Can<i>in vitro</i>assessment provide relevant end points for cognitive drug programs?
Bibliographic record
Abstract
Several start-up biotechnology companies have been created with the primary intent of developing cognitive enhancers. In addition, established pharmaceutical companies also frequently focus their efforts on cognitive drug discovery. In many instances, the rationale and evidence for these endeavors are based largely on in vitro assessments. In particular, the experimental paradigm, know as long-term potentiation (LTP), a cellular model of synaptic plasticity and memory encoding, is being increasing used preclinically for assessing potential nootropic drugs in vitro. Central to this thinking is the idea that the modulation of LTP and/or glutamate receptors are the key criteria that must be met for the development of cognitive enhancers. However, programs targeting the NMDA receptor, a glutamate receptor subtype, over the years have been less than fruitful. In addition, skeptics criticize the relevance of some in vitro tests such as LTP for simulating human cognitive function. Given these considerations, one may wonder if in vitro assessments in general, and the LTP paradigm in particular, provide relevant end points for cognitive drug discovery and development programs. The focus of this article is to address this question and to present evidence as to why in vitro assessment is still critical to the success of any cognitive drug program.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".