Impact of Genetic Variation in OATP Transporters to Drug Disposition and Response
Bibliographic record
Abstract
There has been remarkable progress during the past decade in understanding of how genetic variations in drug metabolizing enzymes and transporters contribute to observed variation in drug responsiveness. Among drug transporters, the organic anion transporting polypeptide (OATP) class of transporters have proven to be remarkably important to the cellular uptake disposition of a variety of clinically important drugs, particularly in organs such as the intestine and liver; we now know that altered OATP activity may confer reduced efficacy and potentially increased risk of drug-related toxicity. OATP1B1 and OATP1B3 are widely recognized liver-specific members of the family known to modulate the hepatocellular uptake of drugs from the portal vein and thereby modulate systemic exposure and hepatic substrate drug extraction. On the other hand, OATP2B1 and OATP1A2 are expressed on the apical membrane of intestinal enterocytes and though to affect absorption of its drug substrates. Accordingly, genetic variations in these OATP transporters have clinically relevant functional consequences for drug absorption, distribution and excretion, as well as pharmacodynamics response in terms of drug efficacy and toxicity. This article addresses the present evidence of relevance to genetic variations in OATP1B1, OATP1B3, OATP2B1, and OATP1A2 in terms of drug response, efficacy and optimal therapeutics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".