Compounds Reducing Human Sperm Motility as Potential Nonhormonal Contraceptives Identified Using a High-Throughput Phenotypic Screening Platform
Bibliographic record
Abstract
In this article, we detail our latest findings toward developing a diversified series of potential nonhormonal contraceptive compounds using a phenotypic screening approach against human sperm. Phenotypic screening of nine compound libraries (88,773 compounds in total) was conducted using an in-house automated robotic screening platform, allowing quantification of sperm motility in samples pretreated with the compounds. From these screens, 9 chemical series were identified and investigated in hit expansion programs, with a particular focus on identifying chemical matter that selectively reduces sperm motility without any significant cytotoxicity in somatic cells (HepG2 cells). While there were no clinically progressable leads identified, the study did identify some useful tool compounds for research into the fundamental biology underpinning nonhormonal contraceptive discovery, and a lot was learned about the screening technology, which sets us up for future screening to identify and develop better chemical starting points.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".