Polymorphic and Quantum Chemistry Characterization of Candesartan Cilexetil: Importance for the Correct Drug Classification According to Biopharmaceutics Classification System.

The recommended method for the biopharmaceutical evaluation of drug solubility is the shake flask; however, there are discrepancies reported about the solubility of certain compounds measured with this method, one of them is candesartan cilexetil. The present work aimed to elucidate the solubility of candesartan cilexetil by associating others assays such as stability determination, polymorphic characterization and in silico calculations of intrinsic solubility, ionized species, and electronic structures using quantum chemistry descriptors (frontier molecular orbitals and Fukui functions). For the complete biopharmaceutical classification, we also reviewed the permeability data available. The polymorphic form used was previously identified as the form I of candesartan cilexetil. The solubility was evaluated in biorelevant media in the pH range of 1.2-6.8 at 37.0°C according to the stability previously assessed. The solubility of candesartan cilexetil is pH dependent and the dose/solubility ratios obtained demonstrated the low solubility of the prodrug. The in silico calculations supported the found results and evidenced the main groups involved in the solvation, benzimidazole, and tetrazol-biphenyl. The human absolute bioavailability reported demonstrates that candesartan cilexetil has low permeability and when associated with the low solubility allows to classify it as class 4 of the Biopharmaceutics Classification System.

Opportunities and challenges of real-time release testing in biopharmaceutical manufacturing.

Real-time release testing (RTRT) is defined as "the ability to evaluate and ensure the quality of in-process and/or final drug product based on process data, which typically includes a valid combination of measured material attributes and process controls" (ICH Q8[R2]). This article discusses sensors (process analytical technology, PAT) and control strategies that enable RTRT for the spectrum of critical quality attributes (CQAs) in biopharmaceutical manufacturing. Case studies from the small-molecule and biologic pharmaceutical industry are described to demonstrate how RTRT can be facilitated by integrated manufacturing and multivariable control strategies to ensure the quality of products. RTRT can enable increased assurance of product safety, efficacy, and quality-with improved productivity including faster release and potentially decreased costs-all of which improve the value to patients. To implement a complete RTRT solution, biologic drug manufacturers need to consider the special attributes of their industry, particularly sterility and the measurement of viral and microbial contamination. Continued advances in on-line and in-line sensor technologies are key for the biopharmaceutical manufacturing industry to achieve the potential of RTRT. Related article: http://onlinelibrary.wiley.com/doi/10.1002/bit.26378/full.

Validation of Dissolution Testing with Biorelevant Media: An OrBiTo Study.

Dissolution testing with biorelevant media has become widespread in the pharmaceutical industry as a means of better understanding how drugs and formulations behave in the gastrointestinal tract. Until now, however, there have been few attempts to gauge the reproducibility of results obtained with these methods. The aim of this study was to determine the interlaboratory reproducibility of biorelevant dissolution testing, using the paddle apparatus (USP 2). Thirteen industrial and three academic laboratories participated in this study. All laboratories were provided with standard protocols for running the tests: dissolution in FaSSGF to simulate release in the stomach, dissolution in a single intestinal medium, FaSSIF, to simulate release in the small intestine, and a "transfer" (two-stage) protocol to simulate the concentration profile when conditions are changed from the gastric to the intestinal environment. The test products chosen were commercially available ibuprofen tablets and zafirlukast tablets. The biorelevant dissolution tests showed a high degree of reproducibility among the participating laboratories, even though several different batches of the commercially available medium preparation powder were used. Likewise, results were almost identicalbetween the commercial biorelevant media and those produced in-house. Comparing results to previous ring studies, including those performed with USP calibrator tablets or commercially available pharmaceutical products in a single medium, the results for the biorelevant studies were highly reproducible on an interlaboratory basis. Interlaboratory reproducibility with the two-stage test was also acceptable, although the variability was somewhat greater than with the single medium tests. Biorelevant dissolution testing is highly reproducible among laboratories and can be relied upon for cross-laboratory comparisons.

Impact of the US FDA "Biopharmaceutics Classification System" (BCS) Guidance on Global Drug Development.

