{"id":"https://openalex.org/W4406260753","doi":"https://doi.org/10.1109/bibm62325.2024.10822746","title":"CTP-LLM: Clinical Trial Phase Transition Prediction Using Large Language Models","display_name":"CTP-LLM: Clinical Trial Phase Transition Prediction Using Large Language Models","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406260753","doi":"https://doi.org/10.1109/bibm62325.2024.10822746"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822746","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822746","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006296381","display_name":"Michael Reinisch","orcid":"https://orcid.org/0009-0007-0606-6771"},"institutions":[{"id":"https://openalex.org/I181401687","display_name":"American University","ror":"https://ror.org/052w4zt36","country_code":"US","type":"education","lineage":["https://openalex.org/I181401687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Reinisch","raw_affiliation_strings":["American University,Department of Computer Science,Washington DC,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"American University,Department of Computer Science,Washington DC,USA","institution_ids":["https://openalex.org/I181401687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103255246","display_name":"Jianfeng He","orcid":"https://orcid.org/0000-0001-8572-4806"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianfeng He","raw_affiliation_strings":["Virginia Tech,Department of Computer Science,Falls Church,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech,Department of Computer Science,Falls Church,USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076513042","display_name":"Chenxi Liao","orcid":"https://orcid.org/0000-0001-5704-1880"},"institutions":[{"id":"https://openalex.org/I181401687","display_name":"American University","ror":"https://ror.org/052w4zt36","country_code":"US","type":"education","lineage":["https://openalex.org/I181401687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenxi Liao","raw_affiliation_strings":["American University,Department of Neuroscience,Washington DC,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"American University,Department of Neuroscience,Washington DC,USA","institution_ids":["https://openalex.org/I181401687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017272529","display_name":"Sauleh Siddiqui","orcid":"https://orcid.org/0000-0002-2466-8924"},"institutions":[{"id":"https://openalex.org/I181401687","display_name":"American University","ror":"https://ror.org/052w4zt36","country_code":"US","type":"education","lineage":["https://openalex.org/I181401687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sauleh Siddiqui","raw_affiliation_strings":["American University,Department of Environmental Science,Washington DC,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"American University,Department of Environmental Science,Washington DC,USA","institution_ids":["https://openalex.org/I181401687"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088099909","display_name":"Bei Xiao","orcid":"https://orcid.org/0000-0002-5055-5712"},"institutions":[{"id":"https://openalex.org/I181401687","display_name":"American University","ror":"https://ror.org/052w4zt36","country_code":"US","type":"education","lineage":["https://openalex.org/I181401687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bei Xiao","raw_affiliation_strings":["American University,Department of Computer Science,Washington DC,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"American University,Department of Computer Science,Washington DC,USA","institution_ids":["https://openalex.org/I181401687"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3667","last_page":"3672"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.945900022983551,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9341999888420105,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6237007975578308},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4885912537574768},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4625517725944519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4090654253959656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6237007975578308},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4885912537574768},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4625517725944519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4090654253959656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822746","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822746","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1997362383","https://openalex.org/W2083258699","https://openalex.org/W2162730913","https://openalex.org/W2461620095","https://openalex.org/W2592585722","https://openalex.org/W2804165413","https://openalex.org/W2910268846","https://openalex.org/W3000340225","https://openalex.org/W3098630015","https://openalex.org/W3184476827","https://openalex.org/W4210389911","https://openalex.org/W4294763143","https://openalex.org/W4313545873","https://openalex.org/W4319986513","https://openalex.org/W4385072800","https://openalex.org/W4385373826","https://openalex.org/W4385574097","https://openalex.org/W4387848740","https://openalex.org/W4390789641","https://openalex.org/W6771242713","https://openalex.org/W6776048684","https://openalex.org/W6842553014","https://openalex.org/W6858025956","https://openalex.org/W6862222442"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"New":[0],"medical":[1],"treatment":[2],"development":[3],"requires":[4],"multiple":[5],"phases":[6,115],"of":[7,16,138],"clinical":[8,87,143],"trials.":[9],"Recent":[10],"literature":[11],"indicates":[12],"that":[13],"the":[14,17,45,58,70,93,124,136],"design":[15,34],"trial":[18,23,33,38,88,110,144,148],"protocols":[19],"significantly":[20],"contributes":[21],"to":[22,36,129],"performance.":[24],"We":[25,42,55],"investigated":[26],"Clinical":[27],"Trial":[28],"Outcome":[29],"Prediction":[30],"(CTOP)":[31],"using":[32],"documents":[35],"predict":[37],"phase":[39,89,111],"transitions":[40,112],"automatically.":[41],"propose":[43],"CTP-LLM,":[44],"first":[46],"Large":[47],"Language":[48],"Model":[49],"(LLM)":[50],"based":[51,65],"model":[52,84],"for":[53,78],"CTOP.":[54],"also":[56],"introduce":[57],"PhaseTransition":[59],"(PT)":[60],"Dataset;":[61],"which":[62],"labels":[63],"trials":[64],"on":[66],"their":[67],"progression":[68],"through":[69],"regulatory":[71],"process":[72],"and":[73,116,146],"serves":[74],"as":[75],"a":[76,104,117],"benchmark":[77],"CTOP":[79],"evaluation.":[80],"Our":[81,132],"fine-tuned":[82],"GPT-3.5-based":[83],"(CTP-LLM)":[85],"predicts":[86],"transition":[90,125],"by":[91],"analyzing":[92],"trial\u2019s":[94],"original":[95],"protocol":[96],"texts":[97],"without":[98],"requiring":[99],"human-selected":[100],"features.":[101],"CTP-LLM":[102],"achieves":[103],"67%":[105],"accuracy":[106,119],"rate":[107,120],"in":[108,122,141],"predicting":[109,123],"across":[113],"all":[114],"75%":[118],"specifically":[121],"from":[126],"Phase":[127],"III":[128],"final":[130],"approval.":[131],"experimental":[133],"performance":[134],"highlights":[135],"potential":[137],"LLM-powered":[139],"applications":[140],"forecasting":[142],"outcomes":[145],"assessing":[147],"design.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
