Advancing pharmaceutical quality: An overview of science and research in the U.S. FDA's Office of Pharmaceutical Quality

Statistical data treatment for residence time distribution studies in pharmaceutical manufacturing

Residence time distribution (RTD) method has been widely used in the pharmaceutical manufacturing for understanding powder dynamics within unit operations and continuous integrated manufacturing lines. The dynamics thus captured is then used to develop predictive models for unit operations and important RTD-based applications ensuring product quality assurance. Despite thorough efforts in tracer selection, data acquisition, and calibration model development to obtain tracer concentration profiles for RTD studies, there can exist significant noise in these profiles. This noise can make it challenging to identify the underlying signal and get a representative RTD of the system under study. Such concerns have previously indicated the importance of noise handling for RTD measurements in literature. However, the literature does not provide sufficient information on noise handling or data treatment strategies for RTD studies. To this end, we investigate the impact of varying levels of noise using different tracers on measurement of RTD profile and its applications. We quantify the impact of different denoising methods (time and frequency averaging methods). Through this investigation, we see that Savitsky Golay filtering turns out to a good method for denoising RTD profiles despite varying noise levels. The investigation is performed such that the key features of the RTD profile (which are important for RTD based applications) are preserved. Subsequently, we also investigate the impact of denoising on RTD-based applications such as out-of-specification (OOS) analysis and RTD modeling. The results show that the degree of noise levels considered in this work do not significantly impact the RTD-based applications.

Lubricant Sensitivity of Direct Compression Grades of Lactose in Continuous and Batch Tableting Process

Modern pharmaceutical manufacturing based on Quality by Design and digitalisation is revolutionising the pharmaceutical industry. Continuous processes are promoted as they increase efficiency and improve quality control. Compared to batch blending, continuous blending is easier to scale and provides advantages for achieving blend homogeneity. One potential challenge of continuous blending is the risk of over-lubrication. In this study, blending homogeneity and lubricant sensitivity are investigated for both batch and continuous processes. Given their distinct chemical structures and morphologies, anhydrous lactose and granulated lactose are expected to exhibit varying sensitivities to changes in process settings across both technologies. The findings suggest that both lactose grades provide highly stable blends that can be safely utilised in both batch and continuous modes. Optimisation should focus on process variables, such as the quality of loss-in-weight feeders used for dosing low doses of ingredients. The most significant process parameter for lubricant sensitivity was the type of lactose used. Anhydrous lactose produced harder tablets than the more porous granulated lactose but was more sensitive to lubrication at the same settings. The magnesium stearate content and its interaction with the type of lactose are also critical factors, with magnesium stearate having a counterproductive impact on tabletability.

"Lab of the Future"─Today: Fully Automated System for High-Throughput Mass Spectrometry Analysis of Biotherapeutics

Here we describe a state-of-the-art, integrated, multi-instrument automated system designed to execute methods involved in mass spectrometry characterization of biotherapeutics. The system includes liquid and microplate handling robotics and utilities, integrated LC-MS, along with data analysis software, to perform sample purification, preparation, and analysis as a seamless integrated unit. The automated process begins with tip-based purification of target proteins from expression cell-line supernatants, which is initiated once the samples are loaded onto the automated system and the metadata are retrieved from our corporate data aggregation system. Subsequently, the purified protein samples are prepared for MS, including deglycosylation and reduction steps for intact and reduced mass analysis, and proteolytic digestions, desalting, and buffer exchange via centrifugation for peptide map analysis. The prepared samples are then loaded into the LC-MS instrumentation for data acquisition. The acquired raw data are initially stored on a local area network storage system that is monitored by watcher scripts that then upload the raw MS data to a network of cloud-based servers. The raw MS data are processed with the appropriately configured analysis workflows such as database search for peptide mapping or charge deconvolution for undigested proteins. The results are verified and formatted for expert curation directly in the cloud. Finally, the curated results are appended to sample metadata in the corporate data aggregation system to accompany the biotherapeutic cell lines in subsequent processes.

Rapid Characterization of Antibodies via Automated Flow Injection Coupled with Online Microdroplet Reactions and Native-pH Mass Spectrometry

Microdroplet reactions have aroused much interest due to significant reaction acceleration (e.g., ultrafast protein digestion in microdroplets could occur in less than 1 ms). This study integrated a microdroplet protein digestion technique with automated sample flow injection and online mass spectrometry (MS) analysis, to develop a rapid and robust method for structural characterization of monoclonal antibodies (mAbs) that is essential to assess the antibody drug's safety and quality. Automated sequential aspiration and mixing of an antibody and an enzyme (IdeS or IgdE) enabled rapid analysis with high reproducibility (total analysis time: 2 min per sample; reproducibility: ∼2% coefficient of variation). Spraying the sample in ammonium acetate buffer (pH 7) using a jet stream source allowed efficient digestion of antibodies and efficient ionization of resulting antibody subunits under native-pH conditions. Importantly, it also provided a platform to directly study specific binding of an antibody and an antigen (e.g., detecting the complexes mAb/RSFV antigen and F(ab')2/RSVF in this study). Furthermore, subsequent tandem MS analysis of a resulting subunit from microdroplet digestion enabled localizing post-translational modifications on particular domains of a mAb in a rapid fashion. In combination with IdeS digestion of an antibody, additional tris(2-carboxyethyl)phosphine (TCEP) reduction and N-glycosidase F (PNGase F) deglycosylation reactions that facilitate antibody analysis could be realized in "one-pot" spraying. Interestingly, increased deglycosylation yield in microdroplets was found, simply by raising the sample temperature. We expect that our method would have a high impact for rapid characterization of monoclonal antibodies.

