Matches in SemOpenAlex for { <https://semopenalex.org/work/W2994361471> ?p ?o ?g. }
Showing items 1 to 64 of
64
with 100 items per page.
- W2994361471 abstract "Recently, it has been shown how artificial intelligence (AI) has the possibility to dramatically shorten the drug development pipeline by identifying insights that may have otherwise been missed. However, one major critique of these methods has been their black-box nature and the lack of mechanistic biology. To address these issues, OneThree Biotech has developed an extensive platform of biology-driven AI approaches that accelerate early stage drug development. Beginning with novel target identification, we present ECLIPSE, an AI approach that combines genomic, cell line and experimental design features to identify essential genes within cancer cell lines, based upon CRISPR and shRNA loss-of-function screenings. We demonstrated that ECLIPSE could accurately identify known and potential cancer targets, as well as be used to determine drug efficacy in the clinic. In cases where a compound’s target is unknown, we introduce BANDIT, a Bayesian model that combines divergent data sources to predict the targets and mechanisms for small molecules with unprecedented accuracy and versatility. Using BANDIT, we successfully identified a novel class of microtubule inhibitors and a previously unknown mechanism of ONC201, an anti-cancer small molecule, which led to a successful Phase 2 trial in a rare glioblastoma. Building on these approaches, we also introduce our suite of drug synergy prediction models. These models can not only predict the level of expected drug synergy in specific cancer types, but can also be used to pinpoint the specific mechanisms of actions that contribute to synergy. Altogether, OneThree’s platform is a comprehensive AI approach that combines high quality AI with mechanistic biology to optimize early-stage drug development. Citation Format: Coryandar Gilvary, Neel Madhukar, Olivier Elemento. OneThree Biotech’s artificial intelligence platform for optimizing drug development [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr B031. doi:10.1158/1535-7163.TARG-19-B031" @default.
- W2994361471 created "2019-12-13" @default.
- W2994361471 creator A5036395961 @default.
- W2994361471 creator A5061702711 @default.
- W2994361471 creator A5068268768 @default.
- W2994361471 date "2019-12-01" @default.
- W2994361471 modified "2023-09-27" @default.
- W2994361471 title "Abstract B031: OneThree Biotech’s artificial intelligence platform for optimizing drug development" @default.
- W2994361471 doi "https://doi.org/10.1158/1535-7163.targ-19-b031" @default.
- W2994361471 hasPublicationYear "2019" @default.
- W2994361471 type Work @default.
- W2994361471 sameAs 2994361471 @default.
- W2994361471 citedByCount "0" @default.
- W2994361471 crossrefType "proceedings-article" @default.
- W2994361471 hasAuthorship W2994361471A5036395961 @default.
- W2994361471 hasAuthorship W2994361471A5061702711 @default.
- W2994361471 hasAuthorship W2994361471A5068268768 @default.
- W2994361471 hasConcept C116834253 @default.
- W2994361471 hasConcept C119857082 @default.
- W2994361471 hasConcept C121608353 @default.
- W2994361471 hasConcept C154945302 @default.
- W2994361471 hasConcept C2780035454 @default.
- W2994361471 hasConcept C3020340455 @default.
- W2994361471 hasConcept C41008148 @default.
- W2994361471 hasConcept C54355233 @default.
- W2994361471 hasConcept C59822182 @default.
- W2994361471 hasConcept C60644358 @default.
- W2994361471 hasConcept C64903051 @default.
- W2994361471 hasConcept C70721500 @default.
- W2994361471 hasConcept C74187038 @default.
- W2994361471 hasConcept C86803240 @default.
- W2994361471 hasConcept C98274493 @default.
- W2994361471 hasConceptScore W2994361471C116834253 @default.
- W2994361471 hasConceptScore W2994361471C119857082 @default.
- W2994361471 hasConceptScore W2994361471C121608353 @default.
- W2994361471 hasConceptScore W2994361471C154945302 @default.
- W2994361471 hasConceptScore W2994361471C2780035454 @default.
- W2994361471 hasConceptScore W2994361471C3020340455 @default.
- W2994361471 hasConceptScore W2994361471C41008148 @default.
- W2994361471 hasConceptScore W2994361471C54355233 @default.
- W2994361471 hasConceptScore W2994361471C59822182 @default.
- W2994361471 hasConceptScore W2994361471C60644358 @default.
- W2994361471 hasConceptScore W2994361471C64903051 @default.
- W2994361471 hasConceptScore W2994361471C70721500 @default.
- W2994361471 hasConceptScore W2994361471C74187038 @default.
- W2994361471 hasConceptScore W2994361471C86803240 @default.
- W2994361471 hasConceptScore W2994361471C98274493 @default.
- W2994361471 hasLocation W29943614711 @default.
- W2994361471 hasOpenAccess W2994361471 @default.
- W2994361471 hasPrimaryLocation W29943614711 @default.
- W2994361471 hasRelatedWork W10562162 @default.
- W2994361471 hasRelatedWork W10925699 @default.
- W2994361471 hasRelatedWork W3524434 @default.
- W2994361471 hasRelatedWork W447235 @default.
- W2994361471 hasRelatedWork W5023946 @default.
- W2994361471 hasRelatedWork W5067772 @default.
- W2994361471 hasRelatedWork W790358 @default.
- W2994361471 hasRelatedWork W8010423 @default.
- W2994361471 hasRelatedWork W8588242 @default.
- W2994361471 hasRelatedWork W3107350 @default.
- W2994361471 isParatext "false" @default.
- W2994361471 isRetracted "false" @default.
- W2994361471 magId "2994361471" @default.
- W2994361471 workType "article" @default.