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Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design

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A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Pharmaceutical Technology, Manufacturing and Devices".

Deadline for manuscript submissions: closed (10 November 2020) | Viewed by 42023

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Prof. Dr. Amrit Paudel

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Graz University of Technology & Research Center Pharmaceutical Engineering (RCPE), Graz, Austria
Interests: drug delivery; solid-state pharmaceutics; stability; amorphous drugs; pharmaceutical material science; pulmonary drug delivery; poorly soluble drug formulations; biopharmaceutics
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Special Issue Information

Dear Colleagues,

Pharmaceutical process and product design still largely encompass the trial and error and empirically-based approaches. However, the advancement in physical, chemical, biological, clinical, and engineering science as well as in computational technologies over the last few decades has shown encouraging contributions in shifting the paradigm of drug product development towards rationally- and mechanistically-based products. This enables a priori predictions of material properties, processability, manufacturability, drug release, and clinical performance, as well as physical and chemical stability of pharmaceutical products. This could ultimately be achieved by understanding multiscale physical and chemical processes of a wide range of length and time scales involved in transforming a drug molecule to a finished dosage form with a desired/tailored performance. A comprehensive knowledge obtained through the advanced characterization of solution, colloidal, and solid-state chemistry of pharmaceutical formulations and the involved process can be transformed into a set of multiscale computational models that can expedite drug product development by utilizing minimal material and resources. In this context, there is a growing interest of developing digital twins of pharmaceutical processes, and materials up to human physiology to predict the fate of drug formulation during manufacturing, storage, supply chain, as well as administration to patients by leveraging cross-disciplinary science.

Therefore, this Special Issue intends to compile top-level contributions in the form of research articles, opinions, and reviews from key academic and industrial opinion leaders and eminent groups dealing with the predictive science applied to pharmaceutical material, process, and product developments. We encourage the submission of case studies of applying a wide diversity of modeling and simulations, such as molecular simulations, crystals, and crystallization modeling (MD simulations, QM, QC calculations), contact mechanics, macroscopic modeling of particle and powder processes (e.g., CFD-DEM, LBM, FEM, PBE), physiologically-based absorption modeling (e.g., PBPK, PBB, IVIVC), machine learning/AI applied to pharmaceutical product and processes, etc. In addition, small-scale predictive experiments that generate predictive knowledge of processes and products at larger scales, as well as in vitro understanding that can predict the fate of drug product in vivo are also welcome.

Prof. Dr. Amrit Paudel
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Keywords

Mechanistic modeling of drug product processes and up-/downscaling
Model-assisted formulation design and development
Prediction of solubility, miscibility, phase diagrams, and drug-excipient interactions
Predictive approaches to physical and chemical stability
Predictive approaches to pharmaceutical and clinical performance of drug products
Structure–property–performance relationship of pharmaceutical materials

Published Papers (11 papers)

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Research

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13 pages, 757 KiB

Open AccessArticle

Natural Polymer Chitosan as Super Disintegrant in Fast Orally Disintegrating Meloxicam Tablets: Formulation and Evaluation

by Gailute Draksiene, Brigita Venclovaite, Lauryna Pudziuvelyte, Liudas Ivanauskas, Mindaugas Marksa and Jurga Bernatoniene

Pharmaceutics 2021, 13(6), 879; https://doi.org/10.3390/pharmaceutics13060879 - 15 Jun 2021

Cited by 3 | Viewed by 2518

Abstract

The aim of the present investigation was to formulate fast disintegrating tablets of meloxicam by wet granulation technique using medium molecular weight chitosan. The orally disintegrating tablets of meloxicam with chitosan showed good mechanical and disintegration properties and good dissolution rate when prepared in tablet press using 10.8 kN and 11.0 kN compression force. Chitosan is a suitable biopolymer to moderate the disintegration process in orally disintegrating tablets. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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24 pages, 3023 KiB

Open AccessArticle

Understanding Carrier Performance in Low-Dose Dry Powder Inhalation: An In Vitro–In Silico Approach

by Joana T. Pinto, Inês Cachola, João F. Pinto and Amrit Paudel

Pharmaceutics 2021, 13(3), 297; https://doi.org/10.3390/pharmaceutics13030297 - 24 Feb 2021

