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Appendix A Pharma Mod. UNIFAC - Técnico Lisboa PDF

142 Pages·2013·3.07 MB·English
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Preview Appendix A Pharma Mod. UNIFAC - Técnico Lisboa

Implementation and evaluation of two models for solubility of active pharmaceutical ingredients (APIs) Application on solvent selection in process design Sara Antunes Febra Thesis to obtain the Master of Science Degree in Chemical Engineering Examination Committee Chairperson: Prof. Dr. João Manuel Nunes Alvarinhas Fareleira Supervisors: Prof. Dr. Benilde de Jesus Vieira Saramago Dr.-Ing. Thoralf Hartwig Members of the Committee: Prof. Dr. Edmundo José Simões Gomes de Azevedo November 2013 Tomyfamily. Foryourunconditionallove. Acknowledgments I would like to thank many people who have helped me throughout the completion of this dissertation. In first place, a very special thanks to Franc¸ois Ricard and Luisa Freitas dos Santos for welcoming me into GSK, since without their approval it would not have been possible to carry out this thesis. I would like to express my sincere gratitude to my supervisor Dr.-Ing. Thoralf Hartwig, the true embodiment of a mentor. I appreciate his vast knowledge and skill, but especially the inspiring nature that helped me to figure out what I wanted out of my career. Moreover, his encouragement made me feel supported and capable of succeeding all times. One simply could not wish for a better supervisor both at the professional and the personal level. I also feel very grateful for all the effort and availability my IST supervisor Prof. Dr. Benilde Saramago put into reading and improving my written thesis. It was a privilege to have her as my supervisor. On the GSK side, it was an absolute fantastic experience to meet such great scientists and engineers and to have the opportunity to work closely with some of them,namelyNoraPataut,IzabelaPhillips,RobWillacy,HughClark,PeteSzeto,JeremyProdger,Ugo Cocchini,IgorPereira,FranckMallet,MaheshSanganeeandJanFiedler. OnthePSEside,Iwouldlike tothankSeanBerminghamtohavefacilitatedthecollaborationofPSEthatwascrucialforanimportant section of the work. I would like to show my appreciation for the contact that Mark Pinto made to find meaninternshipinGSK,Icannotthankhimenough. CompletingthegPROMSpartoftheworkwould havebeenmuchmoredifficultwithoutthesupportandfriendshipofFrancesPereira. OntheAspenTech side, I want to thank Russel Schofield for being so helpful and collaborative, as well as AspenTech support. On the DDBST side, I thank Wilfried Cordes for reviewing the PMUNIFAC code, as well as Prof. Ju¨rgen Gmehling and Dr. Dana Constantinescu for giving me theopportunity to present my work attheUNIFACConsortiummeetingof2013. IappreciateallthehelpDr. AnjaDiedrichsgavemeinthe understandingofthefundamentalsofthemodelPharmaMod. UNIFAC.Iwouldalsoliketoacknowledge theopportunityProf. Dr. EdmundoAzevedoprovidedme,byallowingmetospendsometimeinhislab with researchers, so I could get up to speed with the solubility reality before beginning my internship. I wanttothankmyboyfriendE´lton,whoexperiencedalltheupsanddownsofmywork,forhislove. Any challengeisjusteasiertoovercomeandthehappinessfrommyachievementsisexpandedwhenheis around. Last but not least, I would like to thank my parents for their unconditional support at all levels throughoutmydegree. Inparticular,theirpatienceandunderstanding. v Resumo A selec¸a˜o do solvente o´timo e, eventualmente, o desenho do processo o´timo, sera´ apenas poss´ıvel a partir da previsa˜o de solubilidade. O modelo