Product Quality Research for Developing and Assessing Regulatory Submissions for Generic Cyclosporine Ophthalmic Emulsions

Approval of the first generic 0.05% cyclosporine ophthalmic emulsion (COE) in the U.S. represents a milestone achievement of the science and research program in the U.S. Food and Drug Administration's Center for Drug Evaluation and Research (CDER). COE is a locally acting complex drug product indicated to increase tear production in patients whose production is presumed to be suppressed due to ocular inflammation associated with keratoconjunctivitis sicca. The path to approval required overcoming numerous scientific challenges to determining therapeutic equivalence to the reference listed drug. Researchers in CDER's Office of Pharmaceutical Quality and Office of Generic Drugs developed a quality by design approach to understand the effects of process and formulation variables on the product's critical quality attributes, including globule size distribution (GSD), turbidity, viscosity, zeta potential, surface tension, and osmolality. CDER researchers explored multiple techniques to perform physicochemical characterization and analyze the GSD including laser diffraction, nanoparticle tracking analysis, cryogenic transmission electron microscopy, dynamic light scattering, asymmetric field flow fractionation, and two-dimensional diffusion ordered spectroscopy nuclear magnetic resonance. Biphasic models to study drug transfer kinetics demonstrated that COEs with qualitative and quantitative sameness and comparable GSDs, analyzed using earth mover's distance, can be therapeutic equivalents. This body of research facilitated the review and approval of the first U.S. generic COE. In addition, the methods and fundamental understanding developed from this research may support the development and assessment of other complex generics. The approval of a generic COE should improve the availability of this complex drug product to U.S. patients.

Benchmarking the Quality Practices of Global Pharmaceutical Manufacturing to Advance Supply Chain Resilience

Over the past several decades, pharmaceutical manufacturing has become increasingly global and supply chains have become longer, more complex, and fragmented. While pharmaceutical products available to patients and customers typically conform with appropriate standards, supply chains are often affected by disruptive events and shocks that impact public health. One approach to assuring the availability of quality pharmaceutical products is to encourage drug manufacturers to invest in quality management maturity (QMM) and promote continual improvement. The interests of patients are served by risk-based drug shortage prevention and mitigation activities that help to proactively manage supply chain complexities and ensure availability of drugs. This paper demonstrates that adherence to certain quality practices enables improved manufacturing performance. Prior research has identified quality practices that are correlated with manufacturing performance. To better understand how these quality practices can be characterized, measured, and analyzed, this research project conducted a voluntary global study of pharmaceutical manufacturing establishments. Over 200 global pharmaceutical manufacturing establishments participated in this Quality Benchmarking Study (QBS) and provided data on manufacturing performance and self-assessments of adherence to quality practices. The analysis of these data found that the implementation level for selected quality management practices correlates positively with certain Key Performance Indicators (KPIs). More specifically, we found a significant positive correlation between (i) Delivery Performance and (ii) Application of QMM principles associated with Technical Production.

Ultrasensitive disulfide scrambling analysis of mAbs by LC-MS with post-column reduction and glycine signal enhancement

Explicitly confirming the complete disulfide bond linkage pattern of a monoclonal antibody (mAb) presents a challenge in the biopharmaceutical industry. Although proper native disulfide connections are in high abundance for analytical purposes within a peptide mapping digest under non-reducing conditions, disulfide scrambling can also exist but be difficult to detect, let alone characterize, particularly at low levels. Here, we developed an ultrasensitive high-confidence method for identifying explicit disulfide connectivity in mAbs. By applying a post-column addition of tris (2-carboxyethyl)phosphine hydrochloride (TCEP) to the liquid chromatography (LC) eluent of a non-reduced mAb digest, partial reduction of disulfide peptides is achieved after the initial peptide separation, allowing both the parent disulfide and its reduced daughter peptides to co-elute for simultaneous mass spectrometry (MS) detection. Combining this concept with the recently discovered ability of glycine to enhance MS signal when added to the LC eluent, we demonstrate a method for detecting, characterizing and quantifying low-abundance disulfide scrambling in mAbs.

Interlaboratory Studies Using the NISTmAb to Advance Biopharmaceutical Structural Analytics

Biopharmaceuticals such as monoclonal antibodies are required to be rigorously characterized using a wide range of analytical methods. Various material properties must be characterized and well controlled to assure that clinically relevant features and critical quality attributes are maintained. A thorough understanding of analytical method performance metrics, particularly emerging methods designed to address measurement gaps, is required to assure methods are appropriate for their intended use in assuring drug safety, stability, and functional activity. To this end, a series of interlaboratory studies have been conducted using NISTmAb, a biopharmaceutical-representative and publicly available monoclonal antibody test material, to report on state-of-the-art method performance, harmonize best practices, and inform on potential gaps in the analytical measurement infrastructure. Reported here is a summary of the study designs, results, and future perspectives revealed from these interlaboratory studies which focused on primary structure, post-translational modifications, and higher order structure measurements currently employed during biopharmaceutical development.

