Designing Polymeric Binders for Pharmaceutical Applications
Bibliographic record
Abstract
The properties of polyvalent polymers to form supramolecular complexes with biological substrates offer many attractive therapeutic possibilities. Polymeric binders are macromolecules designed to exert a pharmacological effect by selectively interacting with exogenous or endogenous substrates. They can be employed to prevent the harmful effects of toxins, inhibit virus colonization or even trigger apoptosis of diseased cells. This chapter presents the fundamentals of developing polymeric binders as new drug entities. The basics of finding the right target, establishing structure–activity relationships and measuring efficacy are highlighted, with numerous examples of polymeric binders at different development stages, including commercialization. Orally administered scavengers represent the most advanced examples in clinical use. Their binding in the gastrointestinal tract results in either local or systemic therapeutic effects. Although they are designed to be non-absorbable, their low systemic exposure is not always devoid of side effects. The required approaches to confirm innocuousness of the macromolecules and the challenges encountered during the clinical phases are also presented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.011 |
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".