Pharmacokinetics and Pharmacodynamic Effect of a Blood-Brain Barrier-Crossing Fusion Protein Therapeutic for Alzheimer’s Disease in Rat and Dog
Bibliographic record
Abstract
PURPOSE: We have recently demonstrated the brain-delivery of an Amyloid-ß oligomer (Aßo)-binding peptide-therapeutic fused to the BBB-crossing single domain antibody FC5. The bi-functional fusion protein, FC5-mFc-ABP (KG207-M) lowered both CSF and brain Aß levels after systemic dosing in transgenic mouse and rat models of Alzheimer's disease (AD). For development as a human therapeutic, we have humanized and further engineered the fusion protein named KG207-H. The purpose of the present study was to carry out comparative PK/PD studies of KG207-H in wild type rat and beagle dogs (middle-aged and older) to determine comparability of systemic PK and CSF exposure between rodent species and larger animals with more complex brain structure such as dogs. METHOD: Beagle dogs were used in this study as they accumulate cerebral Aß with age, as seen in human AD patients, and can serve as a model of sporadic AD. KG207-H (5 to 50 mg/kg) was administered intravenously and serum and CSF samples were serially collected for PK studies and to assess target engagement. KG207-H and Aβ levels were quantified using multiplexed selected reaction monitoring mass spectrometry. RESULTS: After systemic dosing, KG207-H demonstrated similar serum pharmacokinetics in rats and dogs. KG207-H appeared in the CSF in a time- and dose-dependent manner with similar kinetics, indicating CNS exposure. Further analyses revealed a dose-dependent inverse relationship between CSF KG207-H and Aß levels in both species indicating target engagement. CONCLUSION: This study demonstrates translational attributes of BBB-crossing Aβ-targeting biotherapeutic KG207-H in eliciting a pharmacodynamic response, from rodents to larger animal species.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".