Article

Robust Prediction of Personalized In Vivo Response to Unseen Drugs From In Vitro Screens Using a Novel Context-Aware Deconfounding Autoencoder

2021-11-12

Abstract excerpt

<title>Abstract</title> <p>Accurate and robust prediction of patient-specific responses to drug treatments is critical for drug development and personalized medicine. However, patient data are often too scarce to train a generalized machine learning model. Although many methods have been developed to utilize cell line data, few of them can reliably predict individual patient clinical responses to new drugs due to...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: fda5fce9-f358-54d3-850c-c8cdcb91ec59
DOI: 10.21203/rs.3.rs-1013496/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Robust Prediction of Personalized In Vivo Response to Unseen Drugs From In Vitro Screens Using a Novel Context-Aware Deconfounding AutoencoderDOI 10.21203/rs.3.rs-1013496/v1Read

Robust Prediction of Patient-Specific Clinical Response to Unseen Drugs From in vitro Screens Using Context-aware Deconfounding AutoencoderSemantic proximity Read

Robust Prediction of Patient-Specific Clinical Response to Unseen Drugs From <i>in vitro</i> Screens Using Context-aware Deconfounding AutoencoderSemantic proximity Read

Predicting single-cell drug sensitivity utilizing adaptive weighted features for deep transfer learningSemantic proximity Read

BKDRP: A Biological Knowledge-Driven Approach for Drug Response Prediction Using Multi-Omics Data in Cancer Cell LinesSemantic proximity Read

Pan-Cancer Drug Sensitivity Prediction from Gene Expression using Deep LearningSemantic proximity Read

BioXNet: a biologically inspired neural network for deciphering anti-cancer drug response in precision medicineSemantic proximity Read

Patient Informed Domain Adaptation Improves Clinical Drug Response PredictionSemantic proximity Read

Predictive Modeling of Multiplex Chemical Phenomics for Novel Cells and Patients: Applied to Personalized Alzheimer’s Disease Drug RepurposingSemantic proximity Read

TransCDR: a deep learning model for enhancing the generalizability of drug activity prediction through transfer learning and multimodal data fusionSemantic proximity Read

Multi-Omics Modality Completion and Knowledge Distillation for Drug Response Prediction in Cervical CancerSemantic proximity Read

UniCure: A Foundation Model for Predicting Personalized Cancer Therapy ResponseSemantic proximity Read

Interpretable deep recommender system model for prediction of kinase inhibitor efficacy across cancer cell linesSemantic proximity Read