Construction of a 10-year Pharmacogenetic Literature Database with Information on Alternative Allele Frequency: PharmGAF DB
Bibliographic record
Abstract
Background: Following the rapid growth in genetic information related to drug responses, the urgent need to organize this information for clinical use has arisen.The current databases used in Korea lack information about drug responses as they pertain to specific ethnic groups, including Koreans, and the frequency of genomic variants.This study aimed to develop a pharmacogenetics-alternative allele frequency (AAF) database (PharmGAF DB) in South Korea to address this issue.Methods: Drugs were selected from the drug response database of the Korean Ministry of Food and Drug Safety by studying various pharmacogenetic guidelines such as Clinical Pharmacogenetics Implementation Consortium, Dutch Pharmacogenetics Working Group, and Canadian Pharmacogenomics Network for Drug Safety and drug labels accepted by various health authorities such as the United States Food and Drug Administration, European Medicines Agency, and the Pharmaceuticals and Medical Devices Agency.Information on drug responses was collected and updated for a set of selected drugs from pharmacogenetics literature over the past ten years.AAF information was gathered from the Korean Reference Genome Database, the single nucleotide polymorphism database, and the Allele Frequency Net Database.Results: In total, 80 drugs were investigated, and the pharmacogenomic effects of 142 variants in relation to these drugs were updated.Pharmacokinetic effects were found for 51 variants and pharmacodynamic effects were found for 111 variants.AAF information was collected for these variants in Korean, East Asian, and Caucasian populations.Variants for which AAF significantly differed between Koreans and Caucasians were identified.Finally, PharmGAF DB was created by combining information on the pharmacogenomic effects and the AAF. Conclusion:The newly developed database, PharmGAF DB, was created by merging information on how drug responses relate to genotypes and allele frequencies among different ethnic groups.PharmGAF DB should improve drug efficacy and reduce the occurrence of side effects by supporting the implementation of precision medicine in clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.047 | 0.035 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".