Imaging of enzyme replacement therapy using PET
Bibliographic record
Abstract
Direct enzyme replacement therapy (ERT) has been introduced as a means to treat a number of rare, complex genetic conditions associated with lysosomal dysfunction. Gaucher disease was the first for which this therapy was applied and remains the prototypical example. Although ERT using recombinant lysosomal enzymes has been shown to be effective in altering the clinical course of Gaucher disease, Fabry disease, Hurler syndrome, Hunter syndrome, Maroteaux-Lamy syndrome, and Pompe disease, the recalcitrance of certain disease manifestations underscores important unanswered questions related to dosing regimes, tissue half-life of the recombinant enzyme and the ability of intravenously administered enzyme to reach critical sites of known disease pathology. We have developed an innovative method for tagging acid beta-glucocerebrosidase (GCase), the recombinant enzyme formulated in Cerezyme(R) used to treat Gaucher disease, using an (18)F-labeled substrate analogue that becomes trapped within the active site of the enzyme. Using micro-PET we show that the tissue distribution of injected enzyme can be imaged in a murine model and that the PET data correlate with tissue (18)F counts. Further we show that PET imaging readily monitors pharmacokinetic changes effected by receptor blocking. The ability to (18)F-label GCase to monitor the enzyme distribution and tissue half-life in vivo by PET provides a powerful research tool with an immediate clinical application to Gaucher disease and a clear path for application to other ERTs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".