A review on the modernization of pharmaceutical development and manufacturing - Trends, perspectives, and the role of mathematical modeling

The state of technological advancement to address challenges in the manufacture of rAAV gene therapies

Current processes for the production of recombinant adeno-associated virus (rAAV) are inadequate to meet the surging demand for rAAV-based gene therapies. This article reviews recent advances that hold the potential to address current limitations in rAAV manufacturing. A multidisciplinary perspective on technological progress in rAAV production is presented, underscoring the necessity to move beyond incremental refinements and adopt a holistic strategy to address existing challenges. Since several recent reviews have thoroughly covered advancements in upstream technology, this article provides only a concise overview of these developments before moving to pivotal areas of rAAV manufacturing not well covered in other reviews, including analytical technologies for rapid and high-throughput measurement of rAAV quality attributes, mathematical modeling for platform and process optimization, and downstream approaches to maximize efficiency and rAAV yield. Novel technologies that have the potential to address the current gaps in rAAV manufacturing are highlighted. Implementation challenges and future research directions are critically discussed.

Efficient Simulation of Viral Transduction and Propagation for Biomanufacturing

The design of biomanufacturing platforms based on viral transduction and/or propagation poses significant challenges at the intersection between synthetic biology and process engineering. This paper introduces vitraPro, a software toolkit composed of a multiscale model and an efficient numeric technique that can be leveraged for determining genetic and process designs that optimize transduction-based biomanufacturing platforms and viral amplification processes. Viral infection and propagation for up to two viruses simultaneously can be simulated through the model, considering viruses in either the lytic or lysogenic stage, during batch, perfusion, or continuous operation. The model estimates the distribution of the viral genome(s) copy number in the cell population, which is an indicator of transduction efficiency and viral genome stability. The infection age distribution of the infected cells is also calculated, indicating how many cells are in an infection stage compatible with recombinant product expression or viral amplification. The model can also consider the presence of defective interfering particles in the system, which can severely compromise the productivity of biomanufacturing processes. Model benchmarking and validation are demonstrated for case studies of the baculovirus expression vector system and influenza A propagation in suspension cultures.

Optimization of green spherical agglomeration process based on response surface methodology for preparation of high-performance spherical particles

Spherical agglomeration (SA) is a processing technique that enhances the physical properties of particles, reduces the number of unit operations in pharmaceutical manufacturing, and improves process efficiency. However, one of the limitations of SA is its high nonlinearity, which makes scalability a challenge. This prospective study was designed to realize the optimization of SA process parameters of aspirin, the world's first and most widely used nonsteroidal anti-inflammatory drug, by developing a green SA model through response surface methodology. First, Plackett-Burman experiments were conducted to identify the key operating variables affecting SA, and Sustainability Index (STI) was defined to evaluate the effects of these operating variables on the SA and the energy input to the environment during the post-processing process. Furthermore, the effects of three independent variables on mean size, yield, and STI were investigated based on Box-Behnken design. A second-order regression equation with response values was developed to optimize the above three objectives. As a result, the spherical products were obtained with excellent powder properties, including anti-caking property, filtration property, and tableting performance compared to the raw materials. This work provides an experimental and modelling basis for the further application of this environmentally-friendly SA technology.

Mechanistic modeling of in vitro transcription incorporating effects of magnesium pyrophosphate crystallization

The in vitro transcription (IVT) reaction used in the production of messenger RNA vaccines and therapies remains poorly quantitatively understood. Mechanistic modeling of IVT could inform reaction design, scale-up, and control. In this work, we develop a mechanistic model of IVT to include nucleation and growth of magnesium pyrophosphate crystals and subsequent agglomeration of crystals and DNA. To help generalize this model to different constructs, a novel quantitative description is included for the rate of transcription as a function of target sequence length, DNA concentration, and T7 RNA polymerase concentration. The model explains previously unexplained trends in IVT data and quantitatively predicts the effect of adding the pyrophosphatase enzyme to the reaction system. The model is validated on additional literature data showing an ability to predict transcription rates as a function of RNA sequence length.

