{"id":"https://openalex.org/W2963413693","doi":"https://doi.org/10.1016/j.csda.2018.10.013","title":"Bayesian prediction for physical models with application to the optimization of the synthesis of pharmaceutical products using chemical kinetics","display_name":"Bayesian prediction for physical models with application to the optimization of the synthesis of pharmaceutical products using chemical kinetics","publication_year":2018,"publication_date":"2018-11-02","ids":{"openalex":"https://openalex.org/W2963413693","doi":"https://doi.org/10.1016/j.csda.2018.10.013","mag":"2963413693"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.csda.2018.10.013","pdf_url":null,"source":{"id":"https://openalex.org/S132362803","display_name":"Computational Statistics & Data Analysis","issn_l":"0167-9473","issn":["0167-9473","1872-7352"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.csda.2018.10.013","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085965516","display_name":"Antony M. Overstall","orcid":"https://orcid.org/0000-0003-0638-8635"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"funder","lineage":["https://openalex.org/I43439940"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Antony M. Overstall","raw_affiliation_strings":["University of Southampton, Southampton SO17 1BJ, UK"],"affiliations":[{"raw_affiliation_string":"University of Southampton, Southampton SO17 1BJ, UK","institution_ids":["https://openalex.org/I43439940"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001047279","display_name":"David C. Woods","orcid":"https://orcid.org/0000-0001-7648-429X"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"funder","lineage":["https://openalex.org/I43439940"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"David C. Woods","raw_affiliation_strings":["University of Southampton, Southampton SO17 1BJ, UK"],"affiliations":[{"raw_affiliation_string":"University of Southampton, Southampton SO17 1BJ, UK","institution_ids":["https://openalex.org/I43439940"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003476223","display_name":"Kieran Martin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113058","display_name":"Roche (United Kingdom)","ror":"https://ror.org/024tgbv41","country_code":"GB","type":"company","lineage":["https://openalex.org/I118019719","https://openalex.org/I4210113058"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kieran J. Martin","raw_affiliation_strings":["Roche, Welwyn Garden City AL7 1TW, UK"],"affiliations":[{"raw_affiliation_string":"Roche, Welwyn Garden City AL7 1TW, UK","institution_ids":["https://openalex.org/I4210113058"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085965516"],"corresponding_institution_ids":["https://openalex.org/I43439940"],"apc_list":{"value":3340,"currency":"USD","value_usd":3340},"apc_paid":{"value":3340,"currency":"USD","value_usd":3340},"fwci":2.117,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":17,"citation_normalized_percentile":{"value":0.849501,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":90},"biblio":{"volume":"132","issue":null,"first_page":"126","last_page":"142"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9934,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9934,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9905,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9861,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/approximate-bayesian-computation","display_name":"Approximate Bayesian Computation","score":0.42086154}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6183088},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.5997074},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5740021},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.51228917},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.50846756},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47349152},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.46942478},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.46649146},{"id":"https://openalex.org/C124223222","wikidata":"https://www.wikidata.org/wiki/Q2281940","display_name":"Chemical process","level":2,"score":0.46109736},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.43131799},{"id":"https://openalex.org/C2779377595","wikidata":"https://www.wikidata.org/wiki/Q21045424","display_name":"Approximate Bayesian computation","level":3,"score":0.42086154},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40833277},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24616614},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21622801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16352159},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.11944261},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.csda.2018.10.013","pdf_url":null,"source":{"id":"https://openalex.org/S132362803","display_name":"Computational Statistics & Data Analysis","issn_l":"0167-9473","issn":["0167-9473","1872-7352"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":true,"landing_page_url":"https://eprints.soton.ac.uk/425529/2/1_s2.0_S016794731830272X_main.pdf","pdf_url":"https://eprints.soton.ac.uk/425529/2/1_s2.0_S016794731830272X_main.pdf","source":{"id":"https://openalex.org/S4306401019","display_name":"ePrints Soton (University of Southampton)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I43439940","host_organization_name":"University of Southampton","host_organization_lineage":["https://openalex.org/I43439940"],"host_organization_lineage_names":["University of