The important thing in science is not so much to obtain new facts as to discover new ways of thinking about them
W.L. Bragg
Vaccine design[1] is distinct from exploratory research in the fact that the outcome of the experiment has a predetermined quality. The goal is an increase in immunity of any form, or in other words; the outcome is positive only if the vaccine works. This is fundamentally different to exploratory research where the outcome of the experiment is of worth, regardless of the outcome, as long as the experimental approach is solid. For example, investigating whether amyloid β has a role in Alzheimer’s disease is inherently worthwhile, because both outcomes of the research are of interest. It is the knowledge that counts (Figure 1). In contrast, if an “in house”-made synthetic vaccine does not perform according to the hypothesis, there is no interest or follow-up in “why it does not perform”. Indeed, the number of unknown variables that generate the complexity of the immune system is poorly suited for empirical testing if the goal is to understand why a candidate vaccine does not perform; what would be the null-hypothesis? Whereas academic science is designed to increase any form of knowledge, vaccinology is designed to cure disease.
[1] Defined as “product design and testing”, not antigen discovery, which adheres more to the regular search for knowledge.

Figure 1 | Operating framework of academia and pharma The academic system and pharmaceutical companies (pharma) exhibit trivial (though not mutually exclusive) requirements to scientific conduct and success. Of note, in academia the requirements are mainly applicable on single scientists, whereas in pharma the requirements mainly apply to the overarching company.
The difference in scientific approach to vaccine design versus the search for knowledge can have a big impact on the motivation of the individual doing the experimentation. Motivation of scientists has been shown to be mostly self-intrinsic, the individual’s desire to adhere to their own internal standards, competencies and values285–287. Similarly, both high school students and graduate students that score high in intrinsic traits like self-efficacy and self-determination perform better288,289. How does this relate to the difference in scientific approach to vaccine design and knowledge gathering? Perceived self-efficacy is defined as people’s beliefs in their capabilities to produce desired effects by their actions290. Self-efficacy is developed by repeated experiences of perceived control, resulting in increased confidence291–293. For example, a scientist performing a typical vaccination experiment will perceive very little control over the success of the experimental outcome, since the variables of the complex immune system are unknown. In contrast, a scientist probing one variable of a complex and unknown immune system in an experiment may perceive control, because the goal is not success, but knowledge on the single testable variable. This difference is additionally illustrated by determining the sequence of experiments that are required to complete a line of research. Whereas the string of experiments for vaccine design is linear (chemistry, in vitro, in vivo, clinical) and irrespective of the outcome of intermediate experiments, the experiments for scientific knowledge are not predetermined and depend highly on intermediate results. Put differently, there is only one outcome for successful vaccine design, while the outcome of probing a scientific question is often unknown. As such, perceived control of scientists in the outcome of vaccine design is limited, resulting in decreased self-efficacy in the scientific method and potentially reduced motivation. In addition, the predefined experimental design in vaccine design abrogates the need for creativity. This is not trivial, since increases in creative self-efficacy corresponds with increases in creative performance294, a critically important factor in problem solving and science295,296. In fact, increasing creativity in problem solving requires providing explicit strategies that promote cognitive flexibility, not constraint297, as is the case for predetermined product testing. Especially in the case of young scientists, the bigger picture is less clear and short-term self-efficacy may be more important. Management styles of group leaders that promote independence and the ability to explore novel ideas increase perceived autonomy, which enhances self-efficacy and motivation298.
Thus, is vaccine design without creativity? Absolutely not, vaccine conferences display a wealth of novel ideas. However, the testing is often linear and even regulated by legislation in terms of approval for clinical use. Also, the approach of pharmaceutical companies is more readily screening of expansive libraries of candidate compounds through rigorous empirical testing. Using a systematic approach through wide parallel screening of vaccine candidates is only feasible for pharmaceutical companies whose main drive is wealth (Figure 1). Of note, financial incentives for scientists decreases the level of research performance286. The end result is that pharmaceutical companies will vigorously test and only invest in candidates that are truly showing promise, since the monetary loss of pursuing non-viable leads increases exponentially with time220. An academic scientist, however, needs to publish a story, which will most likely be the most successful version of a compound that is difficult to compare to similar compounds, since it was never tested in the first place. Perhaps both the intrinsic motivation (driven by self-efficacy) and the publications as main output of academic science do not provide the proper conditions for vaccine design and testing. So what does the academic sciences provide and how is it able to do this?
Find the answers here!
DISCLAIMER: I do not aim to extrapolate my viewpoint from a scientific subdiscipline or personal experience to the whole scientific community or to make definitive ex cathedra statements about what research should be. However, befitting a discussion, interpretations, implications, limitations and recommendations are appropriate, may be freely challenged and enhance dialogue beyond a mere summary.
Sjoerd schetters
285 Gustin BH. Charisma, Recognition, and the Motivation of Scientists. Am J Sociol 1973; 78: 1119–1134.
286 Ryan JC. The work motivation of research scientists and its effect on research performance. R&D Manag 2014; 44: 355–369.
287 Lam A. What motivates academic scientists to engage in research commercialization: ‘Gold’, ‘ribbon’ or ‘puzzle’? Res Policy 2011; 40: 1354–1368.
288 Bryan RR, Glynn SM, Kittleson JM. Motivation, achievement, and advanced placement intent of high school students learning science. Sci Educ 2011; 95: 1049–1065.
289 Komarraju M, Nadler D. Self-efficacy and academic achievement: Why do implicit beliefs, goals, and effort regulation matter? Learn Individ Differ 2013; 25: 67–72.
290 Bandura A. Self-Efficacy. Corsini Encycl. Psychol. 2010; : 1–3.
291 Maddux JE. Self-efficacy. In: Trusz S, Bąbel P (eds). Interpersonal and Intrapersonal Expectancies. 2016.
292 Usher EL, Pajares F. Sources of Self-Efficacy in School: Critical Review of the Literature and Future Directions. Rev Educ Res 2008; 78: 751–796.
293 Trujillo G, Tanner KD. Considering the role of affect in learning: monitoring students’ self-efficacy, sense of belonging, and science identity. CBE Life Sci Educ 2014; 13: 6–15.
294 Tierney P, Farmer SM. Creative self-efficacy development and creative performance over time. J. Appl. Psychol. 2011; 96: 277–293.
295 Schmidt AL. Creativity in Science : Tensions between Perception and Practice. Creat Educ 2011; 2: 435–445.
296 Hall KL, Feng AX, Moser RP, Stokols D, Taylor BK. Moving the Science of Team Science Forward: Collaboration and Creativity. Am J Prev Med 2008; 35: S243–S249.
297 DeHaan RL. Teaching Creativity and Inventive Problem Solving in Science. CBE—Life Sci Educ 2009; 8: 172–181. 298 Trevelyan R. The Paradox of Autonomy: A Case of Academic Research Scientists. Hum Relations 2001; 54: 495–525.