Cited by 9 | Viewed by 3105

Abstract

The use of physiologically based pharmacokinetic (PBPK) models to support drug product development has become increasingly popular. The in vitro characterization of the materials of the formulation provides valuable descriptors for the in silico prediction of the drug’s pharmacokinetic profile. Thus, the application of an in vitro–in silico framework can be decisive towards the prediction of the in vivo performance of a new medicine. By applying such an approach, this work aimed to derive mechanistic based insights into the potential impact of carrier particles and powder bulk properties on the in vivo performance of a lactose-based dry powder inhaler (DPI). For this, a PBPK model was developed using salbutamol sulphate (SS) as a model drug and the in vitro performance of its low-dose blends (2% w/w) with different types of lactose particles was investigated using different DPI types (capsule versus reservoir) at distinct airflows. Likewise, the influence of various carrier’s particle and bulk properties, device type and airflow were investigated in silico. Results showed that for the capsule-based device, low-dose blends of SS had a better performance, when smaller carrier particles (Dv_0.5 ≈ 50 μm) with about 10% of fines were used. This resulted in a better predicted bioavailability of the drug for all the tested airflows. For the reservoir type DPI, the mean particle size (Dv_0.5) was identified as the critical parameter impacting performance. Shear cell and air permeability or compressibility measurements, particle size distribution by pressure titration and the tensile strength of the selected lactose carrier powders were found useful to generate descriptors that could anticipate the potential in vivo performance of the tested DPI blends. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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22 pages, 5260 KiB

Open AccessArticle

On Absorption Modeling and Food Effect Prediction of Rivaroxaban, a BCS II Drug Orally Administered as an Immediate-Release Tablet

by Varun Kushwah, Sumit Arora, Miklós Tamás Katona, Dattatray Modhave, Eleonore Fröhlich and Amrit Paudel

Pharmaceutics 2021, 13(2), 283; https://doi.org/10.3390/pharmaceutics13020283 - 20 Feb 2021

Cited by 18 | Viewed by 4972

Abstract

The present work evaluates the food effect on the absorption of rivaroxaban (Riva), a BCS II drug, from the orally administered commercial immediate-release tablet (Xarelto IR) using physiologically based pharmacokinetic (PBPK) and conventional in vitro–in vivo correlation (IVIVC) models. The bioavailability of Riva upon oral administration of Xarelto IR tablet is reported to exhibit a positive food effect. The PBPK model for Riva was developed and verified using the previously reported in vivo data for oral solution (5 and 10 mg) and Xarelto IR tablet (5 and 10 mg dose strength). Once the PBPK model was established, the in vivo performance of the tablet formulation with the higher dose strength (Xarelto IR tablet 20 mg in fasted and fed state) was predicted using the experimentally obtained data of in vitro permeability, biorelevant solubility and in vitro dynamic dissolution data using United States Pharmacopeia (USP) IV flow-through cell apparatus. In addition, the mathematical IVIVC model was developed using the in vitro dissolution and in vivo profile of 20 mg strength Xarelto IR tablet in fasted condition. Using the developed IVIVC model, the pharmacokinetic (PK) profile of the Xarelto IR tablet in fed condition was predicted and compared with the PK parameters obtained via the PBPK model. A virtual in vivo PK study was designed using a single-dose, 3-treatment cross-over trial in 50 subjects to predict the PK profile of the Xarelto® IR tablet in the fed state. Overall, the results obtained from the IVIVC model were found to be comparable with those from the PBPK model. The outcome from both models pointed to the positive food effect on the in vivo profile of the Riva. The developed models thus can be effectively extended to establish bioequivalence for the marketed and novel complex formulations of Riva such as amorphous solid dispersions. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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14 pages, 4070 KiB

Open AccessArticle

Novel Polymorph of Favipiravir—An Antiviral Medication

by Alexander S. Goloveshkin, Alexander A. Korlyukov and Anna V. Vologzhanina

Pharmaceutics 2021, 13(2), 139; https://doi.org/10.3390/pharmaceutics13020139 - 21 Jan 2021

