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Review
. 2023 Jan 8;21(1):14.
doi: 10.1186/s12916-022-02719-0.

Recommendations for robust and reproducible preclinical research in personalised medicine

Vibeke Fosse  1 , Emanuela Oldoni  2 , Florence Bietrix  2 , Alfredo Budillon  3 , Evangelos P Daskalopoulos  4 , Maddalena Fratelli  5 , Björn Gerlach  6 , Peter M A Groenen  7 , Sabine M Hölter  8 , Julia M L Menon  9 , Ali Mobasheri  10   11   12   13   14 , Nikki Osborne  15 , Merel Ritskes-Hoitinga  16   17 , Bettina Ryll  18 , Elmar Schmitt  19 , Anton Ussi  2 , Antonio L Andreu  2 , Emmet McCormack  20   21 ; PERMIT group
Collaborators, Affiliations
Review

Recommendations for robust and reproducible preclinical research in personalised medicine

Vibeke Fosse et al. BMC Med. .

Abstract

Background: Personalised medicine is a medical model that aims to provide tailor-made prevention and treatment strategies for defined groups of individuals. The concept brings new challenges to the translational step, both in clinical relevance and validity of models. We have developed a set of recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine.

Methods: These recommendations have been developed following four main steps: (1) a scoping review of the literature with a gap analysis, (2) working sessions with a wide range of experts in the field, (3) a consensus workshop, and (4) preparation of the final set of recommendations.

Results: Despite the progress in developing innovative and complex preclinical model systems, to date there are fundamental deficits in translational methods that prevent the further development of personalised medicine. The literature review highlighted five main gaps, relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. We identified five points of focus for the recommendations, based on the consensus reached during the consultation meetings: (1) clinically relevant translational research, (2) robust model development, (3) transparency and education, (4) revised regulation, and (5) interaction with clinical research and patient engagement. Here, we present a set of 15 recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine.

Conclusions: Appropriate preclinical models should be an integral contributor to interventional clinical trial success rates, and predictive translational models are a fundamental requirement to realise the dream of personalised medicine. The implementation of these guidelines is ambitious, and it is only through the active involvement of all relevant stakeholders in this field that we will be able to make an impact and effectuate a change which will facilitate improved translation of personalised medicine in the future.

Keywords: Personalised medicine; Policy; Preclinical models; Regulation; Translational methods.

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Conflict of interest statement

The following authors declare competing interests:

BG is an employee of PAASP GmbH, shareholder of PAASP GmbH and PAASP US LLC, and executive board member of the Guarantors of EQIPD e.V.

PMAG is an employee of Idorsia Pharmaceuticals Ltd. and holds stocks and shares.

The other authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Outline of recommendations for robust translational methods for personalised medicine. The recommendations are focused on five main areas: (1) clinically relevant translational research, (2) Robust model development, (3) transparency and education, (4) revised regulation, and (5) interaction with clinical research, and all these are interconnected
Fig. 2
Fig. 2
Outline of methodology for developing the recommendations. The methodological approach consisted of four main steps: mapping of current evidence, discussion with field experts, a consensus workshop, and collaborative formulation of the guidelines
See this image and copyright information in PMC

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