A cross-industry forum on benchmarking critical quality attribute identification and linkage to process characterization studies.

Identification of Critical Quality Attributes (CQAs) and subsequent characterization in process development studies are the key elements of quality by design (QbD) for biopharmaceutical products. Since the inception of ICH Q8R2, several articles have been published on approaches to conducting CQA risk assessments as well as the application to process understanding. A survey was conducted by multiple companies participating in an International Consortium working group on the best practices for identifying CQAs with linkages to process characterization (PC) studies. The results indicate that the companies surveyed are using similar approaches/timing to identify CQAs during process development. Consensus was also observed among the companies surveyed with approaches to linkage of CQAs to process characterization studies leading to impact to control strategies and lifecycle management.

Adverse health effects of abuse-deterrent opioids: Evidence from the reformulation of OxyContin.

The United States is currently in the midst of the worst drug epidemic in its history, with nearly 64,000 overdose deaths in 2016. In response, pharmaceutical companies have begun introducing abuse-deterrent painkillers, pills with properties that make the drug more difficult to misuse. The first such painkiller, a reformulated version of OxyContin, was released in 2010. Previous research has found no net effect on opioid mortality, with users substituting from OxyContin toward heroin. This paper explores health effects of the reformulation beyond mortality. In particular, I show that heroin is substantially more likely to be injected than OxyContin, increasing exposure to blood-borne diseases. Exploiting variation across states in OxyContin misuse prior to the reformulation, I find relative increases in the spread of hepatitis B and C in states most likely to be affected by the reformulation. In aggregate, the estimates suggest that absent the reformulation, we would have observed approximately 76% fewer cases of hepatitis C and 53% fewer cases of hepatitis B from 2011 to 2015. I find some suggestive evidence that the reformulation also lead to increases in HIV and hepatitis A, although these findings are less robust. These findings have important implications for future policies addressing the opioid crisis.

Precision of the reportable value-Statistical optimization of the number of replicates.

In pharmaceutical analysis, the precision of the reportable value, i.e. the result which is to be compared to the specification limit(s), is relevant for the suitability of the analytical procedure. Using the variance contributions determined in precision studies addressing the levels injection/system precision, repeatability, and intermediate precision, the number of the corresponding replications for analysis/injection, sample preparation, and series/runs can be varied to improve the precision of the mean (reportable) value (Ermer, Agut, J.Chromatogr. A, 1353 (2014) 71-77). However, this calculation will provide only information on the gain for the precision of the calculated reportable value itself. These so-called point estimators have uncertainty associated with them which can be quantified using statistical confidence intervals. Commonly used statistical equations only allow one to calculate confidence intervals for the intermediate precision of the reportable value, which requires that the routine replication strategy must be defined before starting the precision study. In this paper, statistical models are presented that allow optimizing efficiently the replication strategy with respect to the confidence interval of the precision based on the Satterthwaite approximation posterior, i.e. using the results from the precision study without prior knowledge, as for the point estimate. It is further proposed to simplify the model by including only significant variance contributions larger than 20% of the total variation. The advantage of this minimizing the level of nesting is that the upper precision bound will tighten as the level of nesting decreases. This is important as 90% upper confidence bounds are often up to 2 or 3 times the point estimate, even for a larger number of four runs in the precision study. Four models each have been developed both for a 2-fold balanced nested design representing a complete intermediate precision study, and for a 1-fold balanced nested design using injection/system precision from an independent source. An Excel spreadsheet that performs all the calculations in this paper as well as the appropriate model selection is available from the authors. Due to the usually rather low number of series/runs in precision studies, the uncertainty of the reportable value precision is often dominated by the factor runs. For a statistical evaluation of the precision of the reportable value (in case of three precision levels), the authors recommend a minimum of six runs, two preparations per run, and two injections/analyses per preparation, in order to provide sufficient precision of the variance estimates. However, a risk-based approach is recommended for the decision to apply a statistical evaluation of the precision of the reportable value. In case of low patient risk such as for an assay of a well-characterized drug substance with tightly controlled manufacturing and analytical variability dominating the specification range, a point estimator will usually be adequate to demonstrate the suitability of the analytical procedure.

Partnership for productive development of biosimilar products: perspectives of access to biological products in the Brazilian market.