Cited by 17 | Viewed by 4105

Abstract

Various solid forms of pharmaceutically important compounds exhibit different physical properties and bioactivity; thus, knowledge of the structural landscape and prediction of spontaneous polymorph transformations for an active pharmaceutical ingredient is of practical value for the pharmaceutical industry. By recrystallization from ethyl acetate, a novel polymorph of 6-fluoro-3-hydroxypyrazine-2-carboxamide (trademark favipiravir, RNA polymerase inhibitor) was obtained and characterized using differential scanning calorimetry (DSC), infra-red spectroscopy and powder X-ray diffraction (XRD) analysis. The favipiravir molecule in two polymorphs realizes similar H-bonding motifs, but the overall H-bonded networks differ. Based on periodic density functional theory calculations, the novel tetragonal polymorph with two interpenetrated H-bonded networks is slightly less stable than the orthorhombic one with the zst topology of the underlying H-bonded net that is in accord with experimentally observed powder XRD patterns of slow conversion of the tetragonal phase to the orthorhombic one. However, topological analysis of net relations revealed that no transformations can be applied to convert H-bonded networks in the experimental unit cells, and DSC data indicate no solid-state reactions at heating. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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16 pages, 2068 KiB

Open AccessArticle

Self-Nanoemulsion Loaded with a Combination of Isotretinoin, an Anti-Acne Drug, and Quercetin: Preparation, Optimization, and In Vivo Assessment

by Khaled M. Hosny, Khalid S. Al Nahyah and Nabil A. Alhakamy

Pharmaceutics 2021, 13(1), 46; https://doi.org/10.3390/pharmaceutics13010046 - 30 Dec 2020

Cited by 16 | Viewed by 3442

Abstract

Acne vulgaris is a common skin disease that affects everybody at least once in their lives. The treatment is challenging because the stratum corneum contains rigid corneocytes surrounded by intercellular lamellae that are difficult to bypass. In the present study, we intended to formulate an effective nanoemulsion that could deliver isotretinoin (ITT) with enhanced solubility, permeability, and bioavailability across the skin. ITT can have a serious hepatotoxic effect if given too frequently or erratically. Therefore, to overcome the aforesaid limitation, quercetin (QRS), a hepatoprotective agent, was incorporated into the formulation. Initially, the ITT solubility was determined in various surfactants and cosurfactants to select the essential ingredients to be used in the formulation and to optimize a nanoemulsion that could enhance the solubility and permeability of ITT and its antimicrobial activity against Staphyloccocus aureus, which is the main microorganism responsible for acne vulgaris. The mixture design was applied to study the interactions and optimize the independent variables that could match the prerequisites of selected dependent responses. A formulation containing 0.25 g of rosehip oil, 0.45 g of surfactant (Lauroglycol-90), and 0.3 g of cosurfactant (propylene glycol) was chosen as an optimized desirable formulation. The optimized batch was loaded with QRS and evaluated for in vitro and ex vivo permeation. The in vivo hepatotoxicity was assessed through topical administration. Permeability studies confirmed the enhanced permeation percentage of ITT (52.11 ± 2.85%) and QRS (25.44 ± 3.18%) of the optimized formulation, with an enhanced steady-state flux (Jss). The in vivo studies conducted on experimental animals demonstrated superior hepatoprotective activity of the prepared optimized formulation compared with other formulations of drugs and commercially marketed products. We anticipate that this optimized ITT formulation, followed up with good clinical evaluations, can be a breakthrough in the safe treatment of acne vulgaris. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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14 pages, 609 KiB

Open AccessArticle

Application of Dominance-Based Rough Set Approach for Optimization of Pellets Tableting Process

by Maciej Karolak, Łukasz Pałkowski, Bartłomiej Kubiak, Jerzy Błaszczyński, Rafał Łunio, Wiesław Sawicki, Roman Słowiński and Jerzy Krysiński

Pharmaceutics 2020, 12(11), 1024; https://doi.org/10.3390/pharmaceutics12111024 - 26 Oct 2020

Cited by 6 | Viewed by 2358

Abstract

Multiple-unit pellet systems (MUPS) offer many advantages over conventional solid dosage forms both for the manufacturers and patients. Coated pellets can be efficiently compressed into MUPS in classic tableting process and enable controlled release of active pharmaceutical ingredient (APIs). For patients MUPS are divisible without affecting drug release and convenient to swallow. However, maintaining API release profile during the compression process can be a challenge. The aim of this work was to explore and discover relationships between data describing: composition, properties, process parameters (condition attributes) and quality (decision attribute, expressed as similarity factor f₂) of MUPS containing pellets with verapamil hydrochloride as API, by applying a dominance-based rough ret approach (DRSA) mathematical data mining technique. DRSA generated decision rules representing cause–effect relationships between condition attributes and decision attribute. Similar API release profiles from pellets before and after tableting can be ensured by proper polymer coating (Eudragit^® NE, absence of ethyl cellulose), compression force higher than 6 kN, microcrystalline cellulose (Avicel^® 102) as excipient and tablet hardness ≥42.4 N. DRSA can be useful for analysis of complex technological data. Decision rules with high values of confirmation measures can help technologist in optimal formulation development. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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18 pages, 1055 KiB