Experimental design of a film flow cleaning rig equipped with in-line process analytical technology (PAT) tool for real-time monitoring

The main purpose of this research was to develop an experimental film flow cleaning rig that can be combined with Process analytical technology (PAT) tools to reduce cleaning time and costs. Here, we show that the use of in-line UV-Vis was successful for real-time monitoring of the cleaning process of olanzapine as a challenging residue to clean. The cleaning process was found to be affected by the properties of the olanzapine soil, and the study showed the competing effects of mechanical lift-off and dissolution action with methanol as a solvent. However, The method is limited by the cleaning mechanisms, with the dissolution being the only mechanism that can be accurately quantified using an in-line UV-Vis PAT tool. This experimental approach can be used to optimize cleaning process conditions and solvent choices at the bench scale before deployment. The material of which the cleaning rig was printed limited the solvent that could be used for this study, and future modifications will include a more chemical-resistant material.

A framework for the in silico assessment of the robustness of an MPC in a CDC line in function of process variability

The shift from batch manufacturing towards continuous manufacturing for the production of oral solid dosages requires the development and implementation of process models and process control. Previous work focused mainly on developing deterministic models for the investigated system. Furthermore, the in silico tuning and analysis of a control strategy are mostly done based on deterministic models. This deterministic approach could lead to wrong actions in diversion strategies and poor transferability of the controller performance if the system behaves differently than the deterministic model. This work introduces a framework that explicitly includes the process variability which is characteristic of powder handling processes and tests it on a novel continuous feeding-blending unit (i.e., the FE continuous processing system (CPS)), followed by a tablet press (i.e., the FE 55). It employs a stochastic model by allowing the model parameters to have a probability distribution. The performance of a model predictive control (MPC), steering the feed rate of the main excipient feeder to compensate for the feed rate deviations of the active pharmaceutical ingredient (API) feeder to keep the API concentration close to the desired value, is evaluated and the impact of process variability is assessed in a Monte Carlo (MC) analysis. Next to the process variability, a model for the prediction error of the chemometric model and realistic feed rate disturbances were included to increase the transferability of the results to the real system. The obtained results show that process variability is inherently present and that wrong conclusions can be drawn if it is not taken into account in the in silico analysis.

Control strategy for biopharmaceutical production by model predictive control

The biopharmaceutical industry is rapidly advancing, driven by the need for cutting-edge technologies to meet the growing demand for life-saving treatments. In this context, Model Predictive Control (MPC) has emerged as a promising solution to address the complexity of modern biopharmaceutical production processes. Its ability to optimize operations and ensure consistent product yields has made it an attractive option for manufacturers in this sector. Furthermore, MPC's alignment with the Process Analytical Technology (PAT) initiative provides an additional layer of assurance, facilitating real-time monitoring and enabling swift adjustments to maintain process integrity. This comprehensive review delves into the various applications of MPC, ranging from robust control to stochastic model predictive control, thereby equipping biotechnologists and process engineers with a powerful toolset. By harnessing the capabilities of MPC, as elucidated in this review, manufacturers can confidently navigate the intricate bioprocessing landscape and unlock this approach's full potential in their production processes.

Design space determination of pharmaceutical processes: Effects of control strategies and uncertainty

The identification of process Design Space (DS) is of high interest in highly regulated industrial sectors, such as pharmaceutical industry, where assurance of manufacturability and product quality is key for process development and decision-making. If the process can be controlled by a set of manipulated variables, the DS can be expanded in comparison to an open-loop scenario, where there are no controls in place. Determining the benefits of control strategies may be challenging, particularly when the available model is complex and computationally expensive - which is typically the case of pharmaceutical manufacturing. In this study, we exploit surrogate-based feasibility analysis to determine whether the process satisfies all process constraints by manipulating the process inputs and reduce the effect of uncertainty. The proposed approach is successfully tested on two simulated pharmaceutical case studies of increasing complexity, i.e., considering (i) a single pharmaceutical unit operation, and (ii) a pharmaceutical manufacturing line comprised of a sequence of connected unit operations. Results demonstrate that different control actions can be effectively exploited to operate the process in a wider range of inputs and mitigate uncertainty.

Impact of GAMP 5, data integrity and QbD on quality assurance in the pharmaceutical industry: How obvious is it?

