Bridging science & regulation: quality by design in patient- focused formulation development

Patient acceptance and usability play a crucial role in achieving successful therapeutic outcomes. Consequently, there is an imperative to incorporate patient-focused formulation design into the pharmaceutical development process, particularly for more vulnerable patient populations such as paediatric and geriatric. This approach aligns with the scientific quality by design (QbD) principle, where products' critical quality attributes (CQAs), as well as critical attributes of the starting materials (CMAs) and critical process parameter (CPPs) are identified and tailored to accommodate patient-related attributes. A number of marketed products have failed to reach their full therapeutic potential due to insufficient recognition of patients' needs and the characteristics of the treated disease or condition. As a result, science-based patient-focused formulation development is now supported through regulatory programs and guidelines. Advanced data analysis and computational tools are also leveraged to support safety and effectiveness of new drugs. Regulatory agencies frequently convene expert advisory committees comprising scientists, clinicians, and patient representatives to review and evaluate new drug applications. Various approaches to patient-focused formulation development encompass the selection of specific dosage forms and/or administration routes (e.g. orodispersible and chewable tablets, transdermal patches), modified release formulations (delivering drugs over daily to yearly time frames depending on the dosage form), combination products (mostly marketed as fixed-dose combinations of cardiovascular medicines), personalized medicines (customized based on patients' genetic and/or metabolic characteristics), etc. The identification of potential polypharmacy requirements and specific changes in (patho)physiology, metabolism, and excretion, as well as side effects or changes in behavioral traits arising from the disease's progress, should remain some of key drivers for product design. For special patient groups like children, considerations of palatability (including taste masking), dose adjustment, and age-appropriate dosage forms are essential. Challenges associated with such an approach include heterogeneity of patients, including small sub-populations, and complex process that requires high-risk decision-making during the formulation development. Therefore, fostering scientific evidence and guidance from the early stages of new formulation development, while considering all potential CQAs that might contribute to products' acceptability and usability, is crucial.10th IAPC Meeting, Book of Abstract

Inovacije u formulaciji i procesu: QbD pristup i PAT alati podržani tehnikama veštačke inteligencije

QbD (Quality by Design) and PAT (Process Analytical Technologies) concepts significantly facilitate the implementation of new technologies in the pharmaceuticals ́ formulation and processes development. From simple formulations to complex delivery systems, QbD approach allows identification of the critical process parameters and material properties affecting the pharmaceutical products quality. For the analysis of complex relationships, establishment of the design space and, most importantly, control strategies, modeling and simulation tools are of paramount importance (1). Hybrid models, which combine elements of mechanistic modeling and empirical approach, are particularly important for processing of large amount of data collected by monitoring the process with PAT tools. This enables the establishment of a virtual copy (digital twin), or cyber-physical system, which facilitates the optimization and continuous improvement of the process. Artificial intelligence techniques in formulation and process innovations involve different machine learning algorithms. They are used to solve regression or classification problems and to process data of various types (numerical, textual, images, etc). Artificial neural networks can be applied from the initial formulation development to the production of validation batches for which the bioequivalence predicted by models has been confirmed (2). Artificial intelligence technology is also very important for the design and application of virtual copies of continuous production processes or complex biotechnological processes. This facilitates the implementation of the Real Time Release Testing (RTRT) strategy. It is to be expected that good modeling practices will be more precisely defined through the official regulatory guidelines, in the context of the application of artificial intelligence techniques.QbD (Quality by Design) i PAT (Process Analytical Technologies) koncepti značajno olakšavaju implementaciju novih tehnologija u razvoju formulacija i procesa za proizvodnju farmaceutskih preparata. Оd jednostavnih formulacija do kompleksnih nosača, QbD pristup omogućava identifikaciju kritičnih procesnih parametara i karakteristika materijala koji utiču na kvalitet farmaceutskih proizvoda. Za analizu kompleksnih veza, uspostavljanje design space-a i, što je najznačajnije, kontrolne strategije od izuzetnog značaja su alati za modelovanje i simulacije (1). Hibridni modeli, koji kombinuju elemente mehanističkog modelovanja i empirijskog pristupa su naročito značajni za obradu velikog obima podataka koji se prikupljanju praćenjem procesa PAT alatima. Na taj način se omogućava uspostavljanje virtuelne kopije (digital twin), odnosno sajber-fizičkog sistema, čime je olakšana optimizacija i kontinuirano unapređenje procesa. Tehnike veštačke inteligencije koje se primenjuju u kontekstu implementacije QbD i PAT alata u formulacionim i procesnim inovacijama podrazumevaju različite algoritme mašinskog učenja. Koriste se za rešavanje regresionih ili klasifikacionih problema i obradu podataka različitog tipa (numerički, teksutalni, zapisi u slikovnom formatu, itd). Veštačke neuronske mreže mogu da se primene od inicijalnog razvoja formulacije do proizvodnje validacionih serija za koje je potvrđena bioekvivalentnost predviđena modelima (2). Tehničke veštačke inteligencije su takođe veoma značajne za dizajn i primenu virtuelnih kopija procesa kontinuirane proizvodnje ili kompleksnih biotehnoloških procesa. Na taj način se olakšava implementacija strategije puštanja leka u realnom vremenu (Real Time Release Testing, RTRT). Za očekivati je da se i kroz smernice regulatornih tela preciznije definišu dobre prakse u modelovanju, u kontekstu primene tehnika veštačke inteligencije u podršci QbD i PAT koncepata.VIII Kongres farmaceuta Srbije sa međunarodnim učešćem, 12-15.10.2022. Beogra