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

Recently, the pharmaceutical industry has been facing several challenges associated to the use of outdated development and manufacturing technologies. The return on investment on research and development has been shrinking, and, at the same time, an alarming number of shortages and recalls for quality concerns has been registered. The pharmaceutical industry has been responding to these issues through a technological modernization of development and manufacturing, under the support of initiatives and activities such as quality-by-design (QbD), process analytical technology, and pharmaceutical emerging technology. In this review, we analyze this modernization trend, with emphasis on the role that mathematical modeling plays within it. We begin by outlining the main socio-economic trends of the pharmaceutical industry, and by highlighting the life-cycle stages of a pharmaceutical product in which technological modernization can help both achieve consistently high product quality and increase return on investment. Then, we review the historical evolution of the pharmaceutical regulatory framework, and we discuss the current state of implementation and future trends of QbD. The pharmaceutical emerging technology is reviewed afterwards, and a discussion on the evolution of QbD into the more effective quality-by-control (QbC) paradigm is presented. Further, we illustrate how mathematical modeling can support the implementation of QbD and QbC across all stages of the pharmaceutical life-cycle. In this respect, we review academic and industrial applications demonstrating the impact of mathematical modeling on three key activities within pharmaceutical development and manufacturing, namely design space description, process monitoring, and active process control. Finally, we discuss some future research opportunities on the use of mathematical modeling in industrial pharmaceutical environments.

Big data collection in pharmaceutical manufacturing and its use forproduct quality predictions

Advances in data science and digitalization are transforming the world, and the pharmaceutical industry is no exception. Multiple sensor-equipped manufacturing processes and laboratory analysis are the main sources of primary data, which have been utilized for the presented dataset of 1005 actual production batches of selected medicine. This dataset includes incoming raw material quality results, compression process time series and final product quality results for the selected product. The data is highly valuable for it provides an insight into every 10 seconds of the process trajectory for 1005 actual production batches along with product quality collected over several years. It therefore offers an opportunity to develop advanced analysis models and procedures which would lead to the omission of current conventional and time consuming laboratory testing. Benefits for both the industry and patient are obvious: reducing product lead times and costs of manufacture.

Measurement(s)	Incoming raw material quality (particle size distribution, water content, impurities level, residual solvents, pH) • In process control measurements of tablet core and film coated tablets (weight, thickness, diameter, hardness, yield of a process) • Final medicine quality on a representative sample of film coated tablets (drug release in defined time, active ingredient content, impurities level, residual solven content) • Process time series of selected tablet compression parameters (every 10 s of the compression process)
Technology Type(s)	Laboratory based analysis (particle sizer using laser diffraction, loss on drying method, HPLC method, GC method) • Automatic IPC check machine (combining balance, hardness, thickness and diameter measurements) • HPLC (High performance liquid chromatography), GC (gas chromatography) • Tablet compression machine calibrated sensors for the following main parameters: main and pre-compression force, fill depth, cylindrycal height, ejection force, number of wasted tablets.
Factor Type(s)	batch • code • strength • size • start • api_code • api_batch • smcc_batch • lactose_batch • starch_batch • api_water • api_total_impurities • api_l_impurity • api_content • api_ps01 • api_ps05 • api_ps09 • lactose_water • lactose_sieve0045 • lactose_sieve015 • lactose_sieve025 • smcc_water • smcc_td • smcc_bd • smcc_ps01 • smcc_ps05 • smcc_ps09 • starch_ph • starch_water • tbl_min_hardness • tbl_max_hardness • tbl_av_hardness • tbl_min_thickness • tbl_max_thickness • fct_min_thickness • fct_max_thickness • tbl_min_weight • tbl_max_weight • tbl_rsd_weight • fct_rsd_weight • fct_min_hardness • fct_max_hardness • fct_av_hardness • tbl_tensile • fct_tensile • tbl_yield • batch_yield • time series: tbl_speed • time series: fom • time series: main_comp • time series: tbl_fill • time series: SREL • time series: pre_comp • time series: produced • time series: waste • time series: cyl_main • time series: cyl_pre • time series: stiffness • time series: ejection
Sample Characteristic - Organism	Selected medicine
Sample Characteristic - Environment	manufacturing process
Sample Characteristic - Location	Pharmaceutical industry

Solid-State Deracemization via Temperature Cycles in Continuous Operation: Model-Based Process Design

Solid-state deracemization via temperature cycles converts a racemic crystal mixture into an enantiopure product by periodic cycling of the temperature in the presence of a racemization catalyst. A continuous counterpart of this conventional batch-operated process is proposed that can be performed in mixed suspension mixed product removal crystallizers (MSMPRCs). More specifically, three different configurations are described to perform periodic forcing via temperature cycles, which differ from each other in the type of the feed and in the withdrawal system. We have developed a model by extending our recent population balance equation model of batch solid-state deracemization via temperature cycles, and we exploit this tool to analyze the start-up and periodic steady-state behavior. Moreover, we compare the performance of the different configurations based on the selected key performance indicators, namely, average periodic steady-state enantiomeric excess and productivity. The process with solution feed yields pure enantiomers, while the solid and suspension-fed process alternatives result in highly enantiomerically enriched crystals. We further design an MSMPRC cascade to overcome this purity limitation. This work discusses guidelines on how to transform the batch process of temperature cycles into a continuous operation, which enables stable, unattended operation and chiral crystal production with consistent product quality.