The manufacturing process for biological products is complex, expensive and critical to the final product, with an impact on their efficacy and safety. They have been increasingly used to treat several diseases, and account for approximately 50% of the yearly budget for the Brazilian public health system. As the patents of biological products expire, several biosimilars are developed. However, there are concerns regarding their efficacy and safety; therefore, the regulatory agencies establish rules to approve and monitor these products. In Brazil, partnership programs between national government-owned companies and private technology holders have been implemented, aiming at knowledge sharing, capacity-building and technological transfer. Such partnerships locally promote manufacturing of these strategic drugs at reduced costs to the public health system. These agreements offer mutual advantages to both the government and patent holders: for the former, a biotechnological development flow is established and enables potential cost reduction and self-sufficient production; whereas for the latter, exclusive sales of the product are ensured during technological transfer, for a fixed period.

Scientific, statistical, practical, and regulatory considerations in design space development.

The quality by design (QbD) paradigm guides the pharmaceutical industry towards improved understanding of products and processes, and at the same time facilitates a high degree of manufacturing and regulatory flexibility throughout the establishment of the design space. This review article presents scientific, statistical and regulatory considerations in design space development. All key development milestones, starting with planning, selection of factors, experimental execution, data analysis, model development and assessment, verification, and validation, and ending with design space submission, are presented and discussed. The focus is especially on frequently ignored topics, like management of factors and CQAs that will not be included in experimental design, evaluation of risk of failure on design space edges, or modeling scale-up strategy. Moreover, development of a design space that is independent of manufacturing scale is proposed as the preferred approach.

Partnership for productive development of biosimilar products: perspectives of access to biological products in the Brazilian market / Parceria para o desenvolvimento produtivo com produtos biossimilares: perspectivas de acesso a produtos biológicos no mercado brasileiro

ABSTRACT The manufacturing process for biological products is complex, expensive and critical to the final product, with an impact on their efficacy and safety. They have been increasingly used to treat several diseases, and account for approximately 50% of the yearly budget for the Brazilian public health system. As the patents of biological products expire, several biosimilars are developed. However, there are concerns regarding their efficacy and safety; therefore, the regulatory agencies establish rules to approve and monitor these products. In Brazil, partnership programs between national government-owned companies and private technology holders have been implemented, aiming at knowledge sharing, capacity-building and technological transfer. Such partnerships locally promote manufacturing of these strategic drugs at reduced costs to the public health system. These agreements offer mutual advantages to both the government and patent holders: for the former, a biotechnological development flow is established and enables potential cost reduction and self-sufficient production; whereas for the latter, exclusive sales of the product are ensured during technological transfer, for a fixed period.

RESUMO O processo de manufatura de produtos biológicos é complexo, oneroso e crítico para o produto final, com impacto em sua eficácia e segurança. Seu uso está sendo cada vez mais ampliado no tratamento de diversas doenças, e cerca de 50% do orçamento anual do sistema de saúde público brasileiro é consumido por tais produtos. Com o término da proteção de patentes de produtos biológicos diversos, estão sendo desenvolvidos os biossimilares. Porém, há preocupações relacionadas com sua eficácia e segurança, fazendo com que os órgãos reguladores criem regulamentações para sua aprovação e monitoramento. No Brasil, estão sendo implantados programas de parceria entre laboratórios públicos nacionais e laboratórios detentores de tecnologia, objetivando a obtenção de conhecimento, capacitação profissional e transferência desta tecnologia. Tais parcerias visam à produção local destes medicamentos estratégicos a um custo reduzido para o Sistema Único de Saúde. Os acordos oferecem vantagens mútuas para o governo e o laboratório detentor da patente do produto biológico: ao primeiro, estabelece-se um fluxo de desenvolvimento biotecnológico, que possibilita potencial redução de custos e autossuficiência na produção, enquanto ao segundo garante-se a exclusividade da venda do produto durante a transferência da tecnologia por um prazo estabelecido.

Biochemical comparison of four commercially available human α1-proteinase inhibitors for treatment of α1-antitrypsin deficiency.

Intravenous therapy with purified plasma-derived alpha1-proteinase inhibitor (α1-PI) concentrates is the only specific treatment for α1-PI deficiency. For the therapy to be safe and efficacious, α1-PI concentrates should be highly pure and contain high amounts of functional protein. This study compared the four plasma-derived α1-PI products commercially available in Europe (Respreeza, Prolastin, Alfalastin, Trypsone) by biochemical methods with respect to function, purity, structure, and chemical modifications. Respreeza had the highest level of functional protein (48.8 mg/mL) and the highest specific activity (0.862 mg active α1-PI per mg total protein). By size exclusion chromatography, Respreeza was 97.4% pure, followed by Alfalastin 88.1%, Prolastin 76.9%, and Trypsone 70.8%. By reversed phase chromatography, Respreeza had an α1-PI purity of 97.7%, followed by Trypsone 88.0%, Prolastin 78.0%, and Alfalastin 69.5%. The main protein band by sodium dodecyl sulphate-polyacrylamide gel electrophoresis was found for all products at approximately 50 kDa. Additional protein bands were found for Prolastin, Alfalastin, and Trypsone. The α1-PI products differed in cysteine oxidation state and C-terminal lysine status. α1-PI products tested differ in purity, concentration, and chemical variation. Respreeza has the highest level of purity. The impact of the non-therapeutic proteins identified has not been evaluated.