Open AccessArticle

Multivariate Analytical Approaches to Identify Key Molecular Properties of Vehicles, Permeants and Membranes That Affect Permeation through Membranes

by Omaima N. Najib, Stewart B. Kirton, Gary P. Martin, Michelle J. Botha, Al-Sayed Sallam and Darragh Murnane

Pharmaceutics 2020, 12(10), 958; https://doi.org/10.3390/pharmaceutics12100958 - 11 Oct 2020

Cited by 2 | Viewed by 1774

Abstract

There has been considerable recent interest in employing computer models to investigate the relationship between the structure of a molecule and its dermal penetration. Molecular permeation across the epidermis has previously been demonstrated to be determined by a number of physicochemical properties, for example, the lipophilicity, molecular weight and hydrogen bonding ability of the permeant. However little attention has been paid to modeling the combined effects of permeant properties in tandem with the properties of vehicles used to deliver those permeants or to whether data obtained using synthetic membranes can be correlated with those obtained using human epidermis. This work uses Principal Components Analysis (PCA) to demonstrate that, for studies of the diffusion of three model permeants (caffeine, methyl paraben and butyl paraben) through synthetic membranes, it is the properties of the oily vehicle in which they are applied that dominated the rates of permeation and flux. Simple robust and predictive descriptor-based quantitative structure–permeability relationship (QSPR) models have been developed to support these findings by utilizing physicochemical descriptors of the oily vehicles to quantify the differences in flux and permeation of the model compounds. Interestingly, PCA showed that, for the flux of co-applied model permeants through human epidermis, the permeation of the model permeants was better described by a balance between the physicochemical properties of the vehicle and the permeant rather than being dominated solely by the vehicle properties as in the case of synthetic model membranes. The important influence of permeant solubility in the vehicle along with the solvent uptake on overall permeant diffusion into the membrane was substantiated. These results confirm that care must be taken in interpreting permeation data when synthetic membranes are employed as surrogates for human epidermis; they also demonstrate the importance of considering not only the permeant properties but also those of both vehicle and membrane when arriving at any conclusions relating to permeation data. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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9 pages, 1845 KiB

Open AccessArticle

Image-Based Artificial Intelligence Methods for Product Control of Tablet Coating Quality

by Cosima Hirschberg, Magnus Edinger, Else Holmfred, Jukka Rantanen and Johan Boetker

Pharmaceutics 2020, 12(9), 877; https://doi.org/10.3390/pharmaceutics12090877 - 15 Sep 2020

Cited by 20 | Viewed by 4243

Abstract

Mimicking the human decision-making process is challenging. Especially, many process control situations during the manufacturing of pharmaceuticals are based on visual observations and related experience-based actions. The aim of the present work was to investigate the use of image analysis to classify the quality of coated tablets. Tablets with an increasing amount of coating solution were imaged by fast scanning using a conventional office scanner. A segmentation routine was implemented to the images, allowing the extraction of numeric image-based information from individual tablets. The image preprocessing was performed prior to utilization of four different classification techniques for the individual tablet images. The support vector machine (SVM) technique performed superior compared to a convolutional neural network (CNN) in relation to computational time, and this approach was also slightly better at classifying the tablets correctly. The fastest multivariate method was partial least squares (PLS) regression, but this method was hampered by the inferior classification accuracy of the tablets. Finally, it was possible to create a numerical threshold classification model with an accuracy comparable to the SVM approach, so it is evident that there exist multiple valid options for classifying coated tablets. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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Review

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25 pages, 4563 KiB

Open AccessReview

Modeling and Simulation of Process Technology for Nanoparticulate Drug Formulations—A Particle Technology Perspective

by Jens Uhlemann, Holger Diedam, Werner Hoheisel, Tobias Schikarski and Wolfgang Peukert

Pharmaceutics 2021, 13(1), 22; https://doi.org/10.3390/pharmaceutics13010022 - 24 Dec 2020