In the pharmaceutical industry, it is essential to ensure the safety and efficacy of medicinal products. Therefore a robust quality assurance framework is needed. This manuscript examines the impact of GAMP 5 and data integrity (DI) on quality assurance, while also highlighting the role of quality by design (QbD) principles. GAMP 5 is a widely used framework for validating automated systems that establishes quality assurance practices. DI guarantees the reliability of data collected throughout various stages of drug development. The integration of QbD principles promotes a systematic approach to development that emphasizes a deep understanding of critical quality attributes, risk management, and continuous improvement. With their implementation, organizations are able to meet regulatory requirements and provide safe medications to patients worldwide.

Mechanistic modeling explains the production dynamics of recombinant adeno-associated virus with the baculovirus expression vector system

Current manufacturing processes for recombinant adeno-associated viruses (rAAVs) have less-than-desired yields and produce significant amounts of empty capsids. The increasing demand and the high cost of goods for rAAV-based gene therapies motivate development of more efficient manufacturing processes. Recently, the US Food and Drug Administration (FDA) approved the first rAAV-based gene therapy product manufactured in the baculovirus expression vector system (BEVS), a technology that demonstrated production of high titers of full capsids. This work presents a first mechanistic model describing the key extracellular and intracellular phenomena occurring during baculovirus infection and rAAV maturation in the BEVS. The model predictions are successfully validated for in-house and literature experimental measurements of the vector genome and of structural and non-structural proteins collected during rAAV manufacturing in the BEVS with the TwoBac and ThreeBac constructs. A model-based analysis of the process is carried out to identify the bottlenecks that limit full capsid formation. Vector genome amplification is found to be the limiting step for rAAV production in Sf9 cells using either the TwoBac or ThreeBac system. In turn, vector genome amplification is hindered by limiting Rep78 levels. Transgene and non-essential baculovirus protein expression in the insect cell during rAAV manufacturing also negatively influences the rAAV production yields.

Generic Drug Shortage in Japan: GMP Noncompliance and Associated Quality Issues

Government campaigns to replace off-patent brand pharmaceuticals with low cost generic products in national health insurance systems have apparently increased their production in the last two decades in Japan. The contamination of a batch of generic itraconazole tablets with the sleep inducer rilmazafone caused significant adverse events and related accidents in 2020, amidst increasing use of the generic products in healthcare. Investigations revealed many Good Manufacturing Practice (GMP) violations and other evidence of poor quality management in the manufacturing/marketing authorization holder (MAH). Urgent inspection of other MAHs found multiple cases of GMP noncompliance that resulted in temporary administrative suspension. Various quality issues, including nonconformity in stability monitoring, in these generic MAHs resulted in prolonged suspension of product shipments and shortages in medical institutions. These problems highlighted long-standing issues in quality management by MAHs and inspections by authorities, which had been neglected during rapid production expansion. This review introduces these manufacturing control and management problems and their countermeasures, and discusses the impact of habitual inadequate development processes that disregard the quality-by-design (QbD) perspective as the root cause of the issues.

Differences between Omicron SARS-CoV-2 RBD and other variants in their ability to interact with cell receptors and monoclonal antibodies

SARS-CoV-2 remains a health threat with the continuous emergence of new variants. This work aims to expand the knowledge about the SARS-CoV-2 receptor-binding domain (RBD) interactions with cell receptors and monoclonal antibodies (mAbs). By using constant-pH Monte Carlo simulations, the free energy of interactions between the RBD from different variants and several partners (Angiotensin-Converting Enzyme-2 (ACE2) polymorphisms and various mAbs) were predicted. Computed RBD-ACE2-binding affinities were higher for two ACE2 polymorphisms (rs142984500 and rs4646116) typically found in Europeans which indicates a genetic susceptibility. This is amplified for Omicron (BA.1) and its sublineages BA.2 and BA.3. The antibody landscape was computationally investigated with the largest set of mAbs so far in the literature. From the 32 studied binders, groups of mAbs were identified from weak to strong binding affinities (e.g. S2K146). These mAbs with strong binding capacity and especially their combination are amenable to experimentation and clinical trials because of their high predicted binding affinities and possible neutralization potential for current known virus mutations and a universal coronavirus.Communicated by Ramaswamy H. Sarma.

