Patient-Centric Quality Standards

To ensure the quality, safety and efficacy of medicinal products, it is necessary to develop and execute appropriate manufacturing process and product control strategies. Traditionally, product control strategies have focused on testing known quality attributes with limits derived from levels administered in preclinical and clinical studies with an associated statistical analysis to account for variability. However, not all quality attributes have impact to the patient and those with the potential to impact safety and efficacy may not be significant when dosed at patient-centric levels. Therefore, achieving patient-centricity is understanding patient relevance, which is defined as the level of impact that a quality attribute could have on safety and efficacy within the potential exposure range. A patient-centric quality standard (PCQS) is therefore a set of patient relevant attributes and their associated acceptance ranges to which a drug product should conform within the expected patient exposure range. This manuscript describes historical perspectives details the way to create and leverage a PCQS in a variety of pharmaceutical product modalities.

Re-Envisioning Pharmaceutical Manufacturing: Increasing Agility for Global Patient Access

The traditional paradigm for pharmaceutical manufacturing is focused primarily upon centralized facilities that enable mass production and distribution. While this system reliably maintains high product quality and reproducibility, its rigidity imposes limitations upon new manufacturing innovations that could improve efficiency and support supply chain resiliency. Agile manufacturing methodologies, which leverage flexibility through portability and decentralization, allow manufacturers to respond to patient needs on demand and present a potential solution to enable timely access to critical medicines. Agile approaches are particularly applicable to the production of small-batch, personalized therapies, which must be customized for each individual patient close to the point-of-care. However, despite significant progress in the advancement of agile-enabling technologies across several different industries, there are substantial global regulatory challenges that encumber the adoption of agile manufacturing techniques in the pharmaceutical industry. This review provides an overview of regulatory barriers as well as emerging opportunities to facilitate the use of agile manufacturing for the production of pharmaceutical products. Future-oriented approaches for incorporating agile methodologies within the global regulatory framework are also proposed. Collaboration between regulators and manufacturers to cohesively navigate the regulatory waters is ultimately needed to best serve patients in the rapidly-changing healthcare environment.

Comparing a Statistical Model and Bayesian Approach to Establish the Design Space for the Coating of Ciprofloxacin HCl Beads at Different Scales of Production

The primary objective of this study was to compare two methods for establishing a design space for critical process parameters that affect ethylcellulose film coating of multiparticulate beads and assess this design space validity across manufacturing scales. While there are many factors that can affect film coating, this study will focus on the effects processing conditions have on the quality and extent of film formation, as evaluated by their impact coating yield and drug release. Ciprofloxacin HCl layered beads were utilized as an active substrate core, ethylcellulose aqueous dispersion as a controlled release polymer, and triethyl citrate as a plasticizer. Thirty experiments were conducted using a central composite design to optimize the coating process and map the response surface to build a design space using either statistical least squares or a Bayesian approach. The response surface was fitted using a linear two-factor interaction model with spraying temperature, curing temperature, and curing time as significant model terms. The design spaces established by the two approaches were in close agreement with the statistical least squares approach being more conservative than the Bayesian approach. The design space established for the critical process parameters using small-scale batches was tested using scale-up batches and found to be scale-independent. The robustness of the design space was confirmed across scales and was successfully utilized to establish process signature for the coating process.

A Systematic Approach of Employing Quality by Design Principles: Risk Assessment and Design of Experiments to Demonstrate Process Understanding and Identify the Critical Process Parameters for Coating of the Ethylcellulose Pseudolatex Dispersion Using Non-Conventional Fluid Bed Process

The goal of this study was to utilize risk assessment techniques and statistical design of experiments (DoE) to gain process understanding and to identify critical process parameters for the manufacture of controlled release multiparticulate beads using a novel disk-jet fluid bed technology. The material attributes and process parameters were systematically assessed using the Ishikawa fish bone diagram and failure mode and effect analysis (FMEA) risk assessment methods. The high risk attributes identified by the FMEA analysis were further explored using resolution V fractional factorial design. To gain an understanding of the processing parameters, a resolution V fractional factorial study was conducted. Using knowledge gained from the resolution V study, a resolution IV fractional factorial study was conducted; the purpose of this IV study was to identify the critical process parameters (CPP) that impact the critical quality attributes and understand the influence of these parameters on film formation. For both studies, the microclimate, atomization pressure, inlet air volume, product temperature (during spraying and curing), curing time, and percent solids in the coating solutions were studied. The responses evaluated were percent agglomeration, percent fines, percent yield, bead aspect ratio, median particle size diameter (d50), assay, and drug release rate. Pyrobuttons® were used to record real-time temperature and humidity changes in the fluid bed. The risk assessment methods and process analytical tools helped to understand the novel disk-jet technology and to systematically develop models of the coating process parameters like process efficiency and the extent of curing during the coating process.

Advancing Product Quality: a Summary of the Inaugural FDA/PQRI Conference

On September 16 and 17, 2014, the Food and Drug Administration (FDA) and Product Quality Research Institute (PQRI) inaugurated their Conference on Evolving Product Quality. The Conference is conceived as an annual forum in which scientists from regulatory agencies, industry, and academia may exchange viewpoints and work together to advance pharmaceutical quality. This Conference Summary Report highlights key topics of this conference, including (1) risk-based approaches to pharmaceutical development, manufacturing, regulatory assessment, and post-approval changes; (2) FDA-proposed quality metrics for products, facilities, and quality management systems; (3) performance-based quality assessment and clinically relevant specifications; (4) recent developments and implementation of continuous manufacturing processes, question-based review, and European Medicines Agency (EMA)-FDA pilot for Quality-by-Design (QbD) applications; and (5) breakthrough therapies, biosimilars, and international harmonization, focusing on ICH M7 and Q3D guidelines. The second FDA/PQRI conference on advancing product quality is planned for October 5-7, 2015.