Cited by 12 | Viewed by 3163

Abstract

Crystalline organic nanoparticles and their amorphous equivalents (ONP) have the potential to become a next-generation formulation technology for dissolution-rate limited biopharmaceutical classification system (BCS) class IIa molecules if the following requisites are met: (i) a quantitative understanding of the bioavailability enhancement benefit versus established formulation technologies and a reliable track record of successful case studies are available; (ii) efficient experimentation workflows with a minimum amount of active ingredient and a high degree of digitalization via, e.g., automation and computer-based experimentation planning are implemented; (iii) the scalability of the nanoparticle-based oral delivery formulation technology from the lab to manufacturing is ensured. Modeling and simulation approaches informed by the pharmaceutical material science paradigm can help to meet these requisites, especially if the entire value chain from formulation to oral delivery is covered. Any comprehensive digitalization of drug formulation requires combining pharmaceutical materials science with the adequate formulation and process technologies on the one hand and quantitative pharmacokinetics and drug administration dynamics in the human body on the other hand. Models for the technical realization of the drug production and the distribution of the pharmaceutical compound in the human body are coupled via the central objective, namely bioavailability. The underlying challenges can only be addressed by hierarchical approaches for property and process design. The tools for multiscale modeling of the here-considered particle processes (e.g., by coupled computational fluid dynamics, population balance models, Noyes–Whitney dissolution kinetics) and physiologically based absorption modeling are available. Significant advances are being made in enhancing the bioavailability of hydrophobic compounds by applying innovative solutions. As examples, the predictive modeling of anti-solvent precipitation is presented, and options for the model development of comminution processes are discussed. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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30 pages, 1689 KiB

Open AccessReview

Periodic DFT Calculations—Review of Applications in the Pharmaceutical Sciences

by Anna Helena Mazurek, Łukasz Szeleszczuk and Dariusz Maciej Pisklak

Pharmaceutics 2020, 12(5), 415; https://doi.org/10.3390/pharmaceutics12050415 - 01 May 2020

Cited by 38 | Viewed by 6945

Abstract

In the introduction to this review the complex chemistry of solid-state pharmaceutical compounds is summarized. It is also explained why the density functional theory (DFT) periodic calculations became recently so popular in studying the solid APIs (active pharmaceutical ingredients). Further, the most popular programs enabling DFT periodic calculations are presented and compared. Subsequently, on the large number of examples, the applications of such calculations in pharmaceutical sciences are discussed. The mentioned topics include, among others, validation of the experimentally obtained crystal structures and crystal structure prediction, insight into crystallization and solvation processes, development of new polymorph synthesis ways, and formulation techniques as well as application of the periodic DFT calculations in the drug analysis. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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Other

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15 pages, 713 KiB

Open AccessPerspective

Working within the Design Space: Do Our Static Process Characterization Methods Suffice?

by Moritz von Stosch, René Schenkendorf, Geoffroy Geldhof, Christos Varsakelis, Marco Mariti, Sandrine Dessoy, Annick Vandercammen, Alexander Pysik and Matthew Sanders

Pharmaceutics 2020, 12(6), 562; https://doi.org/10.3390/pharmaceutics12060562 - 17 Jun 2020

Cited by 19 | Viewed by 3865

Abstract

The Process Analytical Technology initiative and Quality by Design paradigm have led to changes in the guidelines and views of how to develop drug manufacturing processes. On this occasion the concept of the design space, which describes the impact of process parameters and material attributes on the attributes of the product, was introduced in the ICH Q8 guideline. The way the design space is defined and can be presented for regulatory approval seems to be left to the applicants, among who at least a consensus on how to characterize the design space seems to have evolved. The large majority of design spaces described in publications seem to follow a “static” statistical experimentation and modeling approach. Given that temporal deviations in the process parameters (i.e., moving within the design space) are of a dynamic nature, static approaches might not suffice for the consideration of the implications of variations in the values of the process parameters. In this paper, different forms of design space representations are discussed and the current consensus is challenged, which in turn, establishes the need for a dynamic representation and characterization of the design space. Subsequently, selected approaches for a dynamic representation, characterization and validation which are proposed in the literature are discussed, also showcasing the opportunity to integrate the activities of process characterization, process monitoring and process control strategy development. Full article

(This article belongs to the Special Issue Digital Pharmaceutics: Model-Informed Pharmaceutical Products and Process Design)

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