The National Center for Advancing Translational Science (NCATS) at NIH defines:
- ‘Translation’ as the process of turning observations in the laboratory, clinic and community into interventions that improve the health of individuals and communities – from diagnostics, preventions, and treatments to medical procedures and behavioral changes.
- ‘Translational research’ as the endeavor to traverse a particular step of the translational process for a particular target or disease.
- ‘Translational science’ (TS) is the field of investigation focused on understanding the scientific and operational principles underlying each step of the translational process.
Whereas translational research focuses on the specific case of a target or disease, translational science is “disease universal” because it focuses on the scientific and operational bottlenecks that are common to translational research for most or all diseases. These obstacles impede and prolong the process of identifying effective new treatments.
Translational Science identifies barriers to the advancement of research across the translational spectrum, works toward a product or approach that overcomes or mitigates that barrier, and is generalizable across multiple diseases/conditions.
Bottlenecks in the Translational Research Pipeline
Basic /Preclinical Research
- Target qualification
- Predictive efficacy
- Predictive toxicology
- ‘Risky’ undruggable targets/ untreatable diseases
- Data interoperability
- Inconsistent diagnostic and outcome criteria
- Clinical trial participant recruitment and diversity
- Clinical trial operational efficiency
- Administrative burdens (IRB)
Clinical Implementation/Public Health
- Time of intervention adoption
- Access and adherence
- Comparative effectiveness
NCATS works with researchers, the public, and other stakeholder groups to design new approaches and technologies that ultimately will deliver more treatments to more people more quickly.
Re-engineering the Translational Pipeline
Examples of Solutions to Overcome Research Bottlenecks
“One size fits all” approach
- Adaptive and other novel trial designs
Low enrollment and diversity in clinical trials
- Enhance community and informatics efforts
Administrative burden for study start-up
- Streamline regulatory processes
Shortage of qualified translational investigators and staff
- Training and career development best practices
Insufficient tools and technologies to predict toxicity and efficacy of new drugs
- Platform-based (WGS for rare diseases, mobile tech for multiple diseases)
Incompatible databases to advance data science
- Data, harmonization, interoperability and integration
Examples of Translational Science Projects
NOT Translational Science
- Testing a compound that was efficacious in an animal model of disease in a human model of disease
- Evaluating the toxicity of a newly developed compound to treat Alzheimer’s disease
- Identifying early biomarkers of Multiple Sclerosis
- Recruitment of historically underrepresented groups into a clinical trial of breast cancer
- Generating a research database of patients with Diabetes in the Bronx
- Developing models/assays that can be better predictors of efficacy in humans than current cell/animal models
- Development of new assay types based on human cells that can identify potential toxicities more accurately and efficiently than current animal testing methods
- Development of framework/models to identify biomarkers that change early in the course of intervention to gauge intervention efficacy
- Systematically studying barriers to enrollment of historically underrepresented groups in clinical trials
- Developing systems to merge clinical datasets from different sources accurately and efficiently
The key distinguishing features of a translational science project are (1) the focus on overcoming roadblocks to enhance the efficiency and speed translational research and (2) the generalizability of the solutions across a range of diseases and conditions.
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