Pharma. mod. UNIFAC (PMUNIFAC)[1], criado espe- cialmente para o efeito, surgiu como um potencial candidato na aplicac¸a˜o em soluc¸o˜es orgaˆnicas de princ´ıpios ativos. Ao contra´rio de NRTL-SAC[2,3] (modelo emp´ırico que se tem mostrado superior a outrosmodelosdesolubilidade),estetemavantagemdeserummodelopreditivo,na˜oexigindodados experimentaisporpartedoutilizador,masapenasestruturamolecular,temperaturaeentalpiadefusa˜o. Na primeira parte deste trabalho, a implementac¸a˜o dos modelos NRTL-SAC e PMUNIFAC foi efetu- ada com sucesso nos softwares gPROMS ModelBuilder e Excel/Visual Basic for Applications (VBA), ferramentas que ficaram acess´ıveis na GlaxoSmithKline (GSK). De seguida, os dois modelos foram avaliados com base na solubilidade experimental de oito mole´culas da GSK. Apenas o NRTL-SAC mostrou previso˜es precisas (ordem de magnitude de discrepaˆncia (OMD) = 0.27 e OMD ma´xima = 1.63), ja´ o modelo PMUNIFAC, mostrou-se aque´m das expetativas, exceto quando se consideraram apenasossistemasquetinhamtodososparaˆmetrosdispon´ıveis(OMDme´dia=0.40eOMDma´xima= 2.05). FoiconclusivoqueomodeloPMUNIFACaindatemmuitosparaˆmetrosemfaltaparaterutilidade em procedimentos de selec¸a˜o de solventes, mas os resultados observados encorajam a continuac¸a˜o do desenvolvimento do modelo. Por u´ltimo, o modelo NRTL-SAC foi aplicado na selec¸a˜o de solventes em dois casos de cristalizac¸a˜o da GSK onde foram identificadas e validadas alternativas, contribuindo positivamenteparaodesenvolvimentodosprocedimentosdeselec¸a˜odesolventesdaempresa. Palavras-chave: Solubilidade;Modelac¸a˜otermodinaˆmica;NRTL-SAC;Pharma. Mod. UNIFAC; Selec¸a˜odesolventes;Equil´ıbroso´lido-l´ıquido. vii Abstract Havinganoptimalsolventselection,andultimatelydesigningtheoptimalprocess,canonlybeachieved withasuitablesolubilitymodel. TheempiricalNRTL-SACmodel[2,3] hasproventobesuperiortoother solubility models. Pharma mod. UNIFAC (PMUNIFAC)[1], specially designed for application in API or- ganic solutions, has arisen as a powerful candidate for the application. Unlike NRTL-SAC, it has the advantage of being a predictive model, i.e., does not require experimental data, but only molecular structure,meltingtemperatureandmeltingenthalpyasuserinput. In the first stage of this study, the implementations of NRTL-SAC and PMUNIFAC were accomplished withsuccessinthesoftwaresgPROMSModelBuilderandExcel/VisualBasicforApplications(VBA)and becameavailableastoolsinternallyinGlaxoSmithKline(GSK).Inthesecondstage,thetwomodelswere evaluatedagainstexperimentaldatafrom8GSKAPIs. OnlyNRTL-SACprovedtobefitforpurpose(av- erage orderof magnitude of discrepancy(OMD) = 0.27and maximum OMD =1.63), since PMUNIFAC predictionswerepooruntilonlysystemswithallparametersavailablebeingconsidered,whichresulted in an average OMD = 0.40 and a maximum OMD = 2.05. It was conclusive that PMUNIFAC still has too many missing parameters to be applied in solubility modelling, but its results were encouraging to support its further development. In the last stage of the study, NRTL-SAC was successfully applied in the solvent selection of two GSK crystallisation cases. Alternative solvent systems were identified and validated,addingvaluetothesolventselectionprocedureofthecompany. Keywords: Solubility;Molecularmodelling;NRTL-SAC;Pharma. Mod. UNIFAC;Solventselection; Solid-liquidequilibria. ix

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3.1 Solvent Selection Tool Database - General Information . the prediction of activity coefficients for SLE, followed by UNIFAC and COSMO-RS. A Ph.D.
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