Implementation of Quality by Design (QbD) for development of bilayer tablets

Bilayer tablets offer various drug release profiles for individual drugs incorporated in each layer of a bilayer tablet, which is rarely achievable by conventional tablets. These tablets also help avoid physicochemical incompatibilities between drugs and excipients. Successful manufacturing of such more complex dosage forms depends upon screening of material attributes of API and excipients as well as optimization of processing parameters of individual unit operations of the manufacturing process that must be strictly monitored and controlled to obtain an acceptable drug product quality and performance in order to achieve safety and efficacy per regulatory requirements. Optimizing formulation attributes and manufacturing processes during critical stages, such as blending, granulation, pre-compression, and main compression, can help avoid problems such as weight variation, segregation, and delamination of individual layers, which are frequently faced during the production of bilayer tablets. The main objective of this review is to establish the basis for the implementation of Quality by Design (QbD) system principles for the design and development of bilayer tablets, encompassing the preliminary and systematic risk assessment of critical material attributes (CMAs) and critical process parameters (CPPs) with respect to in-process and finished product critical quality attributes (CQAs). Moreover, the applicability of the QbD methodology based on its purpose is discussed and complemented with examples of bilayer tablet technology.

Advancing non-destructive analysis of 3D printed medicines

Pharmaceutical 3D printing (3DP) has attracted significant interest over the past decade for its ability to produce personalised medicines on demand. However, current quality control (QC) requirements for traditional large-scale pharmaceutical manufacturing are irreconcilable with the production offered by 3DP. The US Food and Drug Administration (FDA) and the UK Medicines and Healthcare Products Regulatory Agency (MHRA) have recently published documents supporting the implementation of 3DP for point-of-care (PoC) manufacturing along with regulatory hurdles. The importance of process analytical technology (PAT) and non-destructive analytical tools in translating pharmaceutical 3DP has experienced a surge in recognition. This review seeks to highlight the most recent research on non-destructive pharmaceutical 3DP analysis, while also proposing plausible QC systems that complement the pharmaceutical 3DP workflow. In closing, outstanding challenges in integrating these analytical tools into pharmaceutical 3DP workflows are discussed.

Techno-economic analysis of dynamic, end-to-end optimal pharmaceutical campaign manufacturing using PharmaPy

Increased interest in the pharmaceutical industry to transition from batch to continuouos manufacturing motivates the use of digital frameworks that allow systematic comparison of candidate process configurations. This paper evaluates the technical and economic feasibility of different end-to-end optimal process configurations, viz. batch, hybrid and continuous, for small-scale manufacturing of an active pharmaceutical ingredient. Production campaigns were analyzed for those configurations containing continuous equipment, where significant start-up effects are expected given the relatively short campaign times considered. Hybrid operating mode was found to be the most attractive process configuration at intermediate and large annual production targets, which stems from combining continuous reactors and semi-batch vaporization equipment. Continuous operation was found to be more costly, due to long stabilization times of continuous crystallization, and thermodynamic limitations of flash vaporization. Our work reveals the benefits of systematic digital evaluation of process configurations that operate under feasible conditions and compliant product quality attributes.

Association of burnout with depression in pharmacists: A network analysis

Background

Burnout and depression have overlapping symptoms, but the extent of overlap remains unclear, and the complex relationship between burnout and depression in pharmacists is rarely explored.

Methods

We investigated burnout and depression in 1,322 frontline pharmacists, and explored the complex relationship between burnout and depression in those pharmacists using network analysis.

Results

Network analysis showed that there were 5 communities. A partial overlap was found between burnout and depressive symptoms in pharmacists. The nodes MBI-6 (I have become more callous toward work since I took this job), D18 (My life is meaningless), and D10 (I get tired for no reason) had the highest expected influence value. D1 (I feel down-hearted and blue) and D14 (I have no hope for the future) were bridge symptoms connected with emotional exhaustion and reduced professional efficacy, respectively.

