Nuclear Receptors and the Regulation of Drug‐Metabolizing Enzymes and Drug Transporters: Implications for Interindividual Variability in Response to Drugs
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
Erratic or unpredictable response to drugs remains a challenge of modern drug therapy. An important determinant of such interindividual differences in drug response is variability in the expression of drug-metabolizing enzymes and/or transporters at sites of absorption and/or tissue distribution. Variable drug-metabolizing enzyme and transporter expression can result in unpredictable exposure and tissue distribution of drugs and may manifest as adverse effects or therapeutic failure. In the past decade, important new insights have been made relating to the regulatory mechanisms governing the expression of drug-metabolizing enzymes and transporters by ligand-activated nuclear receptors. Specifically, there is compelling evidence to demonstrate that PXR, CAR, FXR, LXR, VDR, HNF4alpha, and AhR form a battery of nuclear receptors that regulate the expression of many important drug-metabolizing enzyme and transporters. In this review, the authors focus on clinically important drug-metabolizing enzymes such as CYP3A4, CYP2B6, CYP2C9, CYP2C19, UGT1A1, SULT2A1, and glutathione S-transferases and their regulation by nuclear receptors. They also review the nuclear receptor-mediated regulation of drug transporters such as MDR1, MRP2, MRP4, BSEP, BCRP, NTCP, OATP1B3, and OATP1A2. Finally, they outline how the drug development process has been affected by the current understanding of the involvement of nuclear receptors in the regulation of drug disposition genes.
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 | 0.029 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 it