Using residence time distribution in pharmaceutical solid dose manufacturing - A critical review

While continuous manufacturing (CM) of pharmaceutical solid-based drug products has been shown to be advantageous for improving the product quality and process efficiency in alignment with FDA's support of the quality-by-design paradigm (Lee, 2015; Ierapetritou et al., 2016; Plumb, 2005; Schaber, 2011), it is critical to enable full utilization of CM technology for robust production and commercialization (Schaber, 2011; Byrn, 2015). To do so, an important prerequisite is to obtain a detailed understanding of overall process characteristics to develop cost-effective and accurate predictive models for unit operations and process flowsheets. These models are utilized to predict product quality and maintain desired manufacturing efficiency (Ierapetritou et al., 2016). Residence time distribution (RTD) has been a widely used tool to characterize the extent of mixing in pharmaceutical unit operations (Vanhoorne, 2020; Rogers and Ierapetritou, 2015; Teżyk et al., 2015) and manufacturing lines and develop computationally cheap predictive models. These models developed using RTD have been demonstrated to be crucial for various flowsheet applications (Kruisz, 2017; Martinetz, 2018; Tian, 2021). Though extensively used in the literature (Gao et al., 2012), the implementation, execution, evaluation, and assessment of RTD studies has not been standardized by regulatory agencies and can thus lead to ambiguity regarding their accurate implementation. To address this issue and subsequently prevent unforeseen errors in RTD implementation, the presented article aims to aid in developing standardized guidelines through a detailed review and critical discussion of RTD studies in the pharmaceutical manufacturing literature. The review article is divided into two main sections - 1) determination of RTD including different steps for RTD evaluation including experimental approach, data acquisition and pre-treatment, RTD modeling, and RTD metrics and, 2) applications of RTD for solid dose manufacturing. Critical considerations, pertaining to the limitations of RTDs for solid dose manufacturing, are also examined along with a perspective discussion of future avenues of improvement.

Innate Immunity Modulating Impurities and the Immunotoxicity of Nanobiotechnology-Based Drug Products

Innate immunity can be triggered by the presence of microbial antigens and other contaminants inadvertently introduced during the manufacture and purification of bionanopharmaceutical products. Activation of these innate immune responses, including cytokine secretion, complement, and immune cell activation, can result in unexpected and undesirable host immune responses. These innate modulators can also potentially stimulate the activation of adaptive immune responses, including the formation of anti-drug antibodies which can impact drug effectiveness. To prevent induction of these adverse responses, it is important to detect and quantify levels of these innate immunity modulating impurities (IIMIs) that may be present in drug products. However, while it is universally agreed that removal of IIMIs from drug products is crucial for patient safety and to prevent long-term immunogenicity, there is no single assay capable of directly detecting all potential IIMIs or indirectly quantifying downstream biomarkers. Additionally, there is a lack of agreement as to which of the many analytical assays currently employed should be standardized for general IIMI screening. Herein, we review the available literature to highlight cellular and molecular mechanisms underlying IIMI-mediated inflammation and its relevance to the safety and efficacy of pharmaceutical products. We further discuss methodologies used for direct and indirect IIMI identification and quantification.

Mathematical modeling and digital design of an intensified filtration-washing-drying unit for pharmaceutical continuous manufacturing

This paper introduces a comprehensive mathematical model of a novel integrated filter-dryer carousel system, designed for continuously filtering, washing and drying a slurry stream into a crystals cake. The digital twin includes models for dead-end filtration, cake washing and convective cake drying, based on dynamic multi-component mass, energy and momentum balances. For set of feed conditions and control inputs, the model allows tracking the solvents and impurities content in the cake (critical quality attributes, CQAs) throughout the whole process. The model parameters were identified for the isolation of paracetamol from a multi-component slurry, containing a non-volatile impurity. The calibrated model was used for identifying the probabilistic design space and maximum throughput for the process, expressing the combinations of the carousel feed conditions and control inputs for which the probability of meeting the target CQAs is acceptable.

Prediction of pharmacokinetic parameters of inhaled indacaterol formulation in healthy volunteers using physiologically-based pharmacokinetic (PBPK) model

BACKGROUND

Inhaled formulations are the first choices for treating asthma and chronic obstructive pulmonary disease (COPD), attracting the increasing investment and development in the pharmaceutical industry. Both the equivalence of local and systemic exposures need to be considered when assessing the equivalence of generic inhaled drugs, which has become a dilemma in the development of generic inhaled drugs. There is an urgent need for reliable methods such as physiologically-based pharmacokinetic (PBPK) model to assist in the development of inhaled drugs.

METHOD

To test the strategy that in silico simulation is an effective tool in developing inhaled products and further assessing their clinically feasibility, a long-acting beta2-adrenergic agonists indacaterol, which was referred as the first-line therapy for patient with COPD, was selected as a tool drug. The PBPK model was established and the predicted plasma concentration curve was obtained by inputting the physicochemical properties of indacaterol and adjusting model parameters. The accuracy of simulation was verified by an alignment with the actual data. The main factor affecting PK in vivo was investigated by parameter sensitivity analysis. The biological equivalent size of indacaterol was investigated by virtual bioequivalence analysis.

RESULTS

The models of indacaterol after intravenous and oral administration were established and confirmed, and used as a background for PBPK model of inhaled administration. All those models showed favorable stability and applicability. Appropriate lung deposition was generated in the PBPK model, and the predicted plasma profile of indacaterol was consistent with the clinical actual observation values. Particle size is the most important factor affecting the PK of indacaterol in vivo. Furthermore, virtual bioequivalence simulation exhibited statistically comparable results between the particle size fluctuates in the range of 3.5-6.5 μm and baseline levels (D90 = 5 μm).

CONCLUSIONS

The PBPK model can simulate the pharmacokinetics and lung deposition of indacaterol, which will be a powerful tool to assist the development of inhaled drugs.

