Pharmacokinetics and Pharmacodynamics of Lipidic Nano-Particles in Cancer
Bibliographic record
Abstract
Nanoscale drug delivery systems (DDS) are used to circumvent some of the non-ideal properties of conventional anticancer chemotherapy drugs. Manipulation of the physical properties of DDS provides improved control over the pharmacokinetics (PK) and pharmacodynamics (PD) of the encapsulated drugs relative to free drugs. Liposomes are the archetypical nanoscale DDS and the first of these received clinical approval in 1990. DOXIL, liposomal doxorubicin, was the first commercially available liposomal anticancer drug (1995). It has an enhanced circulation half-life compared to the free drug because of its surface-grafted polyethylene glycol coating. DOXIL passively targets solid tumors, and once the liposomes localize in the tumor interstitial space, the cytotoxic drug is slowly released within the tumor. Liposomes can act as sustained release delivery system and manipulation of properties such as, liposome diameter, drug release rate, bioavailability and dosing schedule can significantly impact the therapeutic outcome of the liposomal drugs. This review will focus on how alteration of these properties can impact the therapeutic efficacy and side effect profiles of DDS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".