Whole-organism phenotypic screening methods used in early-phase anthelmintic drug discovery
Bibliographic record
Abstract
Diseases caused by parasitic helminths (worms) represent a major global health burden in both humans and animals. As vaccines against helminths have yet to achieve a prominent role in worm control, anthelmintics are the primary tool to limit production losses and disease due to helminth infections in both human and veterinary medicine. However, the excessive and often uncontrolled use of these drugs has led to widespread anthelmintic resistance in these worms - particularly of animals - to almost all commercially available anthelmintics, severely compromising control. Thus, there is a major demand for the discovery and development of new classes of anthelmintics. A key component of the discovery process is screening libraries of compounds for anthelmintic activity. Given the need for, and major interest by the pharmaceutical industry in, novel anthelmintics, we considered it both timely and appropriate to re-examine screening methods used for anthelmintic discovery. Thus, we reviewed current literature (1977–2021) on whole-worm phenotypic screening assays developed and used in academic laboratories, with a particular focus on those employed to discover nematocides. This review reveals that at least 50 distinct phenotypic assays with low-, medium- or high-throughput capacity were developed over this period, with more recently developed methods being quantitative, semi-automated and higher throughput. The main features assessed or measured in these assays include worm motility, growth/development, morphological changes, viability/lethality, pharyngeal pumping, egg hatching, larval migration, CO2- or ATP-production and/or enzyme activity. Recent progress in assay development has led to the routine application of practical, cost-effective, medium- to high-throughput whole-worm screening assays in academic or public-private partnership (PPP) contexts, and major potential for novel high-content, high-throughput platforms in the near future. Complementing this progress are major advances in the molecular data sciences, computational biology and informatics, which are likely to further enable and accelerate anthelmintic drug discovery and development.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".