Promises and challenges of pharmacogenetics: an overview of study design, methodological and statistical issues
Bibliographic record
Abstract
Pharmacogenetics is the study of inherited variation in drug response. The goal of pharmacogenetics is to develop novel ways of maximizing drug efficacy and minimizing toxicity for individual patients. Personalized medicine has the potential to allow for a patient's genetic information to predict optimal dosage for a drug with a narrow therapeutic index, to select the most appropriate pharmacological agent for a given patient and to develop cost-effective treatments. Although there is supporting evidence in favour of pharmacogenetics, its adoption in clinical practice has been slow because of sometimes conflicting findings among studies. This failure to replicate findings may result from a lack of high-quality pharmacogenetic studies, as well as unresolved methodological and statistical issues. The objective of this review is to discuss the benefits of incorporating pharmacogenetics into clinical practice. We will also address outstanding methodological and statistical issues that may lead to heterogeneity among reported pharmacogenetic studies and how they may be addressed.
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How this classification was reachedexpand
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".