Drug Transport Across the Blood-Brain Barrier and the Impact of Breast Cancer Resistance Protein (ABCG2)
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
With the discovery of novel therapeutic targets within the central nervous system (CNS), there has been a significant effort to synthesize a multitude of drug molecules with increasing potency and selectivity. However, the impact of the blood-brain barrier (BBB) in limiting effective concentrations of drug candidate from reaching the brain parenchyma is often ignored, resulting in a lack of efficacy when administered to animal models or humans. Intercellular drug transport across the BBB is negligible due to the impermeable tight junctions formed by interconnecting endothelial cells. Furthermore, drug permeability via the transcellular route cannot be assumed for all molecules due to the high expression of drug efflux transport proteins, which effectively extrude compounds from the brain endothelial cell back into the cerebral vasculature. In addition to the extensively-studied P-glycoprotein (P-gp, ABCB1), the brain endothelial cells also express multidrug resistance associated proteins (MRP, ABCC) and breast cancer resistance protein (BCRP, ABCG2), amongst other efflux transporters. While more research has focussed on the impact of P-gp and MRP on drug transport across the BBB, the role of ABCG2 in limiting exposure of drug molecules to the CNS is now becoming more clearly understood. The purpose of this review, therefore, is to summarise the findings of the various studies assessing the expression profile of ABCG2 at the BBB, to provide an overview on the current research being undertaken to identify specific ABCG2 inhibitors with therapeutic benefit, and to critically assess the functional role of ABCG2 on drug transport across the BBB.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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