Matches in SemOpenAlex for { <https://semopenalex.org/work/W3171072207> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W3171072207 endingPage "i36" @default.
- W3171072207 startingPage "i36" @default.
- W3171072207 abstract "Abstract Introduction Image-based phenotypic drug profiling is receiving increasing attention in drug discovery and precision medicine. Compared to classical end-point measurements quantifying drug response, image-based profiling enables both the quantification of drug response and characterization of disease entities and drug mechanisms of actions. In pediatric precision oncology, we aim to study drug response in patient-derived 3D spheroid tumor cell cultures and tackle the challenges of a lack of image-segmentation methods and limited patient-derived material. Methods We investigate deep transfer learning with patient-by-patient fine-tuning for cell-viability quantification. We fine-tune a convolutional neural network (pre-trained on ImageNet) with many cell-line-specific and few patient-specific assay controls. The method is validated using 3D cell cultures in 384-well microplates derived from cell lines with known drug sensitivities and tested with primary patient-derived samples. Network outputs at different drug concentrations are used for drug-sensitivity scoring; dense-layer activations are used in t-distributed stochastic neighbor embedding and clustering of drugs. Results Cell-line experiments confirm expected hits, such as effective treatment with BRAF inhibitors in a BRAF V600E mutated brain tumor model and NTRK inhibitors in a cell line harboring an NTRK-fusion, indicating the predictive power of deep learning to identify drug-hit candidates for individual patients. In patient-derived samples, clustering of drugs further confirms phenotypic similarity according to their mechanisms of actions. Combining drug scoring with phenotypic clustering may provide opportunities for complementary combination treatments. Conclusion Deep transfer learning with patient-by-patient fine-tuning is a promising, segmentation-free image-analysis approach for precision medicine and drug discovery based on 3D spheroid cell cultures." @default.
- W3171072207 created "2021-06-22" @default.
- W3171072207 creator A5004020500 @default.
- W3171072207 creator A5005372827 @default.
- W3171072207 creator A5017416578 @default.
- W3171072207 creator A5019911093 @default.
- W3171072207 creator A5044923549 @default.
- W3171072207 creator A5050777133 @default.
- W3171072207 creator A5071523423 @default.
- W3171072207 date "2021-06-01" @default.
- W3171072207 modified "2023-09-26" @default.
- W3171072207 title "TMOD-04. IMAGE-BASED DRUG RESPONSE PROFILING FROM PEDIATRIC TUMOR CELL SPHEROIDS USING PATIENT-BY-PATIENT DEEP TRANSFER LEARNING" @default.
- W3171072207 doi "https://doi.org/10.1093/neuonc/noab090.145" @default.
- W3171072207 hasPublicationYear "2021" @default.
- W3171072207 type Work @default.
- W3171072207 sameAs 3171072207 @default.
- W3171072207 citedByCount "0" @default.
- W3171072207 crossrefType "journal-article" @default.
- W3171072207 hasAuthorship W3171072207A5004020500 @default.
- W3171072207 hasAuthorship W3171072207A5005372827 @default.
- W3171072207 hasAuthorship W3171072207A5017416578 @default.
- W3171072207 hasAuthorship W3171072207A5019911093 @default.
- W3171072207 hasAuthorship W3171072207A5044923549 @default.
- W3171072207 hasAuthorship W3171072207A5050777133 @default.
- W3171072207 hasAuthorship W3171072207A5071523423 @default.
- W3171072207 hasBestOaLocation W31710722071 @default.
- W3171072207 hasConcept C108583219 @default.
- W3171072207 hasConcept C111919701 @default.
- W3171072207 hasConcept C119857082 @default.
- W3171072207 hasConcept C142724271 @default.
- W3171072207 hasConcept C154945302 @default.
- W3171072207 hasConcept C163763905 @default.
- W3171072207 hasConcept C187191949 @default.
- W3171072207 hasConcept C2780035454 @default.
- W3171072207 hasConcept C2994119904 @default.
- W3171072207 hasConcept C41008148 @default.
- W3171072207 hasConcept C70721500 @default.
- W3171072207 hasConcept C71924100 @default.
- W3171072207 hasConcept C73555534 @default.
- W3171072207 hasConcept C81363708 @default.
- W3171072207 hasConcept C86803240 @default.
- W3171072207 hasConcept C98274493 @default.
- W3171072207 hasConceptScore W3171072207C108583219 @default.
- W3171072207 hasConceptScore W3171072207C111919701 @default.
- W3171072207 hasConceptScore W3171072207C119857082 @default.
- W3171072207 hasConceptScore W3171072207C142724271 @default.
- W3171072207 hasConceptScore W3171072207C154945302 @default.
- W3171072207 hasConceptScore W3171072207C163763905 @default.
- W3171072207 hasConceptScore W3171072207C187191949 @default.
- W3171072207 hasConceptScore W3171072207C2780035454 @default.
- W3171072207 hasConceptScore W3171072207C2994119904 @default.
- W3171072207 hasConceptScore W3171072207C41008148 @default.
- W3171072207 hasConceptScore W3171072207C70721500 @default.
- W3171072207 hasConceptScore W3171072207C71924100 @default.
- W3171072207 hasConceptScore W3171072207C73555534 @default.
- W3171072207 hasConceptScore W3171072207C81363708 @default.
- W3171072207 hasConceptScore W3171072207C86803240 @default.
- W3171072207 hasConceptScore W3171072207C98274493 @default.
- W3171072207 hasIssue "Supplement_1" @default.
- W3171072207 hasLocation W31710722071 @default.
- W3171072207 hasOpenAccess W3171072207 @default.
- W3171072207 hasPrimaryLocation W31710722071 @default.
- W3171072207 hasRelatedWork W10138567 @default.
- W3171072207 hasRelatedWork W11178864 @default.
- W3171072207 hasRelatedWork W14576825 @default.
- W3171072207 hasRelatedWork W5520083 @default.
- W3171072207 hasRelatedWork W6056146 @default.
- W3171072207 hasRelatedWork W7303821 @default.
- W3171072207 hasRelatedWork W9190101 @default.
- W3171072207 hasRelatedWork W11757927 @default.
- W3171072207 hasRelatedWork W18025448 @default.
- W3171072207 hasRelatedWork W35192 @default.
- W3171072207 hasVolume "23" @default.
- W3171072207 isParatext "false" @default.
- W3171072207 isRetracted "false" @default.
- W3171072207 magId "3171072207" @default.
- W3171072207 workType "article" @default.