Diversity extends beyond recruiting a representative sample into purposeful data analysis and expansion of voices and perspectives in the organisations Different layers of Diversity in Genomic data Recruiting data from underrepresented populations Diversity in recruitment and understanding/overcoming cultural barriers Building in-house capability or leveraging external experts to analyse data from. [...] Data and diversity in human genomics | 26 Challenges towards increasing diversity: Asia and Middle East Limited opportunities for international cooperations Example from Asia Due to strict data access laws and regulations in parts of Asia and the One Asian Biobank, due to the stringent legislation in the country they Middle East. [...] Data and diversity in human genomics | 47 Legal issues are also important, but outside of the remit of most funding organisations High Maturity Archetype Lowest ranked opportunities Data sharing Support in addressing legal challenges for data sharing Support in translation efforts to enable use of genomic data to support diagnosis and care Data and diversity in human genomics | 48 For mid maturity. [...] Data and diversity in human genomics | 54 For global collaborations, efforts should focus on data analysis, low- and middle-income country collaborations, and the set-up of regional centres Higher ranked opportunities Solutions/recommendations Data analysis • Fund a goal-driven program to develop local and regional solutions that are cost effective and capable of scaling up. [...] For example, targeted sequencing to develop custom-genotype arrays Support with the development and sharing relevant to future research and clinical care of novel techniques for the analysis and integration of large and diverse data sets • Offer fellowships and exchange visits of local talents from low- and middle-income countries to learn data analysis in advanced environments/labs • Fund exchang.
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- United Kingdom
Table of Contents
- Table of contents 2
- Forward 3
- Executive summary 4
- Definition of diversity in genomic research 4
- Genomic diversity archetypes 4
- Key opportunities for enhancing data diversity globally 4
- The objectives of this project were: 4
- Methodology and sample sizes 5
- Overview of diversity in genomic research 6
- Activity 6
- Considerations 6
- Overview of the geographical coverage of the initiatives and initiative type reviewed in this resea 7
- Key takeaways 7
- Opportunity 7
- The focused long list of initiatives included a range of initiative types, led by different types o 8
- Type of Initiatives 8
- Type of Organisation 8
- Regarding initiative impact, initiatives generally capture at least one type of genomic data and h 9
- Data Access 9
- Genomic Data Type Collected 9
- Cohort size 9
- Regarding diversity value, variables relating to demographics and health information are more commo 10
- Availability of demographics 10
- Availability of health information 10
- Availability of socio-economic information 10
- 55 initiatives responded to our survey, most stating that they aim for broad representation and view 11
- Population of Interest (n=55) 11
- Level of Importance (n=55) 11
- In survey respondents, region, age, gender and ethnicity are most commonly collected, whereas data 12
- 95% collect geographical information 12
- 95% collect demographical information 12
- 82% collect health information 12
- 51% collect socioeconomic information 12
- IQVIA then spoke with representatives from 27 initiatives from four regions to gain deeper insight i 13
- Diversity extends beyond recruiting a representative sample into purposeful data analysis and expans 13
- Different layers of Diversity in Genomic data 13
- Insights by geographical region 14
- This report includes a breakdown of diversity insights by geographical region, as well as the oppor 15
- Regional analysis: North America, EU, Oceania 16
- Key metrics and work in genomics: North America, Europe, Oceania 17
- Key metrics: 17
- # of initiatives 17
- Types of initiatives and organisations (111) 17
- Key metrics and work in genomics: North America, Europe, Oceania 18
- Key metrics: 18
- Types of genetic data collected (26) 18
- Work in Genomics 18
- Mission and goals: 18
- Established capacity and infrastructure: 18
- Diversity data collected: North America, Europe, Oceania 19
- 23 collect geographical information 19
- 8 collect demographical information 19
- 23 collect health information 19
- 14 collect socioeconomic information 19
- Efforts to increase diversity in initiatives: North America, Europe, Oceania 20
- Challenges towards increasing diversity: North America, Europe, Oceania 21
- Regional analysis: Asia and Middle East 22
- Key metrics and work in genomics: Asia and Middle East 23
- Key metrics: 23
- # of initiatives 23
- Types of initiatives and organisations (35) 23
- Key metrics and work in genomics: Asia and Middle East 24
- Key metrics: 24
- Types of genetic data collected (8) 24
- Work in Genomics 24
- Mission and goals: 24
