{"id":"https://openalex.org/W7166862850","doi":"https://doi.org/10.48550/arxiv.2606.31085","title":"DDIAgents: Mechanism-Conditioned Context Flow for Drug-Drug Interaction Prediction","display_name":"DDIAgents: Mechanism-Conditioned Context Flow for Drug-Drug Interaction Prediction","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7166862850","doi":"https://doi.org/10.48550/arxiv.2606.31085"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.31085","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31085","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.31085","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104385986","display_name":"Zhenqian Shen","orcid":"https://orcid.org/0000-0003-4921-7000"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Zhenqian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139788905","display_name":"Yu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042116026","display_name":"Xiaoyi Fu","orcid":"https://orcid.org/0000-0002-5194-391X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Xiaoyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139767876","display_name":"Quanming Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Quanming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T10028","display_name":"Topic Modeling","score":0.28299999237060547,"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/T10028","display_name":"Topic Modeling","score":0.28299999237060547,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.19859999418258667,"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/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.06199999898672104,"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/relevance","display_name":"Relevance (law)","score":0.6983000040054321},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6722000241279602},{"id":"https://openalex.org/keywords/planner","display_name":"Planner","score":0.45419999957084656},{"id":"https://openalex.org/keywords/expert-system","display_name":"Expert system","score":0.4235000014305115},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.37700000405311584}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7569000124931335},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6983000040054321},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6722000241279602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.527999997138977},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49559998512268066},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.45419999957084656},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.4235000014305115},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33149999380111694},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.26429998874664307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.31085","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31085","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.31085","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31085","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Drug-drug":[0],"interaction":[1,21,71],"(DDI)":[2],"prediction":[3,33,91,106],"is":[4],"essential":[5],"for":[6,118],"medication":[7],"safety,":[8],"yet":[9],"it":[10],"requires":[11],"reasoning":[12],"over":[13],"heterogeneous":[14,115],"biomedical":[15],"evidence":[16],"whose":[17],"relevance":[18],"changes":[19],"across":[20],"mechanisms.":[22],"We":[23],"propose":[24],"DDIAgents,":[25],"a":[26,39,42,61],"mechanism-conditioned":[27],"multi-agent":[28,111],"framework":[29],"that":[30,94],"performs":[31],"DDI":[32,90],"through":[34,60],"dynamic":[35],"knowledge":[36,51,117],"orchestration.":[37],"Given":[38],"drug":[40],"pair,":[41],"planner":[43],"agent":[44],"instantiates":[45],"specialized":[46],"expert":[47,79],"agents,":[48],"routes":[49],"mechanism-relevant":[50],"sources":[52],"to":[53,68],"each":[54],"agent,":[55],"and":[56,81,102,120],"aggregates":[57],"their":[58],"analyses":[59],"conclusion":[62],"agent.":[63],"By":[64],"adapting":[65],"context":[66],"flow":[67],"the":[69],"inferred":[70],"mechanism,":[72],"DDIAgents":[73,95,108],"reduces":[74],"irrelevant":[75],"information,":[76],"supports":[77],"complementary":[78],"reasoning,":[80],"produces":[82],"interpretable":[83,121],"agent-level":[84],"rationales.":[85],"Extensive":[86],"experiments":[87],"on":[88],"realistic":[89],"benchmarks":[92],"show":[93],"consistently":[96],"outperforms":[97],"existing":[98],"feature-based,":[99],"graph-based,":[100],"LLM-based,":[101],"agent-based":[103],"baselines.":[104],"Beyond":[105],"performance,":[107],"demonstrates":[109],"how":[110],"systems":[112],"can":[113],"organize":[114],"scientific":[116],"adaptive":[119],"AI4Science":[122],"reasoning.":[123]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-02T00:00:00"}