Personalized or precision medicine is meant to distinguish tailored treatment from trial and error. Today’s concept of precision medicine has evolved to specifically include the ‘omic profile of a patient in the prevention, diagnosis, and treatment of disease. The rapid genomic discoveries made possible through genome-wide association studies coupled with decreasing costs of sequencing and genotyping have repositioned precision medicine from an academic exercise closer to clinical reality. The emergence of electronic health records (EHRs) now makes it possible to both perform population-scale research and to effectively deliver personalized medicine to the individual patient.
While the promise of precision medicine is great, there are several identifiable gaps in current research that limit the reach to all potential patients. One such major gap is diversity in biomedical research, which limits both the generalizability and availability of genomic-based treatments or prevention strategies. New initiatives and studies are now in place to ensure that traditionally underrepresented groups, defined by race/ethnicity, socioeconomic status and/or position, geography, and age, be included in genomic research. As a result, we anticipate a swell of new data and methodologies accelerating the already rapid pace of precision medicine research.
This Research Topic aims to present original research, commentaries, perspectives, and reviews on the impact of diversity in precision medicine research. Example topics include (but are not limited to):
• Development of culturally-appropriate consent and recruitment strategies for precision medicine research
• Diversity in the biomedical workforce, including higher education in science, technology, engineering, mathematics, and medicine (STEMM)
• Barriers to participation in research (such as access to technology, genomic literacy, concerns for digital data privacy, and factors that impact time or means to participate in re-search)
• Approaches for measuring lifestyle, social determinants of health, and environmental exposures in diverse groups
• Issues related to return of research results to diverse groups
• Pharmacogenomics research in diverse populations
• Genomic discovery in non-European populations
• The use of genetic ancestry for genomic discovery (such as admixture mapping)
• Statistical methods for genomic data from multiple populations
Personalized or precision medicine is meant to distinguish tailored treatment from trial and error. Today’s concept of precision medicine has evolved to specifically include the ‘omic profile of a patient in the prevention, diagnosis, and treatment of disease. The rapid genomic discoveries made possible through genome-wide association studies coupled with decreasing costs of sequencing and genotyping have repositioned precision medicine from an academic exercise closer to clinical reality. The emergence of electronic health records (EHRs) now makes it possible to both perform population-scale research and to effectively deliver personalized medicine to the individual patient.
While the promise of precision medicine is great, there are several identifiable gaps in current research that limit the reach to all potential patients. One such major gap is diversity in biomedical research, which limits both the generalizability and availability of genomic-based treatments or prevention strategies. New initiatives and studies are now in place to ensure that traditionally underrepresented groups, defined by race/ethnicity, socioeconomic status and/or position, geography, and age, be included in genomic research. As a result, we anticipate a swell of new data and methodologies accelerating the already rapid pace of precision medicine research.
This Research Topic aims to present original research, commentaries, perspectives, and reviews on the impact of diversity in precision medicine research. Example topics include (but are not limited to):
• Development of culturally-appropriate consent and recruitment strategies for precision medicine research
• Diversity in the biomedical workforce, including higher education in science, technology, engineering, mathematics, and medicine (STEMM)
• Barriers to participation in research (such as access to technology, genomic literacy, concerns for digital data privacy, and factors that impact time or means to participate in re-search)
• Approaches for measuring lifestyle, social determinants of health, and environmental exposures in diverse groups
• Issues related to return of research results to diverse groups
• Pharmacogenomics research in diverse populations
• Genomic discovery in non-European populations
• The use of genetic ancestry for genomic discovery (such as admixture mapping)
• Statistical methods for genomic data from multiple populations