Application of machine-learning algorithms for better understanding of tableting properties of lactose co-processed with lipid excipients

Co-processing (CP) provides superior properties to excipients and has become a reliable option to facilitated formulation and manufacturing of variety of solid dosage forms. Development of directly compressible formulations with high doses of poorly flowing/compressible active pharmaceutical ingredients, such as paracetamol, remains a great challenge for the pharmaceutical industry due to the lack of understanding of the interplay between the formulation properties, process of compaction, and stages of tablets’ detachment and ejection. The aim of this study was to analyze the influence of the compression load, excipients’ co-processing and the addition of paracetamol on the obtained tablets’ tensile strength and the specific parameters of the tableting process, such as (net) compression work, elastic recovery, detachment, and ejection work, as well as the ejection force. Two types of neural networks were used to analyze the data: classification (Kohonen network) and regression networks (multilayer perceptron and radial basis function), to build prediction models and identify the variables that are predominantly affecting the tableting process and the obtained tablets’ tensile strength. It has been demonstrated that sophisticated data-mining methods are necessary to interpret complex phenomena regarding the effect of co-processing on tableting properties of directly compressible excipients

Evaluation of dilution capacity and compaction behaviour of the excipients co-processed by in situ fluidized bed melt granulation

1. INTRODUCTION Co-processing has emerged as a suitable approach to meet the increasing demands for excipients with improved tableting performance. Apart from the most commonly used energy-consuming co-processing methods (e.g. spray-drying and wet granulation), melt granulation as a solvent-free and more environmentally friendly technique has recently gained more attention [1]. The aim of the present study was to investigate the influence of meltable binder particle size and compaction parameters on dilution capacity and compaction behaviour of lactose-based coprocessed excipients. 2. MATERIALS AND METHODS 2.1. Materials Paracetamol (Acros Organics, Belgium) was used as the model drug. Lactose monohydrate (Carlo Erba Reagents, Italy) was used as filler and glyceryl palmitostearate (Precirol® ATO 5 Gattefossé S.A.S, France) as meltable binder. 2.2. Preparation of co-processed excipients Co-processed excipients were prepared by in situ melt granulation in Mycrolab fluid bed processor (OYSTAR Hüttlin, Germany). Precirol® particles (15%) from the 125–180 μm (≈ 150 μm) or 600–710 μm sieve fraction (≈ 655 μm) were used for granulation of lactose (85%). The inlet air flow rate was 30 m3/h, and product temperature during agglomeration was 65 °C. 2.3. Particle size and shape analysis Granule size distribution was evaluated by sieve analysis, and median particle diameter (d50) was calculated by linear interpolation of the cumulative percentage frequency curve. Granule shape was examined by 2D scanned image (4800 dpi resolution) analysis using ImageJ software. The aspect ratio (AR) and circularity (C) were calculated for granule shape evaluation. 2.3. Determination of the Carr index The bulk and tapped (1250 taps) densities of coprocessed excipients and their mixtures with 30, 40 or 50% paracetamol were determined using tap density tester STAV 2003 (J. Engelsmann AG, Germany), and Carr index was calculated. 2.4. Dynamic compaction analysis Co-processed excipients and their mixtures with paracetamol were compressed on a single punch instrumented tablet press (GTP D series, Gamlen Tableting Ltd, UK). Compacts (100 mg) were compressed under compression load of 200 kg (≈ 70 MPa) or 500 kg (≈ 173MPa), and compression speed of 60 or 120 mm/min. 6 mm flat faced punches were used. The obtained force-displacement curves were used to calculate: net work of compression (NW), detachment stress (DS), ejection stress (ES). Tablet crushing force was determined using tablet hardness tester Erweka TBH 125D (Erweka GmbH, Germany), and the values obtained were used to calculate tensile strength (TS). Elastic recovery (24 h after compression) was calculated, as well. 2.4. Experimental Design In order to investigate the influence of binder particle size, paracetamol content and compression speed on the abovementioned compaction properties, compacts were prepared, at compression load of 500 kg, according to 23 full factorial design. 3. RESULTS AND DISCUSSION 3.1. Particle size and shape Larger initial binder particle size led to formation of larger and more spherical granules (Table 1). 147 Table 1. The size and shape of the co-processed excipients’ particles. Binder PS (μm) d50 AR C 150 564.9 1.33 0.81 655 846.2 1.14 0.86 3.2. Flowability The Carr index values obtained indicated considerably better flowability of the coprocessed excipient prepared by using larger binder particles (P655) in comparison with the excipient prepared with smaller binder particles (P150). This might be ascribed to more spherical and larger particles of P655. However, the addition of paracetamol led to an increase in Carr index values and less pronounced differences between two excipients (Fig. 1). Figure 1. The influence of paracetamol loading on flowability of co-processed excipients. 3.3. Compaction behaviour The results obtained revealed better mechanical properties of P150 in comparison with P655 compacts, irrespective of the compression pressure applied. The addition of paracetamol, as the model API with poor compaction properties, led to decrease in tensile strength of the compacts prepared with both excipients, and paracetamol content showed statistically significant influence on TS (p < 0.0001). Acceptable tensile strength (> 1 MPa) could be achieved for compacts with 30% paracetamol compressed at higher compression pressure (≈ 173 MPa). Paracetamol content, compression speed and interaction between binder particle size and paracetamol content were found to significantly affect NW. The influence of binder particle size was more pronounced at higher paracetamol content, with lower NW observed in the case of P655. Higher compression speed led to higher NW. Relatively low values of detachment and ejection stress (< 3.5 MPa) indicate good antiadhesive and lubricating properties of the investigated excipients. Lower values of both parameters were observed in the case of P655 which could be related to different agglomeration mechanisms involved. Besides binder particle size, compression speed and paracetamol content were found to significantly influence these properties. Elastic recovery values of the investigated samples ranged between 12 and 28%. In the case of both excipients, higher elastic recovery values were obtained at higher compression pressure. ER values of the compacts prepared at higher compression pressure were significantly affected by compression speed and interactions of the investigated variables. 4. CONCLUSION The results obtained show that meltable binder particle size affects granule size and shape, and consequently may influence flowability and compaction behaviour of the co-processed excipients. Interactions between binder particle size and compaction variables were also found to affect compaction properties of the investigated excipients.Pharma Sciences of Tomorrow Ljubljana, Slovenia, 15 th -17 th September, 202

