Vrednotenje kritičnih lastnosti pomožnih snovi in kritičnih procesnih parametrov pri razvoju pelet s pristopi vgrajene kakovosti

The preparation of pellets is a complex technological procedure, which requires a large number of experiments for a thorough evaluation. This doctoral thesis provides additional insights into all process steps involved in the preparation of pellets using a range of different approaches. The first chapter is devoted to the retrospective applications of multivariate data analysis (MVDA) and artificial neural networks (ANN), with the aim of identifying critical material attributes (CMAs) and critical process parameters (CPPs) for drug dissolution as the critical quality attribute (CQA) of pellets with a high content of active pharmaceutical ingredient (API). The development of MVDA and ANN model is presented, describing the variability between 49 industrially manufactured batches. Based on the generated models, CMAs and CPPs were successfully identified. The statistical techniques utilize a different approach to data modeling, ANN utilizes nonlinear correlations between factors and responses, whereas MVDA is based on linear correlations. Consequently, we identified other CMAs and CPPs with the ANN model, such as API particle size, which is in line with expectations, as the investigated formulation contains a BCS II class API. Despite the difference in approach to data evaluation, the complementary relationship of MVDA and ANN was elucidatedboth play an important role in facilitating a higher level of process understanding, creating opportunities for root cause investigation, and developing control strategies for pharmaceutical products. To the best of our knowledge, this is the first time that MVDA and ANN were used to process such a broad range of data for the evaluation and optimization of pellets, prepared by extrusion and spheronization on an industrial scale. The utilized Quality by design (QbD) approach governed by data modeling is easily transferable also to other pharmaceutical products. The second chapter presents the benefits of using visual analysis for an in-depth understanding of the processes involved in the example of QbD-guided development of pellets with high API content and three coatings. The benefits of PATVIS APA as one of the dynamic image analysis techniques are showcased: - obtaining target or desired pellet size in the process of extrusion and spheronization - at-line yield evaluation of the extrusion and spheronization process - monitoring the effectiveness of the coating process, detection of potential pellet agglomeration monitoring of coating thickness during the coating process with the option of end point determination. Utilization of dynamic image analysis facilitates real-time adaptation of process parameters, which is an added benefit, as it directly influences the quality of the product and efficiency of the process. The third chapter continues with the exploration of the coating process, with a focus on the spraying process, which influences the quality of the film coating. To increase the chance of success when scaling up from laboratory to production scale, the influence of dispersion properties (viscosity, surface tension, and density) and process parameters (dispersion flow rate, atomization air pressure, and microclimate air pressure) on the average droplet size and their distribution by formation with a three-channel nozzle was investigated. Based on a custom-built optical method concept, which enables the monitoring of the speed, direction, size, and distribution of sizes of droplets, two semi-empirical models were built to predict the average droplet size and their distribution. Based on the models constructed, comparable droplet sizes can be achieved on both scales by adjusting the process parameters. To our knowledge, these are the first model built for prediction of droplet size and their distribution, which include Newtonian and non-Newtonian dispersions and simultaneously include also variation of process parameters. The models constructed can be transferred to all coating processes utilizing the investigated three-channel nozzle. Moreover, the significant advantage of this work is, that the approach for construction of the model can be extended to all processes of droplet formation. Therefore, it can also be applied to spray drying, granulation, and coating of other pharmaceutical products. The most important contribution of this doctoral thesis are the insights into new and innovative approaches for the QbD development of pellets. What is more, the approaches presented can be transferred to other pharmaceutical products. As showcased, the use of DoE is more appropriate at the early stages of product development on a laboratory scale, where experiments can be planned in a systematic way (for example, the evaluation of droplet size). By contrast, the use of statistical techniques, such as MVDA and ANN is more appropriate for the evaluation of large data sets obtained on regular production batches during the lifecycle of the product and they can be used as excellent root cause investigation tools. Like the dynamic imaging method presented (PATVIS APA), it can be used as a