{"id":"https://openalex.org/W4386413533","doi":"https://doi.org/10.1088/2632-2153/acf6aa","title":"Hierarchical Bayesian pharmacometrics analysis of Baclofen for alcohol use disorder","display_name":"Hierarchical Bayesian pharmacometrics analysis of Baclofen for alcohol use disorder","publication_year":2023,"publication_date":"2023-09-01","ids":{"openalex":"https://openalex.org/W4386413533","doi":"https://doi.org/10.1088/2632-2153/acf6aa"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/acf6aa","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/acf6aa","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acf6aa/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acf6aa/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013044301","display_name":"Nina Baldy","orcid":"https://orcid.org/0009-0000-2444-1837"},"institutions":[{"id":"https://openalex.org/I21491767","display_name":"Aix-Marseille Universit\u00e9","ror":"https://ror.org/035xkbk20","country_code":"FR","type":"education","lineage":["https://openalex.org/I21491767"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nina Baldy","raw_affiliation_strings":["INS, INSERM U1106, Aix Marseille Univ, Aix-Marseille Universit\u00e9 Facult\u00e9 de M\u00e9decine de la Timone 27, Boulevard Jean Moulin 13005 Marseille, Marseille, 13005, FRANCE"],"affiliations":[{"raw_affiliation_string":"INS, INSERM U1106, Aix Marseille Univ, Aix-Marseille Universit\u00e9 Facult\u00e9 de M\u00e9decine de la Timone 27, Boulevard Jean Moulin 13005 Marseille, Marseille, 13005, FRANCE","institution_ids":["https://openalex.org/I21491767"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063118702","display_name":"Nicolas Simon","orcid":"https://orcid.org/0000-0003-4393-2257"},"institutions":[{"id":"https://openalex.org/I154526488","display_name":"Inserm","ror":"https://ror.org/02vjkv261","country_code":"FR","type":"government","lineage":["https://openalex.org/I154526488"]},{"id":"https://openalex.org/I21491767","display_name":"Aix-Marseille Universit\u00e9","ror":"https://ror.org/035xkbk20","country_code":"FR","type":"education","lineage":["https://openalex.org/I21491767"]},{"id":"https://openalex.org/I4210159661","display_name":"Economic & Social Sciences, Health Systems & Medical Informatics","ror":"https://ror.org/0508wny29","country_code":"FR","type":"facility","lineage":["https://openalex.org/I154526488","https://openalex.org/I21491767","https://openalex.org/I2802818602","https://openalex.org/I4210090127","https://openalex.org/I4210111578","https://openalex.org/I4210131494","https://openalex.org/I4210159661","https://openalex.org/I4210166444"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nicolas Simon","raw_affiliation_strings":["SESSTIM, INSERM U912, Aix Marseille Univ, Aix-Marseille Universit\u00e9 Facult\u00e9 de M\u00e9decine de la Timone 27, Boulevard Jean Moulin 13005 Marseille, Marseille, 13005, FRANCE"],"affiliations":[{"raw_affiliation_string":"SESSTIM, INSERM U912, Aix Marseille Univ, Aix-Marseille Universit\u00e9 Facult\u00e9 de M\u00e9decine de la Timone 27, Boulevard Jean Moulin 13005 Marseille, Marseille, 13005, FRANCE","institution_ids":["https://openalex.org/I21491767","https://openalex.org/I4210159661","https://openalex.org/I154526488"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047727568","display_name":"Viktor Jirsa","orcid":"https://orcid.org/0000-0002-8251-8860"},"institutions":[{"id":"https://openalex.org/I21491767","display_name":"Aix-Marseille Universit\u00e9","ror":"https://ror.org/035xkbk20","country_code":"FR","type":"education","lineage":["https://openalex.org/I21491767"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Viktor K Jirsa","raw_affiliation_strings":["INS, INSERM U1106, Aix Marseille Univ, Facult\u00e9 de M\u00e9decine, Aix-Marseille Universit\u00e9 Facult\u00e9 de M\u00e9decine de la Timone 27, Boulevard Jean Moulin 13005 Marseille, Marseille, 13005, FRANCE"],"affiliations":[{"raw_affiliation_string":"INS, INSERM U1106, Aix Marseille Univ, Facult\u00e9 de M\u00e9decine, Aix-Marseille Universit\u00e9 Facult\u00e9 de M\u00e9decine de la Timone 27, Boulevard Jean Moulin 13005 Marseille, Marseille, 13005, FRANCE","institution_ids":["https://openalex.org/I21491767"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089498751","display_name":"Meysam Hashemi","orcid":"https://orcid.org/0000-0001-5289-9837"},"institutions":[{"id":"https://openalex.org/I21491767","display_name":"Aix-Marseille Universit\u00e9","ror":"https://ror.org/035xkbk20","country_code":"FR","type":"education","lineage":["https://openalex.org/I21491767"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Meysam