{"id":"https://openalex.org/W3138148502","doi":"https://doi.org/10.1145/3448748.3448768","title":"Comparison of Pharmacokinetic Effects of Ibuprofen Based on Three Statistical Methods","display_name":"Comparison of Pharmacokinetic Effects of Ibuprofen Based on Three Statistical Methods","publication_year":2021,"publication_date":"2021-01-22","ids":{"openalex":"https://openalex.org/W3138148502","doi":"https://doi.org/10.1145/3448748.3448768","mag":"3138148502"},"language":"en","primary_location":{"id":"doi:10.1145/3448748.3448768","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448748.3448768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","raw_type":"proceedings-article"},"type":"article","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/A5017623678","display_name":"Wanqing Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wanqing Peng","raw_affiliation_strings":["College of Mathematics, Sichuan University, Chengdu, Sichuan"],"affiliations":[{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, Sichuan","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100629476","display_name":"Haoxuan Li","orcid":"https://orcid.org/0009-0007-1429-2082"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoxuan Li","raw_affiliation_strings":["College of Mathematics, Sichuan University, Chengdu, Sichuan"],"affiliations":[{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, Sichuan","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017623678"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02438238,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"122","last_page":"127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10908","display_name":"Analytical Chemistry and Chromatography","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10908","display_name":"Analytical Chemistry and Chromatography","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11460","display_name":"Analytical Methods in Pharmaceuticals","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10678","display_name":"Inflammatory mediators and NSAID effects","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2736","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ibuprofen","display_name":"Ibuprofen","score":0.5366520285606384},{"id":"https://openalex.org/keywords/pharmacokinetics","display_name":"Pharmacokinetics","score":0.5347579717636108},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5080695152282715},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.46008017659187317},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4599553346633911},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.4547012746334076},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.43923357129096985},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4342288672924042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.36179494857788086},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2720513641834259},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.22756269574165344}],"concepts":[{"id":"https://openalex.org/C2779944601","wikidata":"https://www.wikidata.org/wiki/Q186969","display_name":"Ibuprofen","level":2,"score":0.5366520285606384},{"id":"https://openalex.org/C112705442","wikidata":"https://www.wikidata.org/wiki/Q323936","display_name":"Pharmacokinetics","level":2,"score":0.5347579717636108},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5080695152282715},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.46008017659187317},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4599553346633911},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.4547012746334076},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.43923357129096985},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4342288672924042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36179494857788086},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2720513641834259},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.22756269574165344}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3448748.3448768","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3448748.3448768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1858095914","https://openalex.org/W2005069607","https://openalex.org/W2058213101","https://openalex.org/W2082204699","https://openalex.org/W2142189325","https://openalex.org/W2142313532","https://openalex.org/W2163206365","https://openalex.org/W2164977460","https://openalex.org/W2255309678","https://openalex.org/W2773902187","https://openalex.org/W2804950423","https://openalex.org/W2943583439","https://openalex.org/W2982092991","https://openalex.org/W4234814574","https://openalex.org/W4242828376"],"related_works":["https://openalex.org/W2381401049","https://openalex.org/W1964364835","https://openalex.org/W2989151164","https://openalex.org/W2382874710","https://openalex.org/W3150770635","https://openalex.org/W2043479546","https://openalex.org/W132599052","https://openalex.org/W2347260871","https://openalex.org/W2024078538","https://openalex.org/W2117545158"],"abstract_inverted_index":{"Ibuprofen":[0],"is":[1,94,105,119],"an":[2],"antipyretic":[3],"and":[4,36,60,79,90,114,117],"analgesic":[5],"anti-inflammatory":[6],"drug.":[7],"In":[8],"order":[9],"to":[10,31,69,111,133],"study":[11],"the":[12,33,71,74,122,130],"pharmacokinetic":[13,26],"characteristics":[14,38],"of":[15,39,41,73,83,88,100,102,124],"Chinese":[16],"healthy":[17,43],"adults":[18],"after":[19,45],"ibuprofen":[20,40],"injection,":[21],"this":[22],"article":[23],"establishes":[24],"a":[25,46],"nonlinear":[27],"mixed":[28],"effect":[29],"model":[30],"analyze":[32,78],"blood":[34],"concentration":[35],"clinical":[37],"12":[42],"volunteers":[44],"single":[47],"dose.":[48],"Three":[49],"statistical":[50],"methods,":[51],"FO":[52,118],"(First-order),":[53],"FOCE-I":[54,104],"(First-order":[55],"conditional":[56],"estimation":[57,98,108],"with":[58,136],"interaction),":[59],"BAYES":[61,93],"(Markov":[62],"chain":[63],"Monte":[64],"Carlo":[65],"Bayesian)":[66],"are":[67],"used":[68],"estimate":[70],"parameters":[72],"population":[75],"pharmacokinetics,":[76],"then":[77],"compare":[80],"in":[81,128],"terms":[82],"relative":[84],"standard":[85],"error,":[86],"goodness":[87,101],"fit":[89],"convergence":[91,138],"speed.":[92,139],"suitable":[95,106,120],"for":[96,107,121],"higher":[97,137],"requirements":[99],"fit,":[103],"that":[109],"needs":[110,132],"consider":[112],"residuals":[113],"inter-individual":[115],"variation,":[116],"evaluation":[123],"massive":[125],"medical":[126],"data,":[127],"which":[129],"estimands":[131],"be":[134],"obtained":[135]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