powerful tool at both stages: during early development to aid process development and understanding as well as during the product lifecycle, as a potential process analytical tool (PAT) tool.Priprava pelet je zahteven tehnološki postopek, ki potrebuje veliko poskusov za dobro razumevanje vseh vplivov. V sklopu doktorske naloge smo z različnimi pristopi poskušali izboljšati razumevanje vseh procesnih korakov. V prvem poglavju smo z uporabo statističnih pristopov multivariatne analize (Multivariate data analysis – MVDA) in nevronskih mrež (Artificial neural network – ANN) napovedali kritične materialne atribute (Critical material attribute – CMA) in kritične procesne parametre (Critical process parameter – CPP), ki vplivajo na sproščanje učinkovine iz pelet z visoko vsebnostjo učinkovine. S pomočjo MVDA in ANN smo zgradili modela, ki opisujeta variabilnost iz 49 industrijsko proizvedenih serij. Na podlagi razvitih modelov smo uspešno identificirali CMA-je in CPP-je preiskovanega izdelka. Uporabljeni statistični tehniki imata različen pristop obdelave podatkov. ANN uporablja nelinearne korelacije med dejavniki in preiskovanimi odzivi, MVDA pa temelji na linearnih korelacijah. Zato smo s pomočjo ANN opredelili tudi druge kritične materialne in procesne parametre, kot je velikost delcev modelne učinkovine, kar je skladno s pričakovanji, saj preiskovana formulacija vsebuje zdravilno učinkovino iz razreda BCS II. Kljub različnemu pristopu obdelave podatkov smo pokazali komplementarnost MVDA in ANN ter njun pomen pri doseganju višje ravni razumevanja procesa, možnosti preiskovanja vzrokov odstopov v procesu in določitvi primerne kontrolne strategije izdelka. Glede na pregled literaturnih virov, sta MVDA in ANN v našem delu prvič uporabljeni za obdelavo tako širokega nabora podatkov za preiskavo in optimizacijo pelet, pripravljenih z iztiskanjem in krogličenjem na industrijski ravni. Ta pristop razvoja izdelkov z vgrajeno kakovostjo, ki uporablja različna statistična orodja, je preprosto prenosljiv tudi na druge farmacevtske izdelke. V drugem poglavju smo na vzorčnem primeru razvoja z vgrajeno kakovostjo (ang. Quality by design – QbD) pelet z visoko vsebnostjo učinkovine in tremi oblogami proučevali prednosti uporabe slikovnih analiz za poglobljeno razumevanje procesa. Predstavili smo uporabnost PATVIS APA kot ene od dinamičnih slikovnih tehnik za: - dosego tarčne ali želene velikosti pelet pri procesu iztiskanja in krogličenja, - oceno izkoristka procesa iztiskanja in krogličenja na liniji (at line), - spremljanje uspešnosti procesa oblaganja pelet, zaznavanje potencialnega aglomeriranja pelet, spremljanje debeline obloge med oblaganjem pelet z možnostjo določitve končne točke. Uporaba dinamične slikovne analize omogoča prilagoditve procesnih parametrov med procesom, kar je dodana vrednost za industrijsko okolje, saj s tem neposredno vpliva na kakovost zdravil in izkoristek serij. V tretjem poglavju smo nadaljevali proučevanje oblaganja pelet. Osredotočili smo se na proces razprševanja, ki pomembno vpliva na kakovost filmske obloge. Z namenom povečanja možnosti za uspeh pri prenosu oblaganja pelet iz laboratorijske na industrijsko raven smo proučili vpliv procesnih parametrov (hitrost pretoka disperzije, tlak za razprševanje, tlak za mikroklimo) in lastnosti disperzije (viskoznost, površinska napetost, gostota) na velikosti kapljic ter porazdelitev velikosti kapljic pri tvorbi s trokanalno šobo. S pomočjo po meri narejene optične proge, ki omogoča spremljanje velikosti, smeri in hitrosti kapljic, smo razvili semiempirična modela za napovedovanje povprečne velikosti in razporeditve velikosti kapljic. Na podlagi modelov lahko dosežemo primerljivo velikost kapljic na laboratorijski in industrijski ravni s prilagoditvijo procesnih parametrov. Po našem vedenju gre za prvi model za napovedovanje tako velikosti kapljic kot njihove razporeditve, ki vključuje newtonske in nenewtonske disperzije ter sočasno tudi variiranje procesnih parametrov. Razvita modela sta uporabna za vse procese oblaganja pelet s proučevano trokanalno šobo. Bistvena prednost pa je, da je pristop k razvoju modela uporaben za vse procese tvorbe kapljic, torej ga lahko razširimo na sušenje z razprševanjem, granuliranje in oblaganje drugih farmacevtskih oblik. Ključna prednost tega raziskovalnega dela je zagotovitev vpogleda v nove in inovativne pristope za razvoj pelet z vgrajeno kakovostjo. Predstavljeni pristopi so prenosljivi tudi na druge farmacevtske izdelke. Načrtovanje eksperimentov je bolj primerno v zgodnjih stopnjah razvoja farmacevtskih izdelkov, posebej na laboratorijski ravni, kjer lahko poskuse načrtujemo sistematično (npr. vrednotenje velikosti kapljic). Statistični tehniki, kot sta MVDA in ANN, pa sta bolj uporabni za vrednotenje večjih sklopov podatkov, ki jih praviloma pridobimo na rednih industrijskih serijah med življenjskim ciklom farmacevtskega izdelka in služita kot odličen pristop pri iskanju vzroka za odstope. Po drugi strani pa so predstavljene dinamične slikovne analize (kot je PATVIS APA) močno orodje v obeh stopnjah procesa, tako med zgodnjim razvojem za poglobljeno razumevanje procesa in življenjskim ciklom izdelka kot ena od potencialnih procesno-analitskih tehnik