Pharmacokinetics, biodistribution and toxicology of novel cell-penetrating peptides
Bibliographic record
Abstract
Abstract Cell-penetrating peptides (CPPs) have been used in basic and preclinical research in the past 30 years to facilitate drug delivery into target cells. However, translation toward the clinic has not been successful so far. Here, we studied the pharmacokinetic (PK) and biodistribution profiles of Shuttle cell-penetrating peptides (S-CPP) in rodents, combined or not with an immunoglobulin G (IgG) cargo. We compared two enantiomers of S-CPP that contain both a protein transduction domain and an endosomal escape domain, with previously shown capacity for cytoplasmic delivery. The plasma concentration versus time curve of both radiolabelled S-CPPs required a two-compartment PK analytical model, which showed a fast distribution phase (t 1/2 α ranging from 1.25 to 3 min) followed by a slower elimination phase (t 1/2 β ranging from 5 to 15 h) after intravenous injection. Cargo IgG combined to S-CPPs displayed longer elimination half-life, of up to 25 h. The fast decrease in plasma concentration of S-CPPs was associated with an accumulation in target organs assessed at 1 and 5 h post-injection, particularly in the liver. In addition, in situ cerebral perfusion (ISCP) of L-S-CPP yielded a brain uptake coefficient of 7.2 ± 1.1 µl g −1 s −1 , consistent with penetration across the blood–brain barrier (BBB), without damaging its integrity in vivo. No sign of peripheral toxicity was detected either by examining hematologic and biochemical blood parameters, or by measuring cytokine levels in plasma. In conclusion, S-CPPs are promising non-toxic transport vectors for improved tissue distribution of drug cargos in vivo.
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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 | 0.000 | 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 | 0.000 |
| 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".