It is generally recognized that, to produce robust and reliable data, research must be protected against bias. There are various measures introduced, from training programs to reporting guidelines, to make sure that “exploratory” and “confirmatory” research output (Dirnagl 2020) can be recognized on the basis of information provided in scientific publications and other reports.
However, the overall speed of introducing these changes remains to be slow and, even according to recent analyses, reporting of sample size estimation, randomization and blinding in preclinical research publications is still disappointingly low (Kousholt et al 2022). Such analyses illustrate two related challenges.
On the one hand, biased research is believed to be more likely to produce unreliable (“non-reproducible”) data and this is one of the arguments used by those who oppose the use of laboratory animals in biomedical research (we have repeatedly written about it – here, here and here).
On the other hand, the above cited publication summarized reporting practices by scientists affiliated with Danish universities. In the EU, the Directive 2010/63/EU explicitly mandates the conduct of a Harm-Benefit Analysis (HBA) of proposed animal research by Competent Authorities. HBA involves the evaluation of potential harms inflicted upon research animals against any potential benefits derived from the research. In practice, however, there is no alignment on how the benefit of the proposed research should be assessed.
To meet the need for a practical and approachable method for assessing research benefit, the HBA International Working Group was convened in January 2023. The working group consisted of nine participants representing a balance of diverse expertise in research, industry, and academia and included a PAASP team member. Two existing HBA frameworks were taken as starting points – one developed by AALAS-FELASA (Laber et al 2016) and the other implemented in Switzerland (Swiss Academies of Arts and Sciences 2022).
The working group constructed a Benefit Assessment Matrix (BAM) that is based on: (1) identification and definition of key factors defining proposed research benefit, (2) identification and definition of modifying factors (i.e., factors related to internal validity and technical feasibility that enable the proposed benefit to translate into qualified benefit); and (3) simple metrics for the user to determine if the criteria for each item has been met.
While the BAM tool does not represent or replace an assessment by Ethics Committees, it is expected that Ethics Committees or equivalent bodies will use it to recognize high-rigor research proposals (and, if needed, grant them a priority review) as well as to identify arguments to challenge the applicants regarding the benefit of proposed studies.
Further, the BAM tool can support scientists willing to highlight the benefit of the proposed studies as well as the implemented rigor measures to achieve the benefit objectives.
The Working Group organized a symposium entitled “Harm-Benefit Analysis: A Tool for the Assessment of Benefit” at the next FELASA congress (LINK) to present the BAM framework and seek further input. Readers of this newsletter interested in learning about BAM details and willing to provide feedback and pilot test the BAM are invited to contact the group via email (info@paasp.net).