In Search of the Right Model
Human organ models offer new opportunities to better understand diseases and develop more targeted therapies. The COVID-19 pandemic provided a unique scientific test case: Within a remarkably short period of time, researchers used a wide range of cell, organoid and tissue models to study the same disease. Scientists from the Berlin Institute of Health at Charité (BIH) and other research institutions systematically reviewed 558 studies. In an interview, authors Maren Hülsemann, Silke Kniffert, Ulf Tölch and Andreas Hocke discuss the potential of human organ models and why differences in methodology and incomplete reporting still limit how reliably these models can inform our understanding of human disease.
What question did you want to answer, what were you particularly interested in?
For the first time, human organ models were adopted by a broad scientific community within a remarkably short period to investigate the same disease: COVID-19. The pandemic therefore created a unique precedent that we sought to examine systematically. Drawing on 558 studies, we assessed the contribution of different cell-, organoid-, and tissue-based models to our understanding of relevant host factors, viral replication, and early immune responses. We were particularly interested in determining whether findings generated across these diverse model systems could be integrated into a robust, comparable, and translationally meaningful evidence base.
What specific challenges did you face when developing your approach?
The greatest challenge was the considerable heterogeneity of the research field. Model systems, cell types, experimental procedures, and outcome measures were described using highly variable terminology and were frequently insufficiently characterised. We therefore had to develop dedicated classification schemes and a detailed framework for data extraction. An additional challenge was the absence of established tools for assessing risk of bias in in vitro studies. Moreover, essential methodological information – including culture conditions, replicates, normalisation procedures, and raw data – was frequently missing, making data harmonisation and preparation for comparative analyses highly resource-intensive and requiring substantial manual effort.
What surprised you and why? What was new?
One of the most striking findings was the discrepancy between the large number of published studies and the comparatively limited amount of data that could be robustly synthesised. Many findings could not be directly compared because of heterogeneous measurement approaches or incomplete reporting. We also observed a marked predominance of respiratory tract models, while negative or null findings were reported only rarely. A key novelty of our study is its comprehensive perspective across model types and organ systems. By examining an entire research field at scale, our review demonstrates how strongly methodological transparency and reporting quality determine the extent to which findings from human organ models can be interpreted, compared, synthesised, and ultimately translated into meaningful scientific evidence.
What significance could this success have for future patients?
Well-characterised human organ models could be particularly valuable in the context of emerging infectious diseases, where they may help to identify at an early stage which organs and cell types are affected, how efficiently a pathogen replicates, and which immune responses it elicits. Such models may also support the more targeted selection of therapeutic strategies and enable unsuitable candidates to be excluded earlier in the development process. To realise this potential, however, models must be reproducible and their results comparable across laboratories. Our work identifies key requirements for transforming fragmented experimental findings into a more reliable preclinical evidence base, thereby enabling human models to be used more rapidly and systematically to address clinically and patient-relevant questions.
Where do you see the translational bridge between research and application?
The translational bridge lies in the systematic integration of experimental findings with clinical observations and patient-derived material. A model is not inherently informative simply because it is based on human cells; it must be demonstrated to recapitulate clinically relevant disease processes. Clinical data can therefore guide model development and validation, while appropriately validated models can facilitate mechanistic investigations and the evaluation of potential therapeutic interventions. Ultimately, effective translation requires an integrated framework comprising biologically relevant models, transparent and reproducible methodologies, accessible data, and interdisciplinary research networks. Such a framework enables a bidirectional exchange between fundamental research and clinical application, allowing experimental and clinical evidence to inform and strengthen one another. ktional miteinander verbindet.