Treatable traits

Within the TRAITS programme, treatable traits in critically ill adults are conceptualised as syndrome agnostic:

• Biological or physiological abnormalities that are proximate determinants of outcome
• measurable using biomarkers or surrogates
• modifiable or reversible with intervention.

Biological targeting

Targeting of modifiable biological or physiological abnormalities that are shared between critical illness syndromes, and dominant feature of a treatable trait. 

Adaptive trial

Ability to continually introduce new interventions, and drop ineffective intervention using a priori defined criteria with adaptive interim analysis, with the potential for the standard care (control) to be upgraded to comprise the safest and most effective agents at the time of randomisation.

Data enabled

Utilises existing data capture frameworks within the NHS in Scotland to supplement and eventually replace traditional data collection methods to create models for efficient data flow in clinical trials.

Bayesian

An intuitive approach to guide decision making on whether an intervention shows promise in a given trait and allows posterior probability estimation to inform whether an intervention will have a clinically important benefit for patients with a specific treatable trait. 

Novel outcome framework

We use intermediate outcome in the causal path to the primary outcome for adaptive analyses. Intermediate outcomes differ by treatable trait.

Embedded biology

Embedded biological characterisation to rapidly advance precision medicine in critical illness through molecular regrouping of critical illnesses, and by seamlessly integrating biomarkers (diagnostic, predictive, prognostic, and surrogate), within a data-enabled clinical trial ecosystem to allow for comparison and analysis of interventions in combination or in series. 

Biomarker discovery, and validation

Assessing molecular mechanisms underpinning intervention effects, to inform future intervention selection, to enable biomarker discovery, and validation. 

Multiple interventions

Ability to test multiple interventions simultaneously. Questions on benefit, futility or harm will be answered on each intervention as soon as sufficient data have accrued.