Are Animal Studies of Antipsychotics Appropriately Dosed?: Lessons from the Bedside to the Bench
Bibliographic record
Abstract
Animal models are crucial for understanding the mechanism of action of antipsychotics. However, the dose of an antipsychotic in animal studies is often arbitrarily chosen, with haloperidol 1 mg/kg being a rather common standard. Recent clinical positron emission tomography (PET) studies in patients show all antipsychotics to block dopamine D2 receptors, and most are effective at doses that lead to 60% to 80% D2 occupancy. When occupancy exceeds 80%, the incidence of side effects rises sharply. To use this "bedside" information to inform the "bench," we measured D2 occupancy in rats using a method similar in principle to the [11C]-raclopride PET method in humans. We found that: 1) as in humans, haloperidol is effective in animal models of antipsychotic action when D2 occupancy > 70% and leads to effects in models of extrapyramidal side effects when D2 occupancy is > 80%; 2) very low doses, 0.06 mg/kg/sc, cause acute D2 occupancy of 75%; 3) and even doses that acutely saturate D2 receptors give little D2 occupancy after 24 hours due to the very short half-life of haloperidol in rats (2.5 hours versus 24 hours in humans). We conclude that most previous animal studies of antipsychotics have used doses giving rise to inappropriately high acute D2 occupancy and inappropriately low D2 occupancy between doses. We exemplify how this dosing confounder could lead to inappropriate conclusions. Data from the bedside translated to the bench--using D2 occupancy as a mediating variable--will lead to more valid animal models.
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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 | 0.077 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.018 |
| Scholarly communication | 0.005 | 0.015 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.016 |
| 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".