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Record W2107470469 · doi:10.1517/17460441.2.s1.s25

Anthelmintic discovery and development in the animal health industry

2007· article· en· W2107470469 on OpenAlexaff
Debra J. Woods, Christelle Lauret, Timothy G. Geary

Bibliographic record

VenueExpert Opinion on Drug Discovery · 2007
Typearticle
Languageen
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsMcGill University
FundersElanco Animal Health
KeywordsDrug discoveryPharmaceutical industryBusinessIdentification (biology)General partnershipIsolation (microbiology)Drug developmentInvestment (military)Paradigm shiftBiotechnologyRisk analysis (engineering)Data scienceBiologyDrugComputer sciencePharmacologyBioinformaticsPolitical scienceFinance

Abstract

fetched live from OpenAlex

Most modern anthelmintics used against human pathogens have come from the animal health (AH) industry. Historically, new molecules were discovered empirically, but recent developments in genomic and screening technologies have significantly enhanced the opportunities for target-based identification of novel therapies. However, drug discovery and development is still a complicated and costly process with high attrition. Absence of a return in investment for tropical parasitic diseases makes it difficult for large pharmaceutical companies to justify seeking antiparasitics for less developed countries in isolation. A partnership in which there is a sharing of costs and leveraging of resources is one way forward and is reflected in the new paradigm of 'integrated drug discovery', where collaborations and networks of academic institutions and industry are working together towards the discovery of new treatments for tropical parasitic diseases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.368
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2007
Admission routes1
Has abstractyes

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