Microencapsulation methods for plants biologically active compounds: A review

Biologically active compounds from plants have attracted great interest due to their affordability, effectiveness and low toxicity. Herbal extracts provide an infinite resource of raw materials for pharmaceutical, cosmetic and food industry. Unfortunately, use of the valuable natural compounds can be limited by their low bioavailability, volatilization of active compounds, sensitivity to the temperature, oxidation and UV light, in vivo instability, as well as unpleasant taste. One of the potential strategies to overcome these issues is microencapsulation of the biologically active ingredients. In this review, preparation, applications and limitations of the most popular techniques for microencapsulation, such as spray drying, fluid bed coating, encapsulation using supercritical fluids, freeze drying, ionic gelation, emulsification-solvent removal methods and formulation of liposomes, were discussed. Also, microparticles properties produced by presented microencapsulation methods were interpreted

Savremeni trendovi u formulaciji i primeni lekova u terapiji depresije kod dece i odraslih

Depression is the most common mental disorder in the general population and often requires long-term administration of antidepressants. Development of the modified release antidepressant products has led to the lower incidence of the adverse effects and improvement in the adherence, and subsequently to better therapeutic outcomes. Modified release may involve delayed and/or prolonged release of antidepressants. There is an increasing number of marketed antidepressant products in the form of orally dispersible tablets, for the treatment of a particular group of patients with impaired swallowing. Pharmacotherapy of depression in children represents a great challenge due to insufficient data regarding efficacy and safety. Furthermore, in the market of Republic of Serbia, there are no antidepressant products in the age-appropriate dosage forms for pediatric patients. It is, therefore, of great importance to address the risks related to the application of the conventional dosage forms of marketed antidepressants (tablets, hard capsules) to children. Novel treatment options include development of carriers for targeted delivery of antidepressants in the central nervous system. Intranasal administration of antidepressants is particularly favored since it allows the delivery of active ingredients via olfactory and trigeminal nerves. Other transmucosal routes of administration, such as buccal or sublingual, can provide improved therapeutic outcomes, compared to the conventional oral administration, due to circumvention of the intense metabolism of the active ingredients and undesired gastrointestinal side effects.Depresija je najčešći mentalni poremećaj u opštoj populaciji i neretko zahteva dugotrajnu primenu lekova iz grupe antidepresiva. Razvojem preparata sa modifikovanim oslobađanjem lekovite supstance omogućeno je smanjenje neželjenih efekata i poboljšanje adherence, a samim tim i poboljšanje terapijskih ishoda. Modifikacija oslobađanja podrazumeva odloženo i/ili produženo oslobađanje antidepresiva. Za terapiju određene grupe pacijenata sa otežanim gutanjem od velikog značaja je i sve veći broj registrovanih preparata u obliku oralno-disperzibilnih tableta. Farmakoterapija depresije kod dece predstavlja veliki izazov zbog nedostatka podataka o efikasnosti i bezbednosti. Takođe, na tržištu Republike Srbije nisu registrovani preparati sa antidepresivima u farmaceutskim oblicima prilagođenim pedijatrijskom uzrastu. Zbog toga je veoma značajno razmotriti rizike povezane sa primenom konvencionalnih farmaceutskih oblika antidepresiva (tablete, tvrde kapsule) kod dece. Savremeni farmaceutski oblici podrazumevaju razvoj nosača za ciljanu isporuku antidepresiva u centralni nervni sistem. Naročito se ističe intranazalni put primene jer omogućava isporuku lekovitih supstanci putem olfaktornog i trigeminalnog nerva. I drugi transmukozni putevi primene, poput bukalnog ili sublingvalnog, omogućavaju unapređenje terapijskih ishoda jer se, u odnosu na peroralni put primene, zaobilazi intenzivan metabolizam lekovitih supstanci i izbegavaju neželjeni gastrointestinalni efekti