Southampton"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false},{"is_oa":true,"landing_page_url":"https://eprints.soton.ac.uk/425529/1/chemkin6.pdf","pdf_url":"https://eprints.soton.ac.uk/425529/1/chemkin6.pdf","source":{"id":"https://openalex.org/S4306401019","display_name":"ePrints Soton (University of Southampton)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I43439940","host_organization_name":"University of Southampton","host_organization_lineage":["https://openalex.org/I43439940"],"host_organization_lineage_names":["University of Southampton"],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1602.01347","pdf_url":"http://arxiv.org/pdf/1602.01347","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.csda.2018.10.013","pdf_url":null,"source":{"id":"https://openalex.org/S132362803","display_name":"Computational Statistics & Data Analysis","issn_l":"0167-9473","issn":["0167-9473","1872-7352"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.45}],"grants":[{"funder":"https://openalex.org/F4320307773","funder_display_name":"GlaxoSmithKline","award_id":null},{"funder":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council","award_id":"EP/J018317/1"}],"datasets":[],"versions":[],"referenced_works_count":29,"referenced_works":["https://openalex.org/W128608554","https://openalex.org/W1545319692","https://openalex.org/W156495478","https://openalex.org/W1607751291","https://openalex.org/W180233418","https://openalex.org/W1916201103","https://openalex.org/W1968512837","https://openalex.org/W1973333099","https://openalex.org/W1991520918","https://openalex.org/W1999698136","https://openalex.org/W1999914758","https://openalex.org/W2013478520","https://openalex.org/W2018044188","https://openalex.org/W2023285629","https://openalex.org/W2040932457","https://openalex.org/W2041215343","https://openalex.org/W2045656233","https://openalex.org/W2047102900","https://openalex.org/W2052953969","https://openalex.org/W2053934160","https://openalex.org/W2098720801","https://openalex.org/W2112949105","https://openalex.org/W2131668296","https://openalex.org/W2136829296","https://openalex.org/W2257111000","https://openalex.org/W2770524864","https://openalex.org/W4249753629","https://openalex.org/W55534668","https://openalex.org/W560187378"],"related_works":["https://openalex.org/W4306376789","https://openalex.org/W4299855329","https://openalex.org/W4241947739","https://openalex.org/W3080378789","https://openalex.org/W3047807024","https://openalex.org/W2788616582","https://openalex.org/W24509564","https://openalex.org/W2249958945","https://openalex.org/W2141452888","https://openalex.org/W137308628"],"abstract_inverted_index":{"Quality":[0],"control":[1],"in":[2,15,62,70],"industrial":[3],"processes":[4],"is":[5,27,60,81,101,142,154,198,221],"increasingly":[6],"making":[7],"use":[8],"of":[9,42,52,54,65,77,93,121,135,139,159,164,171,194,196,207,233],"prior":[10],"scientific":[11],"knowledge,":[12],"often":[13],"encoded":[14],"physical":[16],"models":[17,45,80],"that":[18,167],"require":[19],"numerical":[20,40],"approximation.":[21],"Statistical":[22],"prediction,":[23],"and":[24,73,104,147,162,192,237,239],"subsequent":[25],"optimization,":[26],"key":[28],"to":[29,49,83,111,125,155,204],"ensuring":[30,178],"the":[31,39,44,50,55,63,66,90,157,169,190,202,224,228,234],"process":[32,56,95,110,130,160],"output":[33],"meets":[34],"a":[35,85,94,107,113,133,143,184,205,217],"specification":[36],"target.":[37],"However,":[38],"expense":[41],"approximating":[43],"poses":[46],"computational":[47,79],"challenges":[48],"identification":[51],"combinations":[53,158],"factors":[57,191],"where":[58],"there":[59],"confidence":[61],"quality":[64],"response.":[67],"Recent":[68],"work":[69],"Bayesian":[71],"computation":[72],"statistical":[74],"approximation":[75],"(emulation)":[76],"expensive":[78],"exploited":[82],"develop":[84],"novel":[86],"strategy":[87],"for":[88],"optimizing":[89],"posterior":[91,230],"probability":[92,170],"meeting":[96],"specification.":[97],"The":[98,152,187],"ensuing":[99],"methodology":[100,225],"motivated":[102],"by,":[103],"demonstrated":[105],"on,":[106],"chemical":[108,126],"synthesis":[109],"manufacture":[112],"pharmaceutical":[114,145,175,235],"product,":[115],"within":[116],"which":[117],"an":[118],"initial":[119,165],"set":[120],"substances":[122,141,166,195],"evolve":[123],"according":[124],"reactions,":[127],"under":[128],"certain":[129],"conditions,":[131],"into":[132],"series":[134],"new":[136],"substances.":[137],"One":[138],"these":[140],"target":[144,174,236],"product":[146,176],"two":[148],"are":[149],"unwanted":[150,179],"by-products.":[151],"aim":[153],"determine":[156],"conditions":[161],"amounts":[163,193],"maximize":[168],"obtaining":[172],"sufficient":[173],"whilst":[177],"by-products":[180],"do":[181],"not":[182],"exceed":[183],"given":[185],"level.":[186],"relationship":[188],"between":[189],"interest":[197],"theoretically":[199],"described":[200],"by":[201],"solution":[203],"system":[206],"ordinary":[208],"differential":[209],"equations":[210],"incorporating":[211],"temperature":[212],"dependence.":[213],"Using":[214],"data":[215],"from":[216],"small":[218],"experiment,":[219],"it":[220],"shown":[222],"how":[223],"can":[226],"approximate":[227],"multivariate":[229],"predictive":[231],"distribution":[232],"by-products,":[238],"therefore":[240],"identify":[241],"suitable":[242],"operating":[243],"values.1":[244]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2963413693","counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4}],"updated_date":"2025-04-04T09:27:01.504370","created_date":"2019-07-30"}