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Record W2095803843 · doi:10.1093/jac/dku117

Measurements of the in vitro anti-mycobacterial activity of ivermectin are method-dependent--authors' response

2014· letter· en· W2095803843 on OpenAlexaff
Santiago Ramón‐García, Catherine Vilchèze, Louis Lim, C. Ng, William R. Jacobs, Charles J. Thompson

Bibliographic record

VenueJournal of Antimicrobial Chemotherapy · 2014
Typeletter
Languageen
FieldMedicine
TopicParasitic Diseases Research and Treatment
Canadian institutionsVancouver Hospital and Health Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsIvermectinIn vitroMicrobiologyBiologyMedicinePharmacologyImmunologyVeterinary medicineBiochemistry

Abstract

fetched live from OpenAlex

Sir, Discovering and developing new drugs for treating tuberculosis (TB) is a complex and challenging endeavour and very few drugs have been found that are clinically effective. To be effective, drugs must enter the plasma and move to disperse tissues in which mycobacterial cells reside, both intracellularly and extracellularly. Furthermore, mycobacterial cells residing in these environments are in different physiological states, and therefore likely to have associated differences in drug susceptibilities.1 It is clear that no single drug in our limited TB drug pool can effectively reach and kill all mycobacterial subpopulations. Discarding potential TB drugs based only on plasma indices or intracellular activity, as Muhammed Ameen and Drancourt2 propose, might be a relevant selection criterion if large numbers of clinically tested drugs with activity in vitro were available; however, this is currently not the case for TB drugs. Given this situation, we cannot afford to ignore active drug candidates that have been used clinically for other purposes. Ivermectin is approved for human use in many countries to treat onchocerciasis, lymphatic filariasis, strongyloidiasis and scabies. Muhammed Ameen and Drancourt2 emphasize that effective dosage levels for these conditions are unusually low and would not be effective for TB treatment. Ivermectin is typically administered once a month at a standard dose of 12 mg (maximal concentration in plasma of ∼50 ng/mL3). However, very little is known about the safety and tolerability of ivermectin at higher doses or after more frequent administration. A study in healthy volunteers showed that doses 10 times higher (120 mg) were safe and correlated with higher plasma concentrations (∼0.25 μg/mL).4 In fact, the more severe reactions observed in the treatment of onchocerciasis and lymphatic filariasis with ivermectin are most likely to be secondary immunological effects triggered by the death of the parasite. Thus, higher ivermectin dosages should be explored for TB treatment. Furthermore, we have recently demonstrated that synergistic drug combinations could allow the use of drugs that normally do not inhibit Mycobacterium tuberculosis at clinically relevant concentrations.5 Exploring the synergistic interactions of ivermectin with current anti-TB drugs could allow its use in combinatorial therapies for multidrug-resistant and extensively drug-resistant TB at dosages lower than the MICs of the individual drugs. In summary, our recent discovery showing direct in vitro anti-mycobacterial activity of the avermectins represents only a first step in the long, complex and challenging process of TB drug selection and development. Determining whether ivermectin, or other avermectins, could supplement the current TB armamentarium would require a highly interdisciplinary and comprehensive drug development approach. None to declare.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.014
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0140.016
Insufficient payload (model declined to judge)0.0060.008

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 head0.039
GPT teacher head0.340
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations0
Published2014
Admission routes1
Has abstractyes

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