Good Research Practice in Non-Clinical Pharmacology and Biomedicine

Good Research Practice in Non-Clinical Pharmacology and Biomedicine

Clinical Pharmacology

Biomedicine

Pharmacologists and other experimental life scientists study samples to infer
conclusions about how a molecule, cell, organ, and/or organism work in health
and disease and how this can be altered by drugs. The concept of inference implies
that whatever is reported based on the sample under investigation is representative
for the molecule, cell, organ, or organism under investigation in general. However,
this generalizability requires that two fundamental conditions are met: First, what is
being reported must be a true representation of what has been found. This sounds
trivial, but if data are selected, e.g., by unexplained removal of outliers or reporting is
biased by focusing on the findings in support of a hypothesis, reported data become a
biased rather than a true representation of what has been found. Second, what has
been found must be robust, i.e., other investigators doing a very similar experiment
should come up with similar findings. This requires a complete reporting of what
exactly has been done. It also requires that biases at the level of sampling, measuring,
and analyzing are reduced as much as feasible. These are scientific principles that
have been known for a long time. Nonetheless, scientific practice apparently often
ignores them—in part based on felt pressure to generate as many articles in highprofile
journals as possible. While the behavior of each participant (investigators,
institutions, editors, publishers, and funders) follows an understandable logic, the
result is counterproductive for the greater aims of scientific investigation. Against
this background, this volume in the series Handbook of Experimental Pharmacology
discusses various aspects related to the generation and reporting of robust data. It is
published 100 years after the first volume of the series, and this anniversary is a
fitting occasion to reflect on current practice and to discuss how the robustness of
experimental pharmacology can be enhanced.

Anton Bespalov

Martin C. Michel

Thomas Steckler Editors

Creative Commons Attribution 4.0 License

(http://creativecommons.org/licenses/by/4.0/)

Springer Open

2020

Tatik

http://www.springer.com/series/164

PDF

English

Textbooks

ISSN 0171-2004 ISSN 1865-0325 (electronic)

ISBN 978-3-030-33655-4 ISBN 978-3-030-33656-1 (eBook)

https://doi.org/10.1007/978-3-030-33656-1