Conclusion

A partial overlap exists between burnout and depressive symptoms in pharmacists, mainly in the connection between the emotional exhaustion and reduced professional efficacy and the depressive symptoms. Potential core targets identified in this study may inform future prevention and intervention.

UV-visible absorption spectroscopy for in-line API concentration measurement in nanoparticle production process using controlled expansion of supercritical solutions (CESS®)

Most new small drug molecules in pharmaceutical development require improvement of solubility. The controlled expansion of supercritical solutions (CESS®) process is a nanoparticle production technology, dedicated to enhancing the dissolution rate of active pharmaceutical ingredients (APIs) suffering from poor solubility and enabling novel drug delivery opportunities. In this process, the API is dissolved in supercritical carbon dioxide (scCO₂) and nanoparticles are formed through controlled pressure reduction. To improve process visibility and control, ultraviolet-visible (UV-Vis) spectroscopy was incorporated into CESS® process as a process analytical technology (PAT) tool. The tool quantifies the amount of API dissolved in scCO₂ during the solubilization phase of the process. Sample interfacing of the UV-Vis spectrometer was done with a custom-made pressure and temperature rated transmission flow-through cell. In-process calibration was developed to correlate the UV-Vis absorption spectra to the API concentration. Due to the density-dependent molar absorption coefficient of API in scCO₂, the calibration was done for each combination of temperature and pressure. The developed PAT tool provides insight into the process enabling real-time API quantity estimation. It also facilitates process development through Quality by Design (QbD) and offers a system for enhanced process control and troubleshooting. For instance, the in-line API concentration data allows one to study the solubilization behavior of the API in the process and to optimize the process parameters in order to maximize throughput.

Quality-by-control of intensified continuous filtration-drying of active pharmaceutical ingredients

Continuous manufacturing and closed-loop quality control are emerging technologies that are pivotal for next-generation pharmaceutical modernization. We develop a process control framework for a continuous carousel for integrated filtration-drying of crystallization slurries. The proposed control system includes model-based monitoring and control routines, such as state estimation and real-time optimization, implemented in a hierarchical, three-layer quality-by-control (QbC) framework. We implement the control system in ContCarSim, a publicly available carousel simulator. We benchmark the proposed control system against simpler methods, comprising a reduced subset of the elements of the overall control system, and against open-loop operation (the current standard in pharmaceutical manufacturing). The proposed control system demonstrates superior performance in terms of higher consistency in product quality and increased productivity, proving the benefits of closed-loop control and of model-based techniques in pharmaceutical manufacturing. This study represents a step forward toward end-to-end continuous pharmaceutical processing, and in the evolution of quality-by-design toward quality-by-control.

Quality by Design (QbD) Approach in Marketing Authorization Procedures of Non-Biological Complex Drugs: A Critical Evaluation

The emergence of innovator-driven complex drug products, such as Non-Biological Complex Drugs (NBCDs), has provided disruptive advances in the Nanotechnology and Biotechnology fields. However, the design and development of NBCDs can be particularly challenging due to some unresolved scientific and regulatory challenges associated with the pharmaceutical quality assessment. The application of a more holistic, systematic, integrated science and risk-based approach, such as Quality by Design (QbD), is essential to address key scientific, technological, and regulatory constraints in the research and development of the NBCDs. The deeper product and process understanding derived from the implementation of the QbD approach ensures consistent, reliable, and high-quality pharmaceutical products. Furthermore, this approach promotes innovation and continuous improvement in the entire product lifecycle. Regulatory authorities highly recommend QbD-based submissions to successfully translate NBCDs from laboratory-scale research to the pharmaceutical market with the required quality, safety, and efficacy standards. The main aim of this article is to obtain a comprehensive and in-depth investigation into the state of implementation of the QbD approach in the pharmaceutical development and marketing authorization of NBCDs in Europe and the United States, through the analysis of the available data from their regulatory dossiers. In addition, it aims to understand and discuss how the QbD approach is used and implemented for complex drug products in the pharmaceutical industry, highlighting the gaps and challenges involved with its implementation. An analysis is held regarding QbD's advantages in terms of knowledge growth, regulatory flexibility, and the speed of development based on big data science, along with the reduction of regulatory failures and market withdrawals.