Optimization of a Decoction Process for an Herbal Formula Using a Response Surface Methodology.

An herbal formula, Huang-Qi-Liu-Yi Tang, is a prescription medicine that has been commonly used for the treatment of prostatitis and condyloma acuminatum over the last thousand years. In this study, response surface methodology, with a Box-Behnken design (BBD), was used to optimize the decoction conditions of an herbal formula. Astragaloside, calycosin-7-glucoside, glycyrrhizic acid, liquiritin, polysaccharide, and extractum were used as multiple evaluation markers. Soak time, water-to-medicinal herb ratio, and extraction time were determined as the three main variables by single-factor experiments and further optimized to obtain the maximum yields for the six marker compounds. Data from well-designed experiments were fitted to obtain second-order polynomial equations using multiple regression analysis, and the accuracies of these equations were evaluated and verified using statistical methods. By solving the regression equations and analyzing the three-dimensional response surfaces, optimum conditions were obtained and are summarized as follows: soak time of 57 min, water-to-medicinal herb ratio of 9:1 (mL/g), and extraction time of 48 min. Under optimized conditions, the experimental yields of astragaloside, calycosin-7-glucoside, glycyrrhizic acid, liquiritin, polysaccharide, and extractum were 0.13, 0.085, 1.64, 1.56, 72.19, and 25.64%, respectively, which was in good agreement with the values predicted by the BBD.

In-line monitoring of compaction properties on a rotary tablet press during tablet manufacturing of hot-melt extruded amorphous solid dispersions.

As the number of applications for polymers in pharmaceutical development is increasing, there is need for fundamental understanding on how such compounds behave during tableting. This research is focussed on the tableting behaviour of amorphous polymers, their solid dispersions and the impact of hot-melt extrusion on the compaction properties of these materials. Soluplus, Kollidon VA 64 and Eudragit EPO were selected as amorphous polymers since these are widely studied carriers for solid dispersions, while Celecoxib was chosen as BCS class II model drug. Neat polymers and physical mixtures (up to 35% drug load) were processed by hot-melt extrusion (HME), milled and sieved to obtain powders with comparable particle sizes as the neat polymer. A novel approach was used for in-line analysis of the compaction properties on a rotary tablet press (Modul P, GEA) using complementary sensors and software (CDAAS, GEA). By combining 'in-die' and 'out-of-die' techniques, it was possible to investigate in a comprehensive way the impact of HME on the tableting behaviour of amorphous polymers and their formulations. The formation of stable glassy solutions altered the formulations towards more fragmentary behaviour under compression which was beneficial for the tabletability. Principal component analysis (PCA) was applied to summarize the behaviour during compaction of the formulations, enabling the selection of Soluplus and Kollidon VA 64 as the most favourable polymers for compaction of glassy solutions.

Sensitivity analysis of a pharmaceutical tablet production process from the control engineering perspective.

This paper presents a sensitivity analysis of a pharmaceutical direct compaction process. Sensitivity analysis is an important tool for gaining valuable process insights and designing a process control concept. Examining its results in a systematic manner makes it possible to assign actuating signals to controlled variables. This paper presents mathematical models for individual unit operations, on which the sensitivity analysis is based. Two sensitivity analysis methods are outlined: (i) based on the so-called Sobol indices and (ii) based on the steady-state gains and the frequency response of the proposed plant model.

Statistical analysis and comparison of a continuous high shear granulator with a twin screw granulator: Effect of process parameters on critical granule attributes and granulation mechanisms.

This study is concerned with identifying the design space of two different continuous granulators and their respective granulation mechanisms. Performance of a continuous high shear granulator and a twin screw granulator with paracetamol formulations were examined by face-centered cubic design, which focused on investigating key performance metrics, namely, granule size, porosity, flowability and particle morphology of granules as a function of essential input process parameters (liquid content, throughput and rotation speed). Liquid and residence time distribution tests were also performed to gain insights into the liquid-powder mixing and flow behavior. The results indicated that continuous high shear granulation was more sensitive to process variation and produced spherical granules with monomodal size distribution and distinct internal structure and strength variation. Twin screw granulation with such a particular screw configuration showed narrower design space and granules were featured with multimodal size distribution, irregular shape, less detectible porosity difference and tighter range of strength. Granulation mechanisms explored on the basis of nucleation and growth regime maps revealed that for most cases liquid binder was uniformly distributed with fast droplet penetration into the powder bed and that granule consolidation and coalescence mainly took place in the nucleation, steady growth and rapid growth regimes.

