{"id":"https://openalex.org/W4417515086","doi":"https://doi.org/10.48550/arxiv.2505.06949","title":"Causal knowledge graph analysis identifies adverse drug effects","display_name":"Causal knowledge graph analysis identifies adverse drug effects","publication_year":2025,"publication_date":"2025-05-11","ids":{"openalex":"https://openalex.org/W4417515086","doi":"https://doi.org/10.48550/arxiv.2505.06949"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2505.06949","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.06949","pdf_url":"https://arxiv.org/pdf/2505.06949","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2505.06949","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057787498","display_name":"Sumyyah Toonsi","orcid":"https://orcid.org/0000-0003-4746-4649"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Toonsi, Sumyyah","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059588755","display_name":"Paul N. Schofield","orcid":"https://orcid.org/0000-0002-5111-7263"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schofield, Paul","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5043808311","display_name":"Robert Hoehndorf","orcid":"https://orcid.org/0000-0001-8149-5890"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hoehndorf, Robert","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057787498"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.25699999928474426,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.25699999928474426,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.22349999845027924,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.11810000240802765,"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/causality","display_name":"Causality (physics)","score":0.5367000102996826},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.5307000279426575},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5008000135421753},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.4957999885082245},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4334000051021576},{"id":"https://openalex.org/keywords/knowledge-representation-and-reasoning","display_name":"Knowledge representation and reasoning","score":0.4228000044822693},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3431999981403351},{"id":"https://openalex.org/keywords/causal-structure","display_name":"Causal structure","score":0.33799999952316284},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.3264999985694885},{"id":"https://openalex.org/keywords/pharmacovigilance","display_name":"Pharmacovigilance","score":0.31529998779296875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5856999754905701},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.5367000102996826},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.5307000279426575},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5008000135421753},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.4957999885082245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4368000030517578},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4334000051021576},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4302999973297119},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.4228000044822693},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34360000491142273},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C163504300","wikidata":"https://www.wikidata.org/wiki/Q2364925","display_name":"Causal structure","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C57658597","wikidata":"https://www.wikidata.org/wiki/Q1550789","display_name":"Pharmacovigilance","level":3,"score":0.31529998779296875},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C97364631","wikidata":"https://www.wikidata.org/wiki/Q484284","display_name":"Deductive reasoning","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C116567970","wikidata":"https://www.wikidata.org/wiki/Q864217","display_name":"Biobank","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.2922999858856201},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.28690001368522644},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28119999170303345},{"id":"https://openalex.org/C179420905","wikidata":"https://www.wikidata.org/wiki/Q223871","display_name":"Mediation","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.2727999985218048},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.26579999923706055},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2630999982357025},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25870001316070557},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2505.06949","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.06949","pdf_url":"https://arxiv.org/pdf/2505.06949","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2505.06949","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2505.06949","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2505.06949","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.06949","pdf_url":"https://arxiv.org/pdf/2505.06949","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Knowledge":[0,72],"graphs":[1,23,47,59,78],"and":[2,14,30,48,100,108,125,139,150],"structural":[3],"causal":[4,16,38,81,90,98,226],"models":[5,39],"have":[6,49],"each":[7],"proven":[8],"valuable":[9],"for":[10,155,224],"organizing":[11],"biomedical":[12],"knowledge":[13,22,44,46,58,77],"estimating":[15],"effects,":[17],"but":[18],"remain":[19],"largely":[20],"disconnected:":[21],"encode":[24],"qualitative":[25],"relationships":[26],"focusing":[27],"on":[28],"facts":[29],"deductive":[31,54,85],"reasoning":[32,55],"without":[33],"formal":[34,80],"probabilistic":[35],"semantics,":[36,82],"while":[37,87,172],"lack":[40],"integration":[41],"with":[42,79,105,169,194],"background":[43,110],"in":[45],"no":[50],"access":[51],"to":[52,129,136],"the":[53,159,199,206],"capabilities":[56,86],"that":[57,188,216],"provide.":[60],"To":[61],"bridge":[62],"this":[63],"gap,":[64],"we":[65,142],"introduce":[66],"a":[67,114,220],"novel":[68,211],"formulation":[69,103],"of":[70,201,209],"Causal":[71],"Graphs":[73],"(CKGs)":[74],"which":[75],"extend":[76],"preserving":[83],"their":[84],"enabling":[88],"principled":[89],"inference.":[91,227],"CKGs":[92],"support":[93],"deconfounding":[94],"via":[95],"explicitly":[96],"marked":[97],"edges":[99],"facilitate":[101],"hypothesis":[102],"aligned":[104],"both":[106],"encoded":[107],"entailed":[109],"knowledge.":[111],"We":[112],"constructed":[113],"Drug-Disease":[115],"CKG":[116],"(DD-CKG)":[117],"integrating":[118],"disease":[119,127,152],"progression":[120],"pathways,":[121],"drug":[122,167,192,203],"indications,":[123,204],"side-effects,":[124],"hierarchical":[126],"classification":[128],"enable":[130],"automated":[131],"large-scale":[132],"mediation":[133],"analysis.":[134],"Applied":[135],"UK":[137],"Biobank":[138],"MIMIC-IV":[140],"cohorts,":[141],"tested":[143],"whether":[144],"drugs":[145],"mediate":[146],"effects":[147,193],"between":[148],"indications":[149],"downstream":[151],"progression,":[153],"adjusting":[154],"confounders":[156],"inferred":[157],"from":[158],"DD-CKG.":[160],"Our":[161],"approach":[162],"successfully":[163],"reproduced":[164],"known":[165],"adverse":[166,178],"reactions":[168],"high":[170],"precision":[171],"identifying":[173],"previously":[174],"undocumented":[175],"significant":[176],"candidate":[177],"effects.":[179],"Further":[180],"validation":[181],"through":[182],"side":[183],"effect":[184],"similarity":[185],"analysis":[186],"demonstrated":[187],"combining":[189],"our":[190,210,217],"predicted":[191],"established":[195],"databases":[196],"significantly":[197],"improves":[198],"prediction":[200],"shared":[202],"supporting":[205],"clinical":[207],"relevance":[208],"findings.":[212],"These":[213],"results":[214],"demonstrate":[215],"methodology":[218],"provides":[219],"generalizable,":[221],"knowledge-driven":[222],"framework":[223],"scalable":[225]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