NMR Spectroscopy for Protein Higher Order Structure Similarity Assessment in Formulated Drug Products

Peptide and protein drug molecules fold into higher order structures (HOS) in formulation and these folded structures are often critical for drug efficacy and safety. Generic or biosimilar drug products (DPs) need to show similar HOS to the reference product. The solution NMR spectroscopy is a non-invasive, chemically and structurally specific analytical method that is ideal for characterizing protein therapeutics in formulation. However, only limited NMR studies have been performed directly on marketed DPs and questions remain on how to quantitively define similarity. Here, NMR spectra were collected on marketed peptide and protein DPs, including calcitonin-salmon, liraglutide, teriparatide, exenatide, insulin glargine and rituximab. The 1D ¹H spectral pattern readily revealed protein HOS heterogeneity, exchange and oligomerization in the different formulations. Principal component analysis (PCA) applied to two rituximab DPs showed consistent results with the previously demonstrated similarity metrics of Mahalanobis distance (D_M) of 3.3. The 2D ¹H-¹³C HSQC spectral comparison of insulin glargine DPs provided similarity metrics for chemical shift difference (Δδ) and methyl peak profile, i.e., 4 ppb for ¹H, 15 ppb for ¹³C and 98% peaks with equivalent peak height. Finally, 2D ¹H-¹⁵N sofast HMQC was demonstrated as a sensitive method for comparison of small protein HOS. The application of NMR procedures and chemometric analysis on therapeutic proteins offer quantitative similarity assessments of DPs with practically achievable similarity metrics.

Powder composition monitoring in continuous pharmaceutical solid-dosage form manufacturing using state estimation - Proof of concept

In continuous solid-dosage form manufacturing, the powder feeding system is responsible for supplying downstream the correct formulation of the drug product ingredients. The composition of the powder delivered by the feeding system is inferred from the measurements of powder mass flow from the system feeders. The mass flows are, in turn, inferred from the loss in weight measured in the feeder hoppers. Most loss-in-weight feeders post-process the mass flow signal to deliver a smoothed value to the user. However, such estimated mass flows can exhibit a low signal-to-noise ratio. As the feeders are critical elements of the control strategy of the manufacturing line, better instantaneous estimates of mass flow are desirable for improving the quality assurance. In this study, we propose a model-based approach for monitoring the composition of the powder fed to a continuous solid-dosage line. The monitoring system is based on a moving-horizon state estimator, which carries out model-based reconciliation of the feeder mass measurements, thus enabling accurate composition estimation of the powder mixture. Experimental datasets from a direct compression line are used to validate the methodology. Results demonstrate improvement with respect to current industrial solutions.

Hybrid multi-zonal compartment modeling for continuous powder blending processes

To modernize drug manufacturing, the pharmaceutical industry has been moving towards implementing emerging technologies to enhance manufacturing robustness and process reliability for production of regulation compliant drug products. Although different science and risk based technologies, like Quality-by-Design, have been used to illustrate their potential, there still exist some underlying obstacles. Specifically, for the production of oral solid drug products, an in-depth process understanding, and predictive modeling of powder mixing in continuous powder blenders is one such major obstacle and originates from the current limitations of the experimental and modeling approaches. Though first principle based discrete element modeling (DEM) approach can address the above issues, it can get very computationally intensive which limits its applications for predictive modeling. In the proposed work, we aim to address this limitation using a multi-zonal compartment modeling approach, which is constructed from DEM. The approach provides a computationally efficient and mechanistically informed hybrid model. The application of the proposed approach is first demonstrated for a periodic section of the blender, followed by its extension for the entire continuous powder blender and the obtained model predictions are validated. The proposed approach provides an overall assessment of powder mixing along axial and radial directions, which is an important requirement for the quantification of blend uniformity. Given the low computational cost, the developed model can further be integrated within the predictive flowsheet model of the manufacturing line.

Evaluation of strategies for overcoming trifluoroacetic acid ionization suppression resulted in single-column intact level, middle-up, and bottom-up reversed-phase LC-MS analyses of antibody biopharmaceuticals

A wide range of strategies for efficient chromatography and high MS sensitivity in reversed-phase LC-MS analysis of antibody biopharmaceuticals and their large derivates has been evaluated. They included replacing trifluoroacetic acid with alternative acidifiers, relevancy of elevated column temperature, use of dedicated stationary phases, and counteraction of the suppression effect of trifluoroacetic acid in electrospray ionization. At the column temperature of 60 °C, which significantly reduces in-column protein degradation, the BioResolve RP mAb Polyphenyl, BioShell IgG C₄ columns performed best using mobile phases with full or partial replacement of trifluoroacetic acid with difluoroacetic acid in the analysis of intact antibodies. Similarly, 0.03% trifluoroacetic acid in combination with 0.07% formic acid is a good alternative in analyzing antibody chains at 60 °C. Collectively, the addition of 3% 1-butanol to the mobile phase acidified with 0.1% formic acid was the most efficient approach to simultaneously achieving good chromatographic separation and MS sensitivity for intact and reduced antibody biopharmaceuticals. Moreover, this mobile phase combined with the BioResolve RP mAb Polyphenyl column was subsequently demonstrated to provide excellent results for peptide mapping of antibody biopharmaceuticals fully comparable with those obtained using a state-of-the-art column for peptide separation, thus opening an avenue for a single-column multilevel analysis of these biotherapeutics.

