Abstract
The global biomedical research enterprise is driving substantial advances in medicine and healthcare. Yet it appears that the enterprise is rather wasteful, falling short of its true innovative potential. Suggested reasons are manifold and involve various stakeholders, such that there is no single remedy. In the present paper, I will argue that laboratories are the basic working units of the biomedical research enterprise and an important site of action for corrective intervention. Keeping laboratories relatively small will enable better training and mentoring of individual scientists, which in turn will yield better performance of the scientific workforce. The key premise of this argument is that people are at the heart of the successes and failures of biomedical research, yet the human dimension of science has been unduly neglected in practice. Renewed focus on the importance of laboratories and their constituent scientists is one promising approach to reducing waste and increasing efficiency within the biomedical research enterprise.
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Notes
Biomedical research is ultimately aimed at “establish[ing] a body of demonstrable, replicable facts and theory that contributes to knowledge and to the amelioration of human problems” (see www.hhs.gov/ohrp/archive/irb/irb_chapter5.htm; accessed 17 April 2015). Note that this is a broad definition and that ‘biomedical research’ as an umbrella term covers many different scientific fields and disciplines.
In the eyes of the ‘technophiles’ in science and society, any problem can be framed in chiefly technical or structural terms. Accordingly, rational refinement of technique and structure should yield solutions in every case. However, biomedical science is not impersonal, neutral and unfailingly objective—it is, after all, carried out by people. Furthermore, people are at the center of its ultimate mission, namely the improvement of health and wellbeing.
It is not clear how student participation in massive open online courses (MOOCs) relates to actual learning outcomes. In the words of one author: “We have terabytes of data about what students clicked and very little understanding of what changed in their heads” (Reich 2015).
Of course there will be differences in theoretical knowledge depending on the curriculum at a given educational institution, such that, for example, some students are more familiar with molecular biology versus human physiology and vice versa. Interdisciplinarity also means that physicists or engineers can move into biomedical research (e.g. pursuing biophysics or bioengineering in a medical context). For the purpose of the present discussion, I assume that all of these individuals have a basic understanding of scientific principles, physics, chemistry, math, etc. that is required for a career in research.
To some extent, this is simply based on the fact that much of biomedical research requires highly specialized skills and significant physical infrastructure, including sophisticated instruments. It would be very unusual for any one individual to amass all these skills and instruments. At the same time, there is sizable potential for primary research based on published data, much of which is largely untapped and unexplored, and this kind of research can be done by individual investigators without a laboratory (e.g. Blagosklonny 2007). Furthermore, meta-analyses and systematic reviews of existing studies (www.cochrane.org) do not require physical laboratories.
This is true at least for academic laboratories, on which the present discussion is focused. Industrial laboratories differ in some important characteristics and are more akin to ‘data production facilities’. See Ioannidis for an overview of the “extent of interest in research and its results from various perspectives” (Ioannidis 2014).
Laboratories vary considerably in terms of size and composition, a detailed discussion of which is beyond the scope of the present paper. See Carayol and Matt 2004, 2006; Conti and Liu 2015; Verbree et al. 2015, and references therein for research on how organizational factors determine the success and productivity of biomedical laboratories.
Several decades ago, “master” and “apprentice” were described as “terms that have long been used by scientists to cover various role relationships, including senior-and-junior collaborators as well as teacher-and-student” (Zuckerman 1977). Lexical definitions are as follows: apprentice (n.). c.1300, from Old French aprentiz “someone learning” […] from aprendre (Modern French apprendre) “to learn; to teach,” contracted from Latin apprehendere (see apprehend) “to grasp in the senses or mind” (based on entries in Douglas Harper’s Online Etymology Dictionary, www.etymonline.com; accessed 6 April 2015). An apprentice is also someone “who learns a job or skill by working for a fixed period of time for someone who is very good at that job or skill” (Merriam-Webster, www.merriam-webster.com; accessed 6 April 2015).
It is difficult to measure a laboratory’s contributions to biomedical research. As pointed out by Ioannidis et al., “Scientific productivity cannot be judged simply by number of publications. Publication of many low-quality articles is worse than is production of none.” (Ioannidis 2014). Nevertheless, publication output is still widely used to assess the ‘productivity’ of scientists and laboratories.
The US National Institute of General Medical Sciences “support[s] new projects in well-funded laboratories only if they are highly promising and distinct from other funded work in the laboratory. The Institute’s position is generally not to pay such applications. However, under special circumstances and with strong justification, staff may recommend overriding that position” (see http://www.nigms.nih.gov/Research/Application/Pages/NAGMSCouncilGuidelines.aspx; accessed 17 April 2015).
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Disclaimer: The author is an employee of Karolinska Institutet, with no further affiliations as of this writing. The views expressed in this paper are solely the personal views of the author and in no way intended to reflect those of his employer.
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Stroth, N. The Central Importance of Laboratories for Reducing Waste in Biomedical Research. Sci Eng Ethics 22, 1707–1716 (2016). https://doi.org/10.1007/s11948-015-9738-x
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DOI: https://doi.org/10.1007/s11948-015-9738-x