Considerations on pharmacodynamics and pharmacokinetics: Can everything be explained by the extent of drug binding to its receptor?
Bibliographic record
Abstract
It is frequently assumed that pharmacological responses depend solely on the extent of drug binding to its receptor according to the occupational theory. It is therefore presumed that the intensity of the effect is determined by drug concentration at its receptor site, yielding a unique concentration-effect relationship. However, when dependence, abstinence, and tolerance phenomena occur, as well as for pharmacological responses in vivo that are modulated by homeostatic mechanisms, the rate of drug input shifts the concentration-effect relationship. Hence, such responses cannot be explained on the sole basis of the extent of drug binding to its receptor. Information on the cellular and molecular processes involved in the generation of abstinence, dependence, and tolerance will undoubtedly result in the development of pharmacodynamic models allowing a satisfactory explanation of drug effects modulated by these phenomena. Notwithstanding, integrative physiology concepts are required to develop pharmacokinetic-pharmacodynamic models allowing the description of drug effects in an intact organism. It is therefore important to emphasize that integrative physiology cannot be neglected in pharmacology teaching and research, but should be considered as an equally valuable tool as molecular biology and other biomedical disciplines for the understanding of pharmacological effects.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.018 |
| Scholarly communication | 0.003 | 0.013 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".