Assessment of mucoadhesive buccal tablets with propranolol hydrochloride using principal component analysis

Multivariate analysis methods are a set of statistical techniques that allow multiple variables to be tested simultaneously. This makes them ideal for studying relationships in large complex datasets. Pharmaceutical products and drug manufacturing processes are complex systems by nature and can therefore, be described using multifactorial relationships. One of the commonly used methods of multivariate analysis is principal components analysis (PCA), which in short, transforms a large set of variables into a smaller set of new variables, which are designated as principal components (PCs). Principal component represents a linear combination of the original variables (Ferreira et Tobyn, 2015; Esbensen et Geladi, 2009). This study aimed to investigate the variability and the possibility of differentiation of the formulated buccal tablet formulations using PCA.14th Central European Symposium on Pharmaceutical Technology, 28th - 30th September, Ohrid, N. Macedonia, 202

Pregled primene algoritama mašinskog učenja u farmaceutskoj tehnologiji

Machine learning algorithms, and artificial intelligence in general, have a wide range of applications in the field of pharmaceutical technology. Starting from the formulation development, through a great potential for integration within the Quality by design framework, these data science tools provide a better understanding of the pharmaceutical formulations and respective processing. Machine learning algorithms can be especially helpful with the analysis of the large volume of data generated by the Process analytical technologies. This paper provides a brief explanation of the artificial neural networks, as one of the most frequently used machine learning algorithms. The process of the network training and testing is described and accompanied with illustrative examples of machine learning tools applied in the context of pharmaceutical formulation development and related technologies, as well as an overview of the future trends. Recently published studies on more sophisticated methods, such as deep neural networks and light gradient boosting machine algorithm, have been described. The interested reader is also referred to several official documents (guidelines) that pave the way for a more structured representation of the machine learning models in their prospective submissions to the regulatory bodies.Algoritmi mašinskog učenja, kao i veštačka inteligencija u širem smislu, su veoma značajni i primenjuju se u razne svrhe u okviru farmaceutske tehnologije. Počevši od razvoja formulacija, preko izuzetnog potencijala za integraciju u koncept dizajna kvaliteta (engl. Quality by design), algoritmi mašinskog učenja omogućavaju bolje razumevanje uticaja kako formulacionih faktora tako i odgovarajućih procesnih parametara. Algoritmi mašinskog učenja mogu biti od naročitog značaja i za analizu velikog obima podataka koji se generišu korišćenjem procesnih analitičkih tehnologija. U ovom radu su ukratko predstavljene veštačke neuronske mreže, kao jedan od najčešće korišćenih algoritama mašinskog učenja. Prikazani su procesi treninga i testiranja mreža, kao i ilustrativni primeri algoritama primenjenih za različite potrebe razvoja i/ili optimizacije farmaceutskih formulacija i postupaka njihove izrade. Takođe, dat je i pregled budućih trendova u ovoj oblasti, kao i novijih studija o sofisticiranim metodama, poput dubokih neuronskih mreža, i light gradient boosting algoritma. Zainteresovani čitaoci se takođe upućuju na nekoliko zvaničnih dokumenata (vodiča), po uzoru na koje mogu da se očekuju i preporuke za strukturiranu prezentaciju modela mašinskog učenja koji će se podnositi regulatornim telima u okviru dokumentacije koja se priprema za potrebe registracije novih lekova