Microdroplet Ultrafast Reactions Speed Antibody Characterization

Recently, microdroplet reactions have aroused much interest because the microdroplet provides a unique medium where organic reactions could be accelerated by a factor of 10³ or more. However, microdroplet reactions of proteins have been rarely studied. We report the occurrence of multiple-step reactions of a large protein, specifically, the digestion, reduction, and deglycosylation of an intact antibody, which can take place in microseconds with high reaction yields in aqueous microdroplets at room temperature. As a result, fast structural characterization of a monoclonal antibody, essential for assessing its quality as a therapeutic drug, can be enabled. We found that the IgG1 antibody can be digested completely by the IdeS protease in aqueous microdroplets in 250 microseconds, a 7.5 million-fold improvement in speed in comparison to traditional digestion in bulk solution (>30 min). Strikingly, inclusion of the reductant tris(2-carboxyethyl)phosphine in the spray solution caused simultaneous antibody digestion and disulfide bond reduction. Digested and reduced antibody fragments were either collected or analyzed online by mass spectrometry. Further addition of PNGase F glycosylase into the spray solution led to antibody deglycosylation, thereby producing reduced and deglycosylated fragments of analytical importance. In addition, glycated fragments of IgG1 derived from glucose modification were identified rapidly with this ultrafast digestion/reduction technique. We suggest that microdroplets can serve as powerful microreactors for both exploring large-molecule reactions and speeding their structural analyses.

FTIR combined with chemometric tools (fingerprinting spectroscopy) in comparison to HPLC: which strategy offers more opportunities as a green analytical chemistry technique for pharmaceutical analysis

Fourier transform infrared spectroscopy (FTIR) is a widespread technique that can provide a chemical signature (fingerprints) of solid, liquid, or gas samples with a wide range of analytical applications. High-performance liquid chromatography (HPLC) is a leading analytical strategy for pharmaceutical analysis. Here we present a side-by-side comparison of the potential of these techniques for quantitative analysis of pharmaceutical active ingredient combinations in light of green analytical chemistry (GAC) principles. The methods were successfully applied for the analysis of ketoprofen (KTP)/hyoscine (HYS) and benzocaine (BENZ)/dextromethorphan HBr (DEX) in their binary mixtures and pharmaceutical preparations. In FTIR analysis, calibration models were constructed based on partial least squares regression (PLSR) with satisfactory regression coefficients (r2) of 0.9998, 0.9994, 0.9855, and 0.9895 for KTP, HYS, DEX, and BENZ, respectively, over a wide linearity range (10-100, 10-100, 5-75, and 10-100 μg mL-1) that covers the concentration ratios in the market samples. External validation using a validation set and internal validation using leave-one-out-cross-validation calculations were performed, and small root-mean-square-error-of-cross-validation (RMSECV) values were obtained indicating the good resolving power of the models. The same performance was obtained using the HPLC method for separation of the same mixtures with r2 equal to 0.9998, 0.9999, 0.9998, and 0.9998 over linear ranges of 50-1000, 10-200, 5-100, and 5-100 μg mL-1 for KTP, HYS, DEX, and BENZ, respectively. The HPLC methods were validated following ICH guidelines with good recovery percentages in the range of 98-100%. The statistical comparison of the FTIR and HPLC methods for analysis showed almost the same results with good applicability towards commercial dosage forms. Concerning the twelve GAC principles, a detailed comparison was performed to highlight the opportunities of each technique. FTIR-PLSR analysis showed superior performance as it allows for less solvent consumption, portability, less generated waste, short operating time, less operation cost, less energy consumption, and more operator safety and it is easily coupled with chemometric tools. Besides, FTIR is a direct analytical technique that can be used for the analysis of samples in all the physical forms (solid, liquid, and gas) without modifications.

An Overview of Drug Substance Manufacturing Processes

To develop a comprehensive understanding of pharmaceutical drug substance manufacturing (DSM) processes, we conducted a data mining study to examine 50 new drug applications (NDAs) approved in 2010-2016. We analyzed the prevalence of several frequently deployed in-process control (IPC) techniques and postreaction workup procedures, as well as the operational conditions specified for reactions and workups. Our findings show that crystallization and high-performance liquid chromatography (HPLC) were the most commonly used workup steps and in-process controls, respectively, in drug substance manufacturing. On average, each NDA implemented 12.6 in-process controls and 11.3 workups. Operation time for reactions and workup procedures varied from a few minutes to multiple days, though 61% of these were between 1 and 10 h.

High Performance Size Exclusion Chromatography and High-Throughput Dynamic Light Scattering as Orthogonal Methods to Screen for Aggregation and Stability of Monoclonal Antibody Drug Products

The presence of aggregates in monoclonal antibody (mAb) drug product (DP) formulations can present product quality challenges. Here we show that use of High Performance Size Exclusion Chromatography (HP-SEC), in conjunction with high-throughput dynamic light scattering (HT-DLS) analyses of mAb DPs can be a useful strategy to determine monomer content and the presence of aggregates under simulated stress conditions. This analytical approach was used to evaluate four commercially available mAb DPs under different conditions i.e.; original formulations, diluted, and thermo-mechanical stressed condition. Due to particle size limitations of HP-SEC columns, resulting in particles accumulating in the column frits prior to reaching the detector for analysis, there is a possibility that large mAb aggregates may not be detected. Both HP-SEC and HT-DLS were able to detect and resolve the mAb monomer (~10-12 nm) of the DPs in their recommended storage conditions. However, the ability to detect large aggregates (>40 nm) by both analytical methods differed, and HT-DLS was able to detect aggregates between 60 nm and 1400 nm under stress conditions. Our data indicates that HP-SEC, in conjunction with HT-DLS, may be beneficial to detect both mAb DP monomer content and multiple aggregate species (1-1000 nm) in the submicron size range.

Quality Testing of Difficult-to-Make Prescription Pharmaceutical Products Marketed in the US

IMPORTANCE

Health care practitioners and patients must have information to support their confidence in the quality of prescription pharmaceuticals.