Hashemi","raw_affiliation_strings":["Facult\u00e9 de M\u00e9decine, INS, INSERM U1106, Aix Marseille Univ, Aix-Marseille Universit\u00e9 Facult\u00e9 de M\u00e9decine de la Timone 27, Boulevard Jean Moulin 13005 Marseille, Marseille, 13005, FRANCE"],"affiliations":[{"raw_affiliation_string":"Facult\u00e9 de M\u00e9decine, INS, INSERM U1106, Aix Marseille Univ, Aix-Marseille Universit\u00e9 Facult\u00e9 de M\u00e9decine de la Timone 27, Boulevard Jean Moulin 13005 Marseille, Marseille, 13005, FRANCE","institution_ids":["https://openalex.org/I21491767"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089498751"],"corresponding_institution_ids":["https://openalex.org/I21491767"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":1.3845,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.79853134,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"4","issue":"3","first_page":"035048","last_page":"035048"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10056","display_name":"Neurotransmitter Receptor Influence on Behavior","score":0.9616000056266785,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10056","display_name":"Neurotransmitter Receptor Influence on Behavior","score":0.9616000056266785,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11207","display_name":"Alcohol Consumption and Health Effects","score":0.9473000168800354,"subfield":{"id":"https://openalex.org/subfields/2734","display_name":"Pathology and Forensic Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9442999958992004,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/algorithm","display_name":"Algorithm","score":0.6238014698028564},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.6029224395751953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48153549432754517},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4469001293182373},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4286983907222748},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.26472073793411255}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6238014698028564},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.6029224395751953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48153549432754517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4469001293182373},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4286983907222748},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.26472073793411255},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1088/2632-2153/acf6aa","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/acf6aa","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acf6aa/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},{"id":"pmh:oai:HAL:inserm-04544203v1","is_oa":true,"landing_page_url":"https://inserm.hal.science/inserm-04544203","pdf_url":"https://inserm.hal.science/inserm-04544203/document","source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EISSN: 2632-2153","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:51dfd62f57324b1fa20d56261a7e6bad","is_oa":true,"landing_page_url":"https://doaj.org/article/51dfd62f57324b1fa20d56261a7e6bad","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning: Science and Technology, Vol 4, Iss 3, p 035048 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/acf6aa","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/acf6aa","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acf6aa/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G6972315759","display_name":null,"funder_award_id":"DIC20161236442","funder_id":"https://openalex.org/F4320321589","funder_display_name":"Fondation pour la Recherche M\u00e9dicale"}],"funders":[{"id":"https://openalex.org/F4320321589","display_name":"Fondation pour la Recherche M\u00e9dicale","ror":"https://ror.org/04w6kn183"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386413533.pdf"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W1955155554","https://openalex.org/W1983324935","https://openalex.org/W2029670706","https://openalex.org/W2038628922","https://openalex.org/W2059448777","https://openalex.org/W2064117019","https://openalex.org/W2084045976","https://openalex.org/W2093243674","https://openalex.org/W2094615848","https://openalex.org/W2118064230","https://openalex.org/W2130902307","https://openalex.org/W2141636993","https://openalex.org/W2145176659","https://openalex.org/W2145434855","https://openalex.org/W2148534890","https://openalex.org/W2159325249","https://openalex.org/W2168340028","https://openalex.org/W2242847513","https://openalex.org/W2487166295","https://openalex.org/W2577537660","https://openalex.org/W2747622113","https://openalex.org/W2792275927","https://openalex.org/W2888349922","https