Chemometric analysis for identification of botanical raw materials for pharmaceutical use: a case study using Panax notoginseng

The overall control of the quality of botanical drugs starts from the botanical raw material, continues through preparation of the botanical drug substance and culminates with the botanical drug product. Chromatographic and spectroscopic fingerprinting has been widely used as a tool for the quality control of herbal/botanical medicines. However, discussions are still on-going on whether a single technique provides adequate information to control the quality of botanical drugs. In this study, high performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC), capillary electrophoresis (CE) and near infrared spectroscopy (NIR) were used to generate fingerprints of different plant parts of Panax notoginseng. The power of these chromatographic and spectroscopic techniques to evaluate the identity of botanical raw materials were further compared and investigated in light of the capability to distinguishing different parts of Panax notoginseng. Principal component analysis (PCA) and clustering results showed that samples were classified better when UPLC- and HPLC-based fingerprints were employed, which suggested that UPLC- and HPLC-based fingerprinting are superior to CE- and NIR-based fingerprinting. The UPLC- and HPLC- based fingerprinting with PCA were able to correctly distinguish between samples sourced from rhizomes and main root. Using chemometrics and its ability to distinguish between different plant parts could be a powerful tool to help assure the identity and quality of the botanical raw materials and to support the safety and efficacy of the botanical drug products.

Class modeling analysis of heparin 1H NMR spectral data using the soft independent modeling of class analogy and unequal class modeling techniques

To differentiate heparin samples with varying amounts of dermatan sulfate (DS) impurities and oversulfated chondroitin sulfate (OSCS) contaminants, proton NMR spectral data for heparin sodium active pharmaceutical ingredient samples from different manufacturers were analyzed using multivariate chemometric techniques. A total of 168 samples were divided into three groups: (a) Heparin, [DS] ≤ 1.0% and [OSCS] = 0%; (b) DS, [DS] > 1.0% and [OSCS] = 0%; (c) OSCS, [OSCS] > 0% with any content of DS. The chemometric models were constructed and validated using two well-established methods: soft independent modeling of class analogy (SIMCA) and unequal class modeling (UNEQ). While SIMCA modeling was conducted using the entire set of variables extracted from the NMR spectral data, UNEQ modeling was combined with variable reduction using stepwise linear discriminant analysis to comply with the requirement that the number of samples per class exceed the number of variables in the model by at least 3-fold. Comparison of the results from these two modeling approaches revealed that UNEQ had greater sensitivity (fewer false positives) while SIMCA had greater specificity (fewer false negatives). For Heparin, DS, and OSCS, respectively, the sensitivity was 78% (56/72), 74% (37/50), and 85% (39/46) from SIMCA modeling and 88% (63/72), 90% (45/50), and 91% (42/46) from UNEQ modeling. Importantly, the specificity of both the SIMCA and UNEQ models was 100% (46/46) for Heparin with respect to OSCS; no OSCS-containing sample was misclassified as Heparin. The specificity of the SIMCA model (45/50, or 90%) was superior to that of the UNEQ model (27/50, or 54%) for Heparin with respect to DS samples. However, the overall prediction ability of the UNEQ model (85%) was notably better than that of the SIMCA model (76%) for the Heparin vs DS vs OSCS classes. The models were challenged with blends of heparin spiked with nonsulfated, partially sulfated, or fully oversulfated chondroitin sulfate A, dermatan sulfate, or heparan sulfate at the 1.0, 5.0, and 10.0 wt % levels. The results from the present study indicate that the combination of (1)H NMR spectral data and class modeling techniques (viz., SIMCA and UNEQ) represents a promising strategy for assessing the quality of commercial heparin samples with respect to impurities and contaminants. The methodologies show utility for applications beyond heparin to other complex products.

Combining (1)H NMR spectroscopy and chemometrics to identify heparin samples that may possess dermatan sulfate (DS) impurities or oversulfated chondroitin sulfate (OSCS) contaminants

Heparin is a naturally produced, heterogeneous compound consisting of variably sulfated and acetylated repeating disaccharide units. The structural complexity of heparin complicates efforts to assess the purity of the compound, especially when differentiating between similar glycosaminoglycans. Recently, heparin sodium contaminated with oversulfated chondroitin sulfate A (OSCS) has been associated with a rapid and acute onset of an anaphylactic reaction. In addition, naturally occurring dermatan sulfate (DS) was found to be present in these and other heparin samples as an impurity due to incomplete purification. The present study was undertaken to determine whether chemometric analysis of these NMR spectral data would be useful for discrimination between USP-grade samples of heparin sodium API and those deemed unacceptable based on their levels of DS, OSCS, or both. Several multivariate chemometric methods for clustering and classification were evaluated; specifically, principal components analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and the k-nearest-neighbor (kNN) method. Data dimension reduction and variable selection techniques, implemented to avoid over-fitting the training set data, markedly improved the performance of the classification models. Under optimal conditions, a perfect classification (100% success rate) was attained on external test sets for the Heparin vs OSCS model. The predictive rates for the Heparin vs DS, Heparin vs [DS+OSCS], and Heparin vs DS vs OSCS models were 89%, 93%, and 90%, respectively. In most cases, misclassifications can be ascribed to the similarity in NMR chemical shifts of heparin and DS. Among the chemometric methods evaluated in this study, we found that the LDA models were superior to the PLS-DA and kNN models for classification. Taken together, the present results demonstrate the utility of chemometric methods when applied in combination with (1)H NMR spectral analysis for evaluating the quality of heparin APIs.