OBJECTIVE

To determine whether there were clear and substantive differences in major quality attributes between difficult-to-make solid oral dosage form pharmaceutical products marketed in the US.

DESIGN, SETTING, AND PARTICIPANTS

This quality improvement study analyzed US Food and Drug Administration-collected samples of 252 drug products marketed in the US and manufactured in the US, Canada, Europe, India, and the rest of Asia. These drug products were immediate-release solid oral dosage forms considered difficult to make on the basis of product quality history. This sampling included 35 innovator and 217 generic drug samples manufactured by 46 different firms containing 17 different active ingredients. Statistical analysis was performed from February to November 2019.

MAIN OUTCOMES AND MEASURES

All products were tested within their shelf life on the basis of the legally recognized tests of the US Pharmacopeia for the major quality attributes of dosage unit uniformity and dissolution. These tests measure dosage consistency and drug release, respectively. The consistency of either attribute was used to calculate a process performance index to describe the variability in manufacturing.

RESULTS

All 252 drug product samples met the US market standards for dosage unit uniformity and dissolution, although the process performance index (Ppk) for dissolution fell below the level of 4-sigma capability (ie, <1 error per 1600) for 11 different manufacturers and for generics in 4 of 5 regions, including the US. As part of a retrospective analysis, manufacturers performing above the median Ppk for either dissolution or dosage unit uniformity submitted fewer product quality defect reports (mean field alert reports of 0.22 and 0.63, respectively) than those falling at or below the median Ppk for these attributes (mean field alert reports of 2.1 and 1.7, respectively).

CONCLUSIONS AND RELEVANCE

All samples met the US market standards for dosage unit uniformity and dissolution, indicating acceptability for use by patients regardless of manufacturer or region. To our knowledge, this is the largest sampling study of pharmaceutical manufacturers for the US market and these data provide objective insight into the quality of prescription drugs with high manufacturing risks.

Detection of Beta-Glucan Contamination in Nanotechnology-Based Formulations

Understanding the potential contamination of pharmaceutical products with innate immunity modulating impurities (IIMIs) is essential for establishing their safety profiles. IIMIs are a large family of molecules with diverse compositions and structures that contribute to the immune-mediated adverse effects (IMAE) of drug products. Pyrogenicity (the ability to induce fever) and activation of innate immune responses underlying both acute toxicities (e.g., anaphylactoid reactions or pseudoallergy, cytokine storm) and long-term effects (e.g., immunogenicity) are among the IMAE commonly related to IIMI contamination. Endotoxins of gram-negative bacteria are the best-studied IIMIs in that both methodologies for and pitfalls in their detection and quantification are well established. Additionally, regulatory guidance documents and research papers from laboratories worldwide are available on endotoxins. However, less information is currently known about other IIMIs. Herein, we focus on one such IIMI, namely, beta-glucans, and review literature and discuss the experience of the Nanotechnology Characterization Lab (NCL) with the detection of beta-glucans in nanotechnology-based drug products.

Characterization and Control of Dynamic Rearrangement in a Self-Assembled Antibody Carrier

Thorough characterization of protein assemblies is required for the control of structure and robust performance in any given application, especially for the safety and stability of protein therapeutics. Here, we report the use of multiple, orthogonal characterization techniques to enable control over the structure of a multivalent antibody carrier for future use in drug delivery applications. The carrier, known as Hex, contains six antibody binding domains that bind the Fc region of antibodies. Using size exclusion chromatography, analytical ultracentrifugation, and dynamic light scattering, we identified the stoichiometry of assembled Hex-antibody complexes and observed changes in the stoichiometry of nanocarriers when incubated at higher temperatures over time. The characterization data informed the modification of Hex to achieve tighter control over the protein assembly structure for future therapeutic applications. This work demonstrates the importance of using orthogonal characterization techniques and observing protein assembly in different conditions over time to fully understand and control structure and dynamics.

Continuous Manufacturing in Pharmaceutical Process Development and Manufacturing

The pharmaceutical industry has found new applications for the use of continuous processing for the manufacture of new therapies currently in development. The transformation has been encouraged by regulatory bodies as well as driven by cost reduction, decreased development cycles, access to new chemistries not practical in batch, improved safety, flexible manufacturing platforms, and improved product quality assurance. The transformation from batch to continuous manufacturing processing is the focus of this review. The review is limited to small, chemically synthesized organic molecules and encompasses the manufacture of both active pharmaceutical ingredients (APIs) and the subsequent drug product. Continuous drug product is currently used in approved processes. A few examples of production of APIs under current good manufacturing practice conditions using continuous processing steps have been published in the past five years, but they are lagging behind continuous drug product with respect to regulatory filings.

Economic Analysis of Batch and Continuous Biopharmaceutical Antibody Production: A Review

PURPOSE

There is a growing interest in continuous biopharmaceutical processing due to the advantages of small footprint, increased productivity, consistent product quality, high process flexibility and robustness, facility cost-effectiveness, and reduced capital and operating cost. To support the decision making of biopharmaceutical manufacturing, comparisons between conventional batch and continuous processing are provided.

METHODS

Various process unit operations in different operating modes are summarized. Software implementation, as well as computational methods used, are analyzed pointing to the advantages and disadvantages that have been highlighted in the literature. Economic analysis methods and their applications in different parts of the processes are also discussed with examples from publications in the last decade.

RESULTS

The results of the comparison between batch and continuous process operation alternatives are discussed. Possible improvements in process design and analysis are recommended. The methods used here do not reflect Lilly's cost structures or economic evaluation methods.

