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Record W2626352507 · doi:10.1089/nat.2017.0671

Recommendations of the Oligonucleotide Safety Working Group's Formulated Oligonucleotide Subcommittee for the Safety Assessment of Formulated Oligonucleotide-Based Therapeutics

2017· article· en· W2626352507 on OpenAlexaff
Jennifer Marlowe, Violetta Akopian, Priya Karmali, Douglas J. Kornbrust, Jennifer A. Lockridge, Sean C. Semple

Bibliographic record

VenueNucleic Acid Therapeutics · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsArbutus Biopharma (Canada)
Fundersnot available
KeywordsOligonucleotideComputational biologyDrug developmentPharmacologyDrugComputer scienceMedicineRisk analysis (engineering)BiologyBiochemistry

Abstract

fetched live from OpenAlex

The use of lipid formulations has greatly improved the ability to effectively deliver oligonucleotides and has been instrumental in the rapid expansion of therapeutic development programs using oligonucleotide drugs. However, the development of such complex multicomponent therapeutics requires the implementation of unique, scientifically sound approaches to the nonclinical development of these drugs, based upon a hybrid of knowledge and experiences drawn from small molecule, protein, and oligonucleotide therapeutic drug development. The relative paucity of directly applicable regulatory guidance documents for oligonucleotide therapeutics in general has resulted in the generation of multiple white papers from oligonucleotide drug development experts and members of the Oligonucleotide Safety Working Group (OSWG). The members of the Formulated Oligonucleotide Subcommittee of the OSWG have utilized their collective experience working with a variety of formulations and their associated oligonucleotide payloads, as well as their insights into regulatory considerations and expectations, to generate a series of consensus recommendations for the pharmacokinetic characterization and nonclinical safety assessment of this unique class of therapeutics. It should be noted that the focus of Subcommittee discussions was on lipid nanoparticle and other types of particulate formulations of therapeutic oligonucleotides and not on conjugates or other types of modifications of oligonucleotide structure intended to facilitate delivery.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.040
GPT teacher head0.312
Teacher spread0.272 · 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.

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

Citations32
Published2017
Admission routes1
Has abstractyes

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