Ignite Creation Date:
2025-12-25 @ 2:59 AM
Ignite Modification Date:
2025-12-26 @ 1:40 AM
Study NCT ID:
NCT03987633
Status:
RECRUITING
Last Update Posted:
2025-03-10
First Post:
2019-06-12
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
EMPOWER-1: A Multi-site Clinical Cohort Research Study to Reduce Health Inequality
Sponsor:
Future Genetics Limited
Organization:
Study Overview
Official Title:
EMPOWER-1: A Multi-site Clinical Cohort Study to Reduce Health Inequality: Identifying Ethnic Disparities in Treatment Failures for Medicines Prescribed to Treat Diseases That Cause Significant Mortality and Morbidity in the UK Population
Status:
RECRUITING
Status Verified Date:
2025-03
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
EMPOWER
Brief Summary:
Health inequality and genetic disparity are a significant issue in the United Kingdom (UK).
This study focuses on diseases that are associated with significant morbidity and mortality in the UK, and specifically examines the extent and basis of treatment failure in different patient populations.
The vast majority of drug registration clinical trials have under-representation of ethnic minority populations. In addition, the wider Caucasian populations have reasonably different clinical characteristics to the population that participated in the drug licencing clinical trials. A consequence of this is that drugs are licensed for use in real-world general patient populations where the clinical trial results are simply not statistically significant to specifically demonstrate efficacy or safety in populations that were either absent or under-represented in the drug registration clinical trials. When these facts are considered alongside data that supports significant under-reporting of adverse events in the real-world setting within the UK (and globally, e.g the USA and Europe), it highlights that pharmacovigilance systems are unable to capture drug effectiveness and safety data in a manner that can reasonably assure appropriate prescribing in the wider patient populations.
This large real-world research study aims to identify whether commonly prescribed drugs are effective in treating illnesses that cause significant poor health and death in the different patient populations that represent the UK.
The goal of this study is to generate large quantitative data-sets that may inform clinical practice to reduce the existing health inequality and genetic disparity in the UK.
This study focuses on diseases that are associated with significant morbidity and mortality in the UK, and specifically examines the extent and basis of treatment failure in different patient populations.
The vast majority of drug registration clinical trials have under-representation of ethnic minority populations. In addition, the wider Caucasian populations have reasonably different clinical characteristics to the population that participated in the drug licencing clinical trials. A consequence of this is that drugs are licensed for use in real-world general patient populations where the clinical trial results are simply not statistically significant to specifically demonstrate efficacy or safety in populations that were either absent or under-represented in the drug registration clinical trials. When these facts are considered alongside data that supports significant under-reporting of adverse events in the real-world setting within the UK (and globally, e.g the USA and Europe), it highlights that pharmacovigilance systems are unable to capture drug effectiveness and safety data in a manner that can reasonably assure appropriate prescribing in the wider patient populations.
This large real-world research study aims to identify whether commonly prescribed drugs are effective in treating illnesses that cause significant poor health and death in the different patient populations that represent the UK.
The goal of this study is to generate large quantitative data-sets that may inform clinical practice to reduce the existing health inequality and genetic disparity in the UK.
Detailed Description:
This multi-centre real-world study will recruit patients across different National Health Service (NHS) sites based in England, where the overall patient population demographic profile is sufficiently variable to allow for meaningful representation of different ethnicities in the analysis of pooled data-sets.
The study addresses the issue of health inequality and genetic disparity in the United Kingdom (UK) by recruiting up to 200,000 patients primarily from the three main ethnic groups in the UK; namely White (Caucasian), African-Caribbean (Black), and South Asian (Asian) populations on a 1:1:1 ratio.
Biological samples, medical records, alongside specific questionnaires will be used in data analyses to help identify treatment failures in different populations for the 19 disease areas under investigation, which are a significant cause of morbidity and mortality in the UK.
Analysis of patient populations may provide real-world evidence around disease prevalence between and within different ethnic groups. The data may also support hypothesis driven genetic analysis to identify putative bio-markers associated with treatment failure.
Data from this study will be published, and findings could better inform clinical practice in the management of diseases that cause significant poor health and death in the different populations that represent the UK.
The study addresses the issue of health inequality and genetic disparity in the United Kingdom (UK) by recruiting up to 200,000 patients primarily from the three main ethnic groups in the UK; namely White (Caucasian), African-Caribbean (Black), and South Asian (Asian) populations on a 1:1:1 ratio.
Biological samples, medical records, alongside specific questionnaires will be used in data analyses to help identify treatment failures in different populations for the 19 disease areas under investigation, which are a significant cause of morbidity and mortality in the UK.
Analysis of patient populations may provide real-world evidence around disease prevalence between and within different ethnic groups. The data may also support hypothesis driven genetic analysis to identify putative bio-markers associated with treatment failure.
Data from this study will be published, and findings could better inform clinical practice in the management of diseases that cause significant poor health and death in the different populations that represent the UK.
Study Oversight
Has Oversight DMC:
True
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: