Clinical significance of organic anion transporting polypeptides (OATPs) in drug disposition: their roles in hepatic clearance and intestinal absorption
Bibliographic record
Abstract
Organic anion transporting polypeptide (OATP) family transporters accept a number of drugs and are increasingly being recognized as important factors in governing drug and metabolite pharmacokinetics. OATP1B1 and OATP1B3 play an important role in hepatic drug uptake while OATP2B1 and OATP1A2 might be key players in intestinal absorption and transport across blood-brain barrier of drugs, respectively. To understand the importance of OATPs in the hepatic clearance of drugs, the rate-determining process for elimination should be considered; for some drugs, hepatic uptake clearance rather than metabolic intrinsic clearance is the more important determinant of hepatic clearances. The importance of the unbound concentration ratio (liver/blood), K(p,uu) , of drugs, which is partly governed by OATPs, is exemplified in interpreting the difference in the IC(50) of statins between the hepatocyte and microsome systems for the inhibition of HMG-CoA reductase activity. The intrinsic activity and/or expression level of OATPs are affected by genetic polymorphisms and drug-drug interactions. Their effects on the elimination rate or intestinal absorption rate of drugs may sometimes depend on the substrate drug. This is partly because of the different contribution of OATP isoforms to clearance or intestinal absorption. When the contribution of the OATP-mediated pathway is substantial, the pharmacokinetics of substrate drugs should be greatly affected. This review describes the estimation of the contribution of OATP1B1 to the total hepatic uptake of drugs from the data of fold-increases in the plasma concentration of substrate drugs by the genetic polymorphism of this transporter. To understand the importance of the OATP family transporters, modeling and simulation with a physiologically based pharmacokinetic model are helpful.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".