://openalex.org/W2892829094","https://openalex.org/W2893060017","https://openalex.org/W2901943374","https://openalex.org/W2908415824","https://openalex.org/W2920804790","https://openalex.org/W2963977107","https://openalex.org/W2981323645","https://openalex.org/W2990711141","https://openalex.org/W3023066206","https://openalex.org/W3037905600","https://openalex.org/W3039848872","https://openalex.org/W3102763196","https://openalex.org/W3109761717","https://openalex.org/W3176085562","https://openalex.org/W3181378126","https://openalex.org/W3196930063","https://openalex.org/W3200049163","https://openalex.org/W3209597876","https://openalex.org/W4238048406","https://openalex.org/W4252930359","https://openalex.org/W4296001848","https://openalex.org/W4297730691","https://openalex.org/W4399649271","https://openalex.org/W6677822847","https://openalex.org/W6679529799","https://openalex.org/W6690788270","https://openalex.org/W6731701471","https://openalex.org/W6738588474","https://openalex.org/W6756537312","https://openalex.org/W6785642692","https://openalex.org/W6801000636","https://openalex.org/W6868998939","https://openalex.org/W7008929433"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4312192474","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Abstract":[0],"Alcohol":[1],"use":[2,90],"disorder":[3],"(AUD),":[4],"also":[5],"called":[6],"alcohol":[7],"dependence,":[8],"is":[9,84,120],"a":[10,30,57,78,91,100,207],"major":[11],"public":[12],"health":[13],"problem,":[14],"affecting":[15],"almost":[16],"<mml:math":[17,32],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[18,33],"overflow=\"scroll\">":[19,34],"<mml:mn>10</mml:mn>":[20],"<mml:mi":[21,37,39,41,43,47],"mathvariant=\"normal\">%</mml:mi>":[22],"</mml:math>":[23,51],"of":[24,63,80,99,209,238],"the":[25,61,66,97,117,132,138,184,201,220,227,236],"world\u2019s":[26],"population.":[27],"Baclofen,":[28],"as":[29,56,206],"selective":[31],"<mml:msub>":[35],"<mml:mrow>":[36,46],"mathvariant=\"normal\">G</mml:mi>":[38],"mathvariant=\"normal\">A</mml:mi>":[40,44],"mathvariant=\"normal\">B</mml:mi>":[42,48],"</mml:mrow>":[45,49],"</mml:msub>":[50],"receptor":[52],"agonist,":[53],"has":[54],"emerged":[55],"promising":[58],"drug":[59,73],"for":[60,216,247],"treatment":[62],"AUD.":[64,111,262],"However,":[65],"inter-trial,":[67],"inter-individual":[68],"and":[69,127,169,179,194,249,259],"residual":[70],"variability":[71],"in":[72,77,156,186,252],"concentration":[74,175],"over":[75],"time":[76],"population":[79,103],"patients":[81,109],"with":[82,110,148],"AUD":[83],"unknown.":[85],"In":[86],"this":[87],"study,":[88],"we":[89],"hierarchical":[92],"Bayesian":[93,158,222,240],"workflow":[94],"to":[95,108,130,255],"estimate":[96],"parameters":[98,135],"pharmacokinetic":[101],"(PK)":[102],"model":[104,134,217],"from":[105,145],"Baclofen":[106,173],"administration":[107],"By":[112],"monitoring":[113],"various":[114],"convergence":[115,192],"diagnostics,":[116,193],"probabilistic":[118],"methodology":[119],"first":[121],"validated":[122],"on":[123,137,172],"synthetic":[124],"longitudinal":[125],"datasets":[126],"then":[128],"applied":[129],"infer":[131],"PK":[133],"based":[136],"clinical":[139,253],"data":[140,229],"that":[141,153],"were":[142],"retrospectively":[143],"collected":[144],"outpatients":[146],"treated":[147],"oral":[149],"Baclofen.":[150],"We":[151],"show":[152],"state-of-the-art":[154],"advances":[155],"automatic":[157],"inference":[159],"using":[160,242],"self-tuning":[161],"Hamiltonian":[162],"Monte":[163],"Carlo":[164],"(HMC)":[165],"algorithms":[166],"provide":[167],"accurate":[168],"decisive":[170],"predictions":[171],"plasma":[174],"at":[176],"both":[177],"individual":[178],"group":[180],"levels.":[181],"Importantly,":[182],"leveraging":[183],"information":[185,223],"prior":[187],"provides":[188],"faster":[189],"computation,":[190],"better":[191],"substantially":[195],"higher":[196],"out-of-sample":[197],"prediction":[198],"accuracy.":[199],"Moreover,":[200],"root":[202],"mean":[203],"squared":[204],"error":[205],"measure":[208],"within-sample":[210],"predictive":[211],"accuracy":[212],"can":[213],"be":[214],"misleading":[215],"evaluation,":[218],"whereas":[219],"fully":[221],"criteria":[224],"correctly":[225],"select":[226],"true":[228],"generating":[230],"parameters.":[231],"This":[232],"study":[233],"points":[234],"out":[235],"capability":[237],"non-parametric":[239],"estimation":[241,251],"adaptive":[243],"HMC":[244],"sampling":[245],"methods":[246],"easy":[248],"reliable":[250],"settings":[254],"optimize":[256],"dosing":[257],"regimens":[258],"efficiently":[260],"treat":[261]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}