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Record W3194299440 · doi:10.3389/fphar.2021.722889

An Overview of Cell-Based Assay Platforms for the Solute Carrier Family of Transporters

2021· review· en· W3194299440 on OpenAlexaff
Vojtech Dvorak, Tabea Wiedmer, Álvaro Inglés‐Prieto, Patrick Altermatt, Helena Batoulis, Felix Bärenz, Eckhard Bender, Daniela Digles, Franz Dürrenberger, Laura H. Heitman, Adriaan P. IJzerman, Douglas B. Kell, Stefanie Kickinger, Daniel Körzö, Philipp Leippe, Thomas Licher, Vania Manolova, Riccardo Rizzetto, Francesca Sassone, Lia Scarabottolo, Avner Schlessinger, Vanessa Schneider, Hubert J. Sijben, Anna-Lena Steck, Hanna Sundström, Sara Tremolada, Maria Wilhelm, Marina Wright Muelas, Diana Zindel, Claire M. Steppan, Giulio Superti‐Furga

Bibliographic record

VenueFrontiers in Pharmacology · 2021
Typereview
Languageen
FieldMedicine
TopicDrug Transport and Resistance Mechanisms
Canadian institutionsDiscovery Centre
FundersDirectorate for Biological SciencesNational Institutes of HealthInnovative Medicines InitiativeNovo Nordisk FondenVienna Science and Technology FundVifor PharmaPfizerSanofiEuropean CommissionNational Institute of General Medical SciencesNovo NordiskÖsterreichischen Akademie der WissenschaftenEuropean Federation of Pharmaceutical Industries and AssociationsBiotechnology and Biological Sciences Research CouncilAustrian Science FundBayer
KeywordsDruggabilityDrug discoveryComputational biologySUPERFAMILYSolute carrier familyBioinformaticsBiologyComputer scienceMedicineTransporterBiochemistry

Abstract

fetched live from OpenAlex

The solute carrier (SLC) superfamily represents the biggest family of transporters with important roles in health and disease. Despite being attractive and druggable targets, the majority of SLCs remains understudied. One major hurdle in research on SLCs is the lack of tools, such as cell-based assays to investigate their biological role and for drug discovery. Another challenge is the disperse and anecdotal information on assay strategies that are suitable for SLCs. This review provides a comprehensive overview of state-of-the-art cellular assay technologies for SLC research and discusses relevant SLC characteristics enabling the choice of an optimal assay technology. The Innovative Medicines Initiative consortium RESOLUTE intends to accelerate research on SLCs by providing the scientific community with high-quality reagents, assay technologies and data sets, and to ultimately unlock SLCs for drug discovery.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
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 head0.079
GPT teacher head0.384
Teacher spread0.305 · 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 designNot applicable
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

Citations70
Published2021
Admission routes1
Has abstractyes

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