Statistical analysis of industrial-scale roller compactor 'Freund TF-MINI model'.

The aim of this study is to perform a statistical analysis on a pharmaceutical roller compaction process using an industrial-scale roller compactor "Freund TF-MINI model". The process was modelled using response surface methodology (RSM) to better understand and control the process in order to produce ribbons and granules with optimised quality. The significant process parameters were determined to be (i) the screw speed to roll speed ratio and (ii) the roll pressure. The roll speed was kept constant and the roll gap was uncontrolled. The quality attributes of interest are: ribbon density, granule size (D10, D50, D90), amount of fines (granule size <157µm), and tablet hardness. Microcrystalline cellulose (MCC) PH 102 was used as a model material. Design-Expert V9 was utilised to establish the design matrix and to analyse the experimental data. The relationships between the process parameters and the resultant ribbon/granule/tablet characteristics were established. This was followed by an optimisation of the process parameters to obtain the target responses. The results confirmed the attainment of significant models with satisfactory accurate measures. The optimisation allowed for the determination of the process parameters required to produce the best quality tablets.

Design and optimization of disintegrating pellets of MCC by non-aqueous extrusion process using statistical tools.

The objective of the study was to design and optimize a disintegrating pellet formulation of microcrystalline cellulose by non-aqueous extrusion process for a water sensitive drug using various statistical tools. Aspirin was used as a model drug. Disintegrating matrix pellets of aspirin using propylene glycol as a non-aqueous granulation liquid and croscarmellose as a disintegrant was developed. Plackett-Burman design was initially conducted to screen and identify the significant factors. Final optimization of formula was performed by response surface methodology using a central composite design. The critical attributes of the pellet dosage forms (dependent variables); disintegration time, sphericity and yield were predicted with adequate accuracy based on the regression model. Pareto charts and contour charts were studied to understand the influence of factors and predict the responses. A design space was constructed to meet the desirable targets of the responses in terms of disintegration time <5min, maximum yield, sphericity >0.95 and friability <1.7%. The optimized matrix pellets were enteric coated using Eudragit L 100. The drug release from the enteric coated pellets after 30min in the basic media was ~93% when compared to ~77% from the marketed pellets. The delayed release pellets stored at 25°C/60% RH were stable for a period of 10mo. In conclusion, it can be stated that the developed process for disintegrating pellets using non-aqueous granulating agents can be used as an alternative technique for various water sensitive drugs, circumventing the application of volatile organic solvents in conventional drug layering on inert cores. The scope of this study can be further extended to hydrophobic drugs, which may benefit from the rapid disintegration property and the use of various hydrophilic excipients used in the optimized pellet formulation to enhance dissolution and in turn improve bioavailability.

Dissolution curve comparisons through the F(2) parameter, a Bayesian extension of the f(2) statistic.

Dissolution (or in vitro release) studies constitute an important aspect of pharmaceutical drug development. One important use of such studies is for justifying a biowaiver for post-approval changes which requires establishing equivalence between the new and old product. We propose a statistically rigorous modeling approach for this purpose based on the estimation of what we refer to as the F2 parameter, an extension of the commonly used f2 statistic. A Bayesian test procedure is proposed in relation to a set of composite hypotheses that capture the similarity requirement on the absolute mean differences between test and reference dissolution profiles. Several examples are provided to illustrate the application. Results of our simulation study comparing the performance of f2 and the proposed method show that our Bayesian approach is comparable to or in many cases superior to the f2 statistic as a decision rule. Further useful extensions of the method, such as the use of continuous-time dissolution modeling, are considered.

A statistical approach to determining criticality of residual host cell DNA.

We propose a method for determining the criticality of residual host cell DNA, which is characterized through two attributes, namely the size and amount of residual DNA in biopharmaceutical product. By applying a mechanistic modeling approach to the problem, we establish the linkage between residual DNA and product safety measured in terms of immunogenicity, oncogenicity, and infectivity. Such a link makes it possible to establish acceptable ranges of residual DNA size and amount. Application of the method is illustrated through two real-life examples related to a vaccine manufactured in Madin Darby Canine Kidney cell line and a monoclonal antibody using Chinese hamster ovary (CHO) cell line as host cells.

