ADVENTURES IN TARGETING
Bibliographic record
Abstract
An overview of our experiences in the field of immunoliposomal anticancer drugs is provided with respect to choice of ligand, and choice of model system, in order to provide some guidance as to the rational use of this new technology. Liposomes targeted by either peptide or monoclonal antibodies showed significantly higher binding to their respective target cells in vitro compared to non-targeted liposomes in all model systems examined. This higher binding led to higher cytotoxicities relative to non-targeted liposomes. For the immunoliposomes to deliver their entrapped drug to target cell in vivo, long circulations half-lives are required. We have evaluated the pharmacokinetics of liposomes prepared by several different coupling techniques, and have found significant differences in the clearance of these immunoliposomes from the circulation. Immunoliposomes prepared with whole anti-CD19 IgG coupled by the Mal-PEG-DSPE method demonstrated a short plasma half-life, which may reflect the random orientation of the MAb on the liposome surface. Coupling methods that mask or eliminate the Fc region result in immunoliposomes that have clearance rates more similar to untargeted liposomes. Insertion of peptides or antibodies into pre-formed liposomes through incubation with ligand-coupled PEG micelles resulted in immunoliposomes, termed post-insertion liposomes, that demonstrated comparable in vitro binding, pharmacokinetic profiles and in vivo therapeutic efficacy to liposomes made by conventional coupling methods. The therapeutic efficacy of liposomes, prepared by various coupling methods and targeted by different ligands, was compared in several different animal models of either haematological malignancies, pseudometastatic disease or solid tumours. In our hands, successful in vivo targeting has been obtained when the target is either small or readily accessible from the vasculature, where the liposomes have longer circulating half-lives and/or where a ligand against an internalizing epitope has been chosen. These results should aid in the rational design of applications for immunoliposomal drugs in the future.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.019 | 0.012 |
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".