- Established capacity and infrastructure: 24
- Diversity data collected: Asia and Middle East 25
- 8 collect geographical information 25
- 8 collect demographical information 25
- 8 collect health information 25
- 5 collect socioeconomic information 25
- Efforts to increase diversity in initiatives: Asia and Middle East 26
- Challenges towards increasing diversity: Asia and Middle East 27
- Regional analysis: Latin America and Africa 28
- Key metrics and work in genomics: Latin America and Africa 29
- Key metrics: 29
- # of initiatives 29
- Types of initiatives and organisations (24) 29
- Key metrics and work in genomics: Latin America and Africa 30
- Key metrics: 30
- Types of genetic data collected (9) 30
- Work in Genomics 30
- Mission and goals: 30
- Established capacity and infrastructure: 30
- Diversity data collected: Latin America and Africa 31
- 8 collect geographical information 31
- 9 collect demographical information 31
- 8 collect health information 31
- 6 collect socioeconomic information 31
- Efforts to increase diversity in initiatives: Latin America and Africa 32
- Challenges towards increasing diversity: Latin America and Africa 33
- Challenges towards increasing diversity: Latin America and Africa (continued) 34
- Detailed insight: global collaborations 35
- Key metrics and work in genomics: global collaborations 36
- Key metrics: 36
- # of initiatives 36
- Types of initiatives and organisations (28) 36
- Key metrics and work in genomics: global collaborations 37
- Key metrics: 37
- Types of genetic data collected (12) 37
- Work in Genomics 37
- Mission and goals: 37
- Established capacity and infrastructure: 37
- Efforts to increase diversity in initiatives: global collaborations 38
- Challenges towards increasing diversity: global collaborations 39
- Opportunity per genomic maturity archetype 40
- There is high regional variation in terms of maturity of genomics research, as well as different app 41
- Maturity in genomics research 41
- Key takeaways 41
- There is high regional variation in terms of maturity of genomics research, as well as different app 42
- High maturity regions (USA, Canada, UK, Estonia, Australia) 42
- Medium maturity regions (Japan, Taiwan, Thailand, Qatar, Hong Kong, South Africa) 42
- Low maturity regions (Brazil, Mexico, Uganda, India) 42
- The path to full and equitable utilisation of genomics data has several key steps and many hurdles t 43
- A PESTLE Analysis provides an overview of the challenges in genomic diversity in low-and high maturi 44
- Opportunities for funders to positively impact data and diversity in human genomics 45
- For high maturity regions, efforts should focus on minority and community groups engagement, alterna 46
- Higher ranked opportunities 46
- Community efforts 46
- Recruitment 46
- Community efforts 46
- Solutions/recommendations 46
- For high maturity regions, data storage and analysis are the second priority 47
- Lower ranked opportunities 47
- IT infrastructure 47
- Data analysis 47
- Solutions/recommendations 47
- Opportunity 47
- Legal issues are also important, but outside of the remit of most funding organisations 48
- Lowest ranked opportunities 48
- Data sharing 48
- For mid maturity regions, the most important opportunity is to support regional teams with education 49
- Higher ranked opportunities 49
- Education and training 49
- Solutions/recommendations 49
- For mid maturity regions, increasing participant engagement and addressing recruitment/sample logist 50
- Lower ranked opportunities 50
- Participant engagement 50
- Recruitment 50
- Solutions/recommendations 50
- For mid maturity regions addressing IT and legal challenges could foster diversity 51
- Lowest ranked opportunities 51
- IT infrastructure 51
- Legal challenges 51
- For low maturity regions, efforts should focus on growth and retention of local talent and local inf 52
- Higher ranked opportunities 52
- Local infrastructure 52
- Talent growth and retainment 52
- Solutions/recommendations 52
- For low maturity regions, IT infrastructure and local engagement come as second priority 53
- Lower ranked opportunities 53
- IT infrastructure 53
- Engagement of local community 53
- Solutions/recommendations 53
- For low maturity regions, support on novel analytical approaches and alternative recruitment methods 54
- Lowest ranked opportunities 54
- Novel analyses 54
- Recruitment 54
- Opportunity 54
- For global collaborations, efforts should focus on data analysis, low- and middle-income country col 55
- Higher ranked opportunities 55
- Data analysis 55
- Low- and middle-income country collaborations 55
- Regional centers 55
- Solutions/recommendations 55
- For global collaborations, knowledge and skill sharing, and data harmonisation come as second prior 56
- Lower ranked opportunities 56
- Knowledge sharing 56
- Data harmonisation 56
- Solutions/recommendations 56
- For global collaborations legal challenges and cloud-based solutions are deemed important 57
- Lowest ranked opportunities 57
- Data access policies 57
- Legal challenges 57
- Opportunity 57
