Who invented translational science in medicine and health research (National Institutes of Health - NIH)?

The National Institutes of Health (NIH) Invented Translational Science in Medicine and Health Research

The National Center for Advancing Translational Sciences (NCATS) was created within the US National Institutes of Health (NIH) in 2012 to facilitate the translation of new findings in basic research into improved diagnostics and therapeutics. 1

Historical Development of Translational Science

• Translational science emerged from the recognition that traditional research approaches were insufficient to bridge the gap between basic science discoveries and clinical implementation 2

• The concept of translational research was formalized through the development of a multi-step translational (T) model by Dougherty and Conway, which organized research efforts to transform healthcare delivery and improve outcomes 1

• This model identified three major translational steps:

  • T1: Basic biomedical science to clinical efficacy evaluation
  • T2: Clinical efficacy to broader effectiveness studies
  • T3: Implementation of effective therapies in routine clinical practice 1

The Establishment of NCATS and Formalization of Translational Science

• In 2012, the NIH established the National Center for Advancing Translational Sciences (NCATS) as the central institution for advancing translational sciences 1

• NCATS was created with the mission to "transform the way clinical research is conducted by creating a national network for translational medicine that will be more efficient and effective" 1

• Prior to NCATS, in 2006, the Mayo Clinic Center for Clinical and Translational Science (CCaTS) was established as one of the original 12 institutions selected for this translational network 1

Core Principles of Translational Science

• The approach of NCATS involves several key themes:

  • Collaboration across disciplines and organizations
  • Effective linking of research on disease mechanisms with clinical outcomes
  • Joining forces with other agencies to fund larger projects for mutual benefit 1

• Examples of NCATS implementation include:

  • Creation of interdisciplinary teams to solve longstanding problems
  • Development of better models for drug and toxicity testing
  • Collaboration with DARPA and FDA to advance technologies like organs-on-chips in drug screening 1

Team Science Paradigm in Translational Research

• The team science paradigm posits that teams comprising highly specialized, complementary team members are optimal for translating products into practice 1

• This approach recognizes that "No man is big enough to be independent of others," a mantra attributed to Dr. Will Mayo Senior that has become foundational to translational science 1

• Specialization allows professionals to become members of medical or scientific teams, leading to the creation of multiple avenues for post-graduate medical education and post-PhD doctoral training 1

Mechanistic Approach to Understanding Disease

• Translational science has shifted focus toward understanding the biological mechanisms underlying disease to better identify patient populations and target more effective interventions 1

• This approach has led to initiatives like the Research Domain Criteria framework project (RDoC) by the National Institute of Mental Health, which realigns patients with the molecular signatures of their underlying disease 1

Challenges and Pitfalls in Translational Science

• Despite advances in translational science, the reliability of healthcare systems remains limited, with studies suggesting only 60% of recommended care is actually delivered to patients 1

• There is often an imbalance between resources devoted to expanding understanding of disease mechanisms versus improving the mechanisms by which those advances will actually improve health outcomes 2

• Barriers to scientific translation persist, requiring further progress in connecting and collaborating across a wide variety of fields 3

• Successful translational science requires open-minded communication and the ability to overcome typical disciplinary and institutional barriers 4

Future Directions

• Collective intelligence and crowdsourcing applications offer potential for global online networks that could drive alignment of biomedical science with biotechnology, clinical need, and patient experience 3

• Transdisciplinary approaches can enhance cross-disciplinary information exchange, helping researchers frame better questions, integrate more relevant evidence, and advance translational knowledge more effectively 4

• The FAIR (findable, accessible, interoperable, and reusable) data principles are becoming essential for the future of translational science 1