Bench to bedside: what is translational research, and how can automation help?


The term “bench to bedside” has long been used to describe the connection between research and clinical practice, in particular, the translation of scientific discoveries from the “bench” to meaningful clinical practice at the “bedside” 1.

Translational research is a key area that stands to benefit from laboratory automation. Optimising lab processes on the bench improves the discovery rate of clinically impactful results, which can then be translated more smoothly to the bedside.

In this article, the concept of bench to bedside will be explored, including developments and specific examples of translation research, common obstacles, and how automation can help to overcome these.

What is translational research, or “bench to bedside”?

In its most simple terms, translational research (or translational medicine) is the transition of in vitro and experimental animal research to human applications 2.

This involves taking basic experimental results through to preclinical experiments, clinical trials, and finally clinical implementation. 

Modern translational medicine encompasses many different aspects of biomedical research, including “omics” technologies, pharmacology and drug discovery, cellular and molecular diagnostics, and preclinical animal models2. It is critical to ensure that these different approaches are able to work together to quickly and efficiently deliver the benefits of translational research; translational research is, therefore, now central to international health policy, research, and funding initiatives 3.

Bench to bedside example

The steps from bench to bedside within translational research have been defined4:

  • T0: Basic research: T0 is used to define mechanisms of health and disease; methods include preclinical or animal studies and association studies using large datasets 
  • T1: Translation to humans: T1 applies the understanding of disease mechanisms to the health of humans, involving preclinical development, proof of concepts, biomarker studies, and drug discovery
  • T2: Translation to patients: T2 aims to develop evidence-based practice guidelines using Phase I – Phase IV clinical trials
  • T3: Translation to practice: T3 compares the new intervention to widely accepted health practice by utilising comparative effectiveness studies, pragmatic studies, health services research, and behaviour modification 
  • T4: Traslation to communities: T4 aims to optimise interventions and improve population or community health, using epidemiology, policy or environmental changes, prevention studies, cost effectiveness research, and patient preference studies

Adopting a translational research approach has also led to a number of developments in the clinical treatment of diseases.

  • Infectious diseases: The COVID-19 pandemic highlighted the importance of an effective bench to bedside pathway. From sequencing the SARS-CoV-2 genome to the rapid development of vaccines 5, the COVID-19 response showed what is possible when all aspects of the bench to bedside pathway work together
  • Cancer: The emergence of high-throughput molecular techniques, such as omics technologies and biomarker prediction, has accelerated the translation of laboratory findings into clinically relevant applications within cancer 6. An example of this is the personalised response to treatments based on the genetic profiles of lung cancer patients 6
  • Genetic diseases: The Human Genome Project was a landmark project with the principles of translational research at its core 7. The aim of the project was to sequence the entire human genome, determining which genes play a role in disease in order to develop translational medicine treatments 7

Common obstacles in bench to bedside research

Bench to bedside translational research has the potential to harness scientific discoveries to advance human health, introducing new diagnostic tests, therapies, interventions, and improving care for patients 3. However, the translation of bench to bedside research has been slower than expected, and several obstacles still need to be overcome in order to close the gap between laboratory discoveries and new clinical interventions 8

  • Reproducibility: It is now well recognised that many published research findings are not as robust as they claim and cannot be reproduced8. This affects the translation of preclinical findings to human studies and has been highlighted by the biopharmaceutical industry and academic researchers 8
  • Translational models: In vitro and animal models are commonly used in translation research 8. However, there are concerns about how representative these models are of clinical situations, with human clinical trials often not reaching the same conclusions as the in vitro and animal studies that came before 8
  • Asking the right questions: The direction that basic science takes depends upon which questions are asked and which hypotheses are generated 9. As well as creating new knowledge, translational research hypotheses should be informed by how they can make a difference clinically 9
  • Research processes: Research processes at organisational and system levels have influenced the ability to conduct translational research 3. These include ethical and regulatory research processes, patient recruitment, and access to appropriate bioinformatics 3.

Research vs clinical care: A divide between science and medicine has also been recognised, which can be addressed with more collaboration, particularly interdisciplinary collaboration 3

How lab automation can help

Implementing automated processes can increase the reproducibility, efficiency, and quality of lab results, enabling scientists to tackle the big questions in translational research and achieve the bench to bedside clinical impact. 

LINQ is an open integrated automation platform from Automata that can be integrated into laboratory workflows to address the issues raised with translational research.

Automata has already partnered with research and clinical organisations to improve the translation of results from bench to bedside.

The collaboration with The Royal Marsden NHS Foundation Trust will use the LINQ platform to streamline genomic testing processes, increasing capacity without compromising accuracy. Similarly, Automata is collaborating with The Francis Crick Institute to automate critical workflows within their genomic sample preparation.


1. Feldman AM. Bench‐to‐Bedside; Clinical and Translational Research; Personalized Medicine; Precision Medicine—What’s in a Name? Clin Transl Sci. 2015;8(3):171–173. doi: 10.1111/cts.12302

2. Wehling M. Principles of translational science in medicine: from bench to bedside. Cambridge, MA: Academic Press. 2021

3. Fudge N, Sadler E, Fisher HR, et al. Optimising Translational Research Opportunities: A Systematic Review and Narrative Synthesis of Basic and Clinician Scientists’ Perspectives of Factors Which Enable or Hinder Translational Research. PLoS One. 2016;11(8):e0160475. doi: 10.1371/journal.pone.0160475

4. Wichman C, Smith LM, Yu F. A framework for clinical and translational research in the era of rigor and reproducibility. J Clin Transl Sci. 2021;5(1):e31. doi: 10.1017/cts.2020.523

5. Saravanan KA, Panigrahi M, Kumar H, et al. Role of genomics in combating COVID-19 pandemic. Gene. 2022;823:146387. doi: 10.1016/j.gene.2022.146387

6. Zaman A, Bivona TG. Quantitative Framework for Bench-to-Bedside Cancer Research. Cancers. 2022;14(21):5254. doi: 10.3390/cancers14215254

7. Chiche JD, Cariou A, Mira JP. Bench-to-bedside review: fulfilling promises of the Human Genome Project. Crit Care. 2002;6(3):212-5. doi: 10.1186/cc1491

8. Seyhan AA. Lost in translation: The Valley of Death Across Preclinical and Clinical Divide – identification of Problems and Overcoming Obstacles. Translational Medicine Communications. 2019;4:18. doi: 10.1186/s41231-019-0050-7

9. Austin CP. Opportunities and challenges in translational science. Clin Transl Sci. 2021;14(5):1629–1647. doi: 10.1111/cts.13055

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