One- and two-stage Arrhenius models for pharmaceutical shelf life prediction.

One of the most challenging aspects of the pharmaceutical development is the demonstration and estimation of chemical stability. It is imperative that pharmaceutical products be stable for two or more years. Long-term stability studies are required to support such shelf life claim at registration. However, during drug development to facilitate formulation and dosage form selection, an accelerated stability study with stressed storage condition is preferred to quickly obtain a good prediction of shelf life under ambient storage conditions. Such a prediction typically uses Arrhenius equation that describes relationship between degradation rate and temperature (and humidity). Existing methods usually rely on the assumption of normality of the errors. In addition, shelf life projection is usually based on confidence band of a regression line. However, the coverage probability of a method is often overlooked or under-reported. In this paper, we introduce two nonparametric bootstrap procedures for shelf life estimation based on accelerated stability testing, and compare them with a one-stage nonlinear Arrhenius prediction model. Our simulation results demonstrate that one-stage nonlinear Arrhenius method has significant lower coverage than nominal levels. Our bootstrap method gave better coverage and led to a shelf life prediction closer to that based on long-term stability data.

Statistical considerations in setting product specifications.

According to ICH Q6A (1999), a specification is defined as a list of tests, references to analytical procedures, and appropriate acceptance criteria, which are numerical limits, ranges, or other criteria for the tests described. For drug products, specifications usually consist of test methods and acceptance criteria for assay, impurities, pH, dissolution, moisture, and microbial limits, depending on the dosage forms. They are usually proposed by the manufacturers and subject to the regulatory approval for use. When the acceptance criteria in product specifications cannot be pre-defined based on prior knowledge, the conventional approach is to use data from a limited number of clinical batches during the clinical development phases. Often in time, such acceptance criterion is set as an interval bounded by the sample mean plus and minus two to four standard deviations. This interval may be revised with the accumulated data collected from released batches after drug approval. In this article, we describe and discuss the statistical issues of commonly used approaches in setting or revising specifications (usually tighten the limits), including reference interval, (Min, Max) method, tolerance interval, and confidence limit of percentiles. We also compare their performance in terms of the interval width and the intended coverage. Based on our study results and review experiences, we make some recommendations on how to select the appropriate statistical methods in setting product specifications to better ensure the product quality.

A quality by design approach for longitudinal quality attributes.

The concept of quality by design (QbD) as published in ICH-Q8 is currently one of the most recurrent topics in the pharmaceutical literature. This guideline recommends the use of information and prior knowledge gathered during pharmaceutical development studies to provide a scientific rationale for the manufacturing process of a product and provide guarantee of future quality. This poses several challenges from a statistical standpoint and requires a shift in paradigm from traditional statistical practices. First, to provide "assurance of quality" of future lots implies the need to make predictions regarding the quality given past evidence and data. Second, the quality attributes described in the Q8 guidelines are not always a set of unique, independent measurements. In many cases, these criteria are complicated longitudinal data with successive acceptance criteria over a defined period of time. A common example is a dissolution profile for a modified or extended-release solid dosage form that must fall within acceptance limits at several time points. A Bayesian approach for longitudinal data obtained in various conditions of a design of experiment is provided to elegantly address the ICH-Q8 recommendation to provide assurance of quality and derive a scientifically sound design space.

Non-normal random effects models for immunogenicity assay cut point determination.

Administration of biological therapeutics can generate undesirable immune responses that may induce anti-drug antibodies (ADAs). Immunogenicity can negatively affect patients, ranging from mild reactive effect to hypersensitivity reactions or even serious autoimmune diseases. Assessment of immunogenicity is critical as the ADAs can adversely impact the efficacy and safety of the drug products. Well-developed and validated immunogenicity assays are required by the regulatory agencies as tools for immunogenicity assessment. Key to the development and validation of an immunogenicity assay is the determination of a cut point, which serves as the threshold for classifying patients as ADA positive(reactive) or negative. In practice, the cut point is determined as either the quantile of a parametric or nonparametric empirical distribution. The parametric method, which is often based on a normality assumption, may lead to biased cut point estimates when the normality assumption is violated. The non-parametric method, which yields unbiased estimates of the cut point, may have low efficiency when the sample size is small. As the distribution of immune responses are often skewed and sometimes heavy-tailed, we propose two non-normal random effects models for cut point determination. The random effects, following a skew-t or log-gamma distribution, can incorporate the skewed and heavy-tailed responses and the correlation among repeated measurements. Simulation study is conducted to compare the proposed method with the current normal and nonparametric alternatives. The proposed models are also applied to a real dataset generated from assay validation studies.