CONCLUSION

This paper provides a review of the work that has been published in the literature on computational process design and economic analysis methods on continuous biopharmaceutical antibody production and its comparison with a conventional batch process.

Enabling adoption of 2D-NMR for the higher order structure assessment of monoclonal antibody therapeutics

The increased interest in using monoclonal antibodies (mAbs) as a platform for biopharmaceuticals has led to the need for new analytical techniques that can precisely assess physicochemical properties of these large and very complex drugs for the purpose of correctly identifying quality attributes (QA). One QA, higher order structure (HOS), is unique to biopharmaceuticals and essential for establishing consistency in biopharmaceutical manufacturing, detecting process-related variations from manufacturing changes and establishing comparability between biologic products. To address this measurement challenge, two-dimensional nuclear magnetic resonance spectroscopy (2D-NMR) methods were introduced that allow for the precise atomic-level comparison of the HOS between two proteins, including mAbs. Here, an inter-laboratory comparison involving 26 industrial, government and academic laboratories worldwide was performed as a benchmark using the NISTmAb, from the National Institute of Standards and Technology (NIST), to facilitate the translation of the 2D-NMR method into routine use for biopharmaceutical product development. Two-dimensional ¹H,¹⁵N and ¹H,¹³C NMR spectra were acquired with harmonized experimental protocols on the unlabeled Fab domain and a uniformly enriched-¹⁵N, 20%-¹³C-enriched system suitability sample derived from the NISTmAb. Chemometric analyses from over 400 spectral maps acquired on 39 different NMR spectrometers ranging from 500 MHz to 900 MHz demonstrate spectral fingerprints that are fit-for-purpose for the assessment of HOS. The 2D-NMR method is shown to provide the measurement reliability needed to move the technique from an emerging technology to a harmonized, routine measurement that can be generally applied with great confidence to high precision assessments of the HOS of mAb-based biotherapeutics.

An ICP-MS platform for metal content assessment of cell culture media and evaluation of spikes in metal concentration on the quality of an IgG3:κ monoclonal antibody during production

Metal ions can be enzyme cofactors and can directly influence the kinetics of biochemical reactions that also influence the biological production and quality attributes of therapeutic proteins, such as glycan formation and distribution. However, the concentrations of metals in commercially available chemically defined media can range from 1 to 25,000 ppb. Because such concentration changes can impact cell growth, manufacturing yield and product quality the alteration/fluctuation in media composition should be well controlled to maintain product quality. Here, we describe a platform of analytical methods to determine the composition of several metals in different sample matrices using an advanced automated Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). These methods, validated to ICH Q2R1 regulatory validation parameters, were successfully applied to- (a) screen cell culture media; (b) determine changes in the metal concentration during cell growth in spinner flasks, and, (c) determine effect on the glycosylation pattern and homogeneity of an IgG3:κ produced from a murine-hybridoma cell line in bench-top parallel bioreactors due to a spike in copper and iron concentration. Our results show that maintenance of metal content in the cell culture media is critical for product consistency of the IgG3:κ produced.

Translating New Science Into the Drug Review Process: The US FDA's Division of Applied Regulatory Science

In 2011, the US Food and drug Administration (FDA) developed a strategic plan for regulatory science that focuses on developing new tools, standards, and approaches to assess the safety, efficacy, quality, and performance of FDA-regulated products. In line with this, the Division of Applied Regulatory Science was created to move new science into the Center for Drug Evaluation and Research (CDER) review process and close the gap between scientific innovation and drug review. The Division, located in the Office of Clinical Pharmacology, is unique in that it performs mission-critical applied research and review across the translational research spectrum including in vitro and in vivo laboratory research, in silico computational modeling and informatics, and integrated clinical research covering clinical pharmacology, experimental medicine, and postmarket analyses. The Division collaborates with Offices throughout CDER, across the FDA, other government agencies, academia, and industry. The Division is able to rapidly form interdisciplinary teams of pharmacologists, biologists, chemists, computational scientists, and clinicians to respond to challenging regulatory questions for specific review issues and for longer-range projects requiring the development of predictive models, tools, and biomarkers to speed the development and regulatory evaluation of safe and effective drugs. This article reviews the Division's recent work and future directions, highlighting development and validation of biomarkers; novel humanized animal models; translational predictive safety combining in vitro, in silico, and in vivo clinical biomarkers; chemical and biomedical informatics tools for safety predictions; novel approaches to speed the development of complex generic drugs, biosimilars, and antibiotics; and precision medicine.

Application of 2D-NMR with room temperature NMR probes for the assessment of the higher order structure of filgrastim

The higher order structure (HOS) of biotherapeutics is a critical quality attribute that can be evaluated by nuclear magnetic resonance (NMR) spectroscopy at atomic resolution. NMR spectral mapping of HOS can be used to establish HOS consistency of a biologic across manufacturing changes or to compare a biosimilar to an innovator reference product. A previous inter-laboratory study performed using filgrastim drug products demonstrated that two-dimensional (2D)-NMR ¹H^N-¹⁵N^H heteronuclear correlation spectroscopy is a highly robust and precise method for mapping the HOS of biologic drugs at natural abundance using high sensitivity NMR 'cold probes.' Here, the applicability of the 2D-NMR method to fingerprint the HOS of filgrastim products is demonstrated using lower sensitivity, room temperature NMR probes. Combined chemical shift deviation and principal component analysis are used to illustrate the performance and inter-laboratory precision of the 2D-NMR method when implemented on room temperature probes.