealing with problems of reproducibility, but also for us to be really guided by the big questions and problems, and for science to answer more questions that need be answered rather than simply limiting yourself to questions that we achieved responder.

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Kleber Neves is a biomedical, neuroscientist and meta-scientist. He is part of the coordinating team of the Brazilian Reproducibility Initiative at UFRJ.

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