Researchers
Research
Evaluation of interventions linked to treatable traits in critically ill adults to enable precision medicine: Data enabled Bayesian adaptive platform randomised clinical trial with embedded biological characterisation (TRAITS Trial).
Platform overview
Overview
TRAITS Programme breaks from the traditional randomized clinical trial model in critical illness, by studying adult critically ill patients’, agnostic of conventional clinical syndromes, by being data enabled, and using a Bayesian adaptive framework.
One illness with subpopulations = Critical illness grouped into treatable traits defined with a biomarker and a bedside clinical variable or organ dysfunction (i.e., Umbrella Trial).
Adaptive = Ability to add new treatable traits, and / or interventions, and uses all available information for every participant enrolled into the trial.
Efficient use of control participants = Platform trial is designed to increase trial efficiency by using a single usual care per treatable trait, and with.
Potentially improvable population of patients = Critically ill adults where acute mortality with current ‘best care’ is high.
Interim endpoint that are directly linked to treatable trait to get results earlier.
Interim adaptive analyses = Frequent monitoring to a priori defined rules to enable decision making during the trial, thereby minimizing the number of participants and time required to evaluated any one experimental agent.
Data enabled for efficiency = Use of data for simulation of trial features; improved feasibility assessments; efficient assessments by directly capturing routine electronic health record (EHR) into the trial dataset in the future; and more efficient study analyses and interpretation, using standardised and mapped to EHR variables.
Core protocol, and trait-specific subprotocols = vastly compressed start up times for adding new interventions.
Trial schema
Embedded biological characterisation = ‘Learning what we do and doing what we learn’
The embedded biological characterisation protocol will collect blood samples at two time points before and after intervention with explicit goals
- Enable detailed biological feature at baseline, changes in biology following interventions, determine features of a beneficial intervention response at multiple biological levels
- Enable molecular characterisation of critical illness, of current, and new treatable traits
- Discover and validate biomarkers, and novel targets
- Integrated within platform for companion biomarker discovery for tested interventions