MétaCan
Menu
Back to cohort
Record W4388011859 · doi:10.1016/j.omtn.2023.102066

Progress and harmonization of gene editing to treat human diseases: Proceeding of COST Action CA21113 GenE-HumDi

2023· review· en· W4388011859 on OpenAlexaff
Alessia Cavazza, Ayal Hendel, Rasmus O. Bak, Paula Rı́o, Marc Güell, Duško Lainšček, Virginia Arechavala‐Gomeza, Ling Peng, Fatma Zehra Hapil, Joshua Harvey, Francisco G. Ortega, Coral González‐Martínez, Carsten W. Lederer, Kasper Mikkelsen, Giedrius Gasiūnas, Nechama Kalter, Manuel A.F.V. Gonçalves, Julie Petersen, Alejandro Garanto, Lluı́s Montoliu, Marcello Maresca, Stefan E. Seemann, Jan Gorodkin, Loubna Mazini, Juan R. Rodríguez-Madoz, Noelia Maldonado‐Pérez, Torella Laura, Michael Schmueck‐Henneresse, Cristina Maccalli, Julian Grünewald, Gloria Carmona, Neli Kachamakova‐Trojanowska, Annarita Miccio, Francisco Martı́n, Giandomenico Turchiano, Toni Cathomen, Yonglun Luo, Shengdar Q. Tsai, Karim Benabdellah

Bibliographic record

VenueMolecular Therapy — Nucleic Acids · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsInstitute of Infection and Immunity
FundersEuropean Regional Development FundNovo Nordisk FondenConsejería de Salud y Consumo, Junta de AndalucíaJunta de AndalucíaLundbeckfondenConsejería de Transformación Económica, Industria, Conocimiento y UniversidadesConsejería de Salud y Familias, Junta de AndalucíaSteno Diabetes Center AarhusEuropean Cooperation in Science and Technology
KeywordsHarmonizationGenome editingAction (physics)BusinessEngineering ethicsKnowledge managementPolitical scienceBiotechnologyGenomeComputer scienceGeneBiologyEngineeringGenetics

Abstract

fetched live from OpenAlex

The European Cooperation in Science and Technology (COST) is an intergovernmental organization dedicated to funding and coordinating scientific and technological research in Europe, fostering collaboration among researchers and institutions across countries. Recently, COST Action funded the "Genome Editing to treat Human Diseases" (GenE-HumDi) network, uniting various stakeholders such as pharmaceutical companies, academic institutions, regulatory agencies, biotech firms, and patient advocacy groups. GenE-HumDi's primary objective is to expedite the application of genome editing for therapeutic purposes in treating human diseases. To achieve this goal, GenE-HumDi is organized in several working groups, each focusing on specific aspects. These groups aim to enhance genome editing technologies, assess delivery systems, address safety concerns, promote clinical translation, and develop regulatory guidelines. The network seeks to establish standard procedures and guidelines for these areas to standardize scientific practices and facilitate knowledge sharing. Furthermore, GenE-HumDi aims to communicate its findings to the public in accessible yet rigorous language, emphasizing genome editing's potential to revolutionize the treatment of many human diseases. The inaugural GenE-HumDi meeting, held in Granada, Spain, in March 2023, featured presentations from experts in the field, discussing recent breakthroughs in delivery methods, safety measures, clinical translation, and regulatory aspects related to gene editing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.573
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.036
GPT teacher head0.371
Teacher spread0.336 · 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
GenreReview

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

Citations9
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueMolecular Therapy — Nucleic AcidsSame topicCRISPR and Genetic EngineeringFrench-language works237,207