The emerging era of pharmacogenomics: current successes, future potential, and challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The vast range of genetic diversity contributes to a wonderful array of human traits and characteristics. Unfortunately, a consequence of this genetic diversity is large variability in drug response between people, meaning that no single medication is safe and effective in everyone. The debilitating and sometimes deadly consequences of adverse drug reactions (ADRs) are a major and unmet problem of modern medicine. Pharmacogenomics can uncover associations between genetic variation and drug safety and has the potential to predict ADRs in individual patients. Here we review pharmacogenomic successes leading to changes in clinical practice, as well as clinical areas probably to be impacted by pharmacogenomics in the near future. We also discuss some of the challenges, and potential solutions, that remain for the implementation of pharmacogenomic testing into clinical practice for the significant improvement of drug safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it