This Research Topic is the second edition, looking to expand upon the original collection Editor's Feature: Negative Findings in Pharmacogenetics and PharmacogenomicsIn the field of Pharmacogenetics and Pharmacogenomics, there is a significant bias towards publishing positive results over negative or null findings, despite the latter often being well-supported by sound biological reasoning, suitable sample sizes, and robust design. This trend perpetuates a publication bias that skews the scientific record and can mislead research priorities by omitting crucial data. Publishing studies with negative results can prevent unnecessary duplication of research efforts, minimizing both waste of public and private resources and delay in real scientific advancement.This Research Topic aims to push forward the publication of well-designed, statistically powered studies yielding negative or null conclusions. These efforts are essential for gathering key data that can correct the existing publication bias and provide a basis for developing practical applications in pharmacogenetics and pharmacogenomics.We invite submissions of original studies or meta-analyses focusing on negative or null results related to pharmacogenetics, pharmacogenomics, and associated areas such as pharmacokinetics, pharmacodynamics, polymorphic drug metabolism and transport, and drug-drug interactions. Topics include, but are not limited, to:-Studies on the in vitro effects of genetic variations.-Studies on the in vivo effects of genetic variations.-Association studies of Pharmacogenetics or Pharmacogenomics variability with disease risk-Research on pharmacogenetics previously unreported due to negative resultsStudies must be well-designed, have a plausible hypothesis, have good statistical power, rigorous data analysis methods, and assess confounding factors that might influence the results. These could include, for instance, case-control studies, GWAS or NextGen sequencing data for pharmacogenes that have not been reported, because of being negative, or meta-analyses with negative findings that make a substantial contribution to the working hypothesis, provided that the working hypothesis is solid and based on sound published evidence.
This Research Topic is the second edition, looking to expand upon the original collection Editor's Feature: Negative Findings in Pharmacogenetics and PharmacogenomicsIn the field of Pharmacogenetics and Pharmacogenomics, there is a significant bias towards publishing positive results over negative or null findings, despite the latter often being well-supported by sound biological reasoning, suitable sample sizes, and robust design. This trend perpetuates a publication bias that skews the scientific record and can mislead research priorities by omitting crucial data. Publishing studies with negative results can prevent unnecessary duplication of research efforts, minimizing both waste of public and private resources and delay in real scientific advancement.This Research Topic aims to push forward the publication of well-designed, statistically powered studies yielding negative or null conclusions. These efforts are essential for gathering key data that can correct the existing publication bias and provide a basis for developing practical applications in pharmacogenetics and pharmacogenomics.We invite submissions of original studies or meta-analyses focusing on negative or null results related to pharmacogenetics, pharmacogenomics, and associated areas such as pharmacokinetics, pharmacodynamics, polymorphic drug metabolism and transport, and drug-drug interactions. Topics include, but are not limited, to:-Studies on the in vitro effects of genetic variations.-Studies on the in vivo effects of genetic variations.-Association studies of Pharmacogenetics or Pharmacogenomics variability with disease risk-Research on pharmacogenetics previously unreported due to negative resultsStudies must be well-designed, have a plausible hypothesis, have good statistical power, rigorous data analysis methods, and assess confounding factors that might influence the results. These could include, for instance, case-control studies, GWAS or NextGen sequencing data for pharmacogenes that have not been reported, because of being negative, or meta-analyses with negative findings that make a substantial contribution to the working hypothesis, provided that the working hypothesis is solid and based on sound published evidence.