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Record W4379208474 · doi:10.55927/ijsmr.v1i4.4374

Genetic Pharmacotherapy

2023· article· en· W4379208474 on OpenAlexfundno aff
Rehan Haider

Bibliographic record

VenueInternational Journal of Scientific Multidisciplinary Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsnot available
FundersUniversity of Calgary
KeywordsPharmacotherapyDrug developmentDrugComputational biologyDrug targetMedicineNeurosciencePharmacologyBiologyComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

In current drug development, proof-of-concept—determining whether a ligand engaging its target is likely to be therapeutic—requires specific ligands. This presents a catch-22, as the motivation to develop ligands requires proof-of-concept studies that cannot be conducted without ligands. A strategy we term genetic pharmacotherapy—a refinement of genetic blockade focused on drug-gable targets—obviates the catch-22 by enabling proof-of-concept studies before the development of specific ligands via genetic means in mouse models. In this strategy, which could help avert investment in molecular entities that will ultimately prove therapeutically efficacious, a gene is conditionally down-regulated via a molecular switch in adult mice. Both the precise temporal control of the intervention and the consequent change in the target protein function parallels the administration of drugs, with the additional advantage of perfect specificity. Moreover, genetic pharmacotherapy overcomes the impediment of the blood-brain barrier, which makes developing ligands for psychiatric disorders particularly challenging

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.085
GPT teacher head0.446
Teacher spread0.362 · 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 designBench or experimental
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Scientific Multidisciplinary ResearchSame topicProtein Degradation and InhibitorsFrench-language works237,207