The FDA guidance on application of the biopharmaceutics classification system (BCS) for waiver of in vivo bioequivalence (BE) studies was issued in August 2000. Since then, this guidance has created worldwide interest among biopharmaceutical scientists in regulatory agencies, academia, and industry toward its implementation and further expansion. This article describes how the review implementation of this guidance was undertaken at the FDA and results of these efforts over last dozen years or so across the new, and the generic, drug domains are provided. Results show that greater than 160 applications were approved, or tentatively approved, based on the BCS approach across multiple therapeutic areas; an additional significant finding was that at least 50% of these approvals were in the central nervous system (CNS) area. These findings indicate a robust utilization of the BCS approach toward reducing unnecessary in vivo BE studies and speeding up availability of high quality pharmaceutical products. The article concludes with a look at the adoption of this framework by regulatory and health policy organizations across the globe, and FDA's current thinking on areas of improvement of this guidance.

Immunoassays for Measuring Serum Concentrations of Monoclonal Antibodies and Anti-biopharmaceutical Antibodies in Patients.

Monoclonal antibodies (mAbs) may be used as biopharmaceuticals to treat various diseases, ranging from oncology to inflammatory and cardiovascular affections. Trustworthy analytical methods are necessary to study their pharmacokinetics, both during their development and in post-marketing studies. Because biopharmaceuticals are macromolecules, ligand-binding assays (both immunoassays and bioassays) are methods of choice to measure their concentrations. Immunoassays are based on the capture of biopharmaceuticals by their target, which may be a circulating or membrane antigen or by an antibody recognizing their structure. Bioassays measure the activity of the biopharmaceutical in a specific in vitro test. A number of techniques have been reported, but their limits of detection and quantification vary widely. Anti-drug antibodies (ADA) against biopharmaceuticals are often formed and sometimes interfere with clinical efficacy. Accurate and reliable detection of ADA is therefore necessary. Binding of ADA is dependent on affinity and avidity, which makes quantification challenging. In this review, we discuss the benefits and limitations of each method to determine mAb levels and carefully compare ADA assays.

Current and evolving approaches for improving the oral permeability of BCS Class III or analogous molecules.

The Biopharmaceutics Classification System (BCS) classifies pharmaceutical compounds based on their aqueous solubility and intestinal permeability. The BCS Class III compounds are hydrophilic molecules (high aqueous solubility) with low permeability across the biological membranes. While these compounds are pharmacologically effective, poor absorption due to low permeability becomes the rate-limiting step in achieving adequate bioavailability. Several approaches have been explored and utilized for improving the permeability profiles of these compounds. The approaches include traditional methods such as prodrugs, permeation enhancers, ion-pairing, etc., as well as relatively modern approaches such as nanoencapsulation and nanosizing. The most recent approaches include a combination/hybridization of one or more traditional approaches to improve drug permeability. While some of these approaches have been extremely successful, i.e. drug products utilizing the approach have progressed through the USFDA approval for marketing; others require further investigation to be applicable. This article discusses the commonly studied approaches for improving the permeability of BCS Class III compounds.

Assessment Methodology for Process Validation Lifecycle Stage 3A.

The paper introduces evaluation methodologies and associated statistical approaches for process validation lifecycle Stage 3A. The assessment tools proposed can be applied to newly developed and launched small molecule as well as bio-pharma products, where substantial process and product knowledge has been gathered. The following elements may be included in Stage 3A: number of 3A batch determination; evaluation of critical material attributes, critical process parameters, critical quality attributes; in vivo in vitro correlation; estimation of inherent process variability (IPV) and PaCS index; process capability and quality dashboard (PCQd); and enhanced control strategy. US FDA guidance on Process Validation: General Principles and Practices, January 2011 encourages applying previous credible experience with suitably similar products and processes. A complete Stage 3A evaluation is a valuable resource for product development and future risk mitigation of similar products and processes. Elements of 3A assessment were developed to address industry and regulatory guidance requirements. The conclusions made provide sufficient information to make a scientific and risk-based decision on product robustness.

The Effect of Excipients on the Permeability of BCS Class III Compounds and Implications for Biowaivers.

PURPOSE: Currently, the FDA allows biowaivers for Class I (high solubility and high permeability) and Class III (high solubility and low permeability) compounds of the Biopharmaceutics Classification System (BCS). Scientific evidence should be provided to support biowaivers for BCS Class I and Class III (high solubility and low permeability) compounds. METHODS: Data on the effects of excipients on drug permeability are needed to demonstrate that commonly used excipients do not affect the permeability of BCS Class III compounds, which would support the application of biowaivers to Class III compounds. This study was designed to generate such data by assessing the permeability of four BCS Class III compounds and one Class I compound in the presence and absence of five commonly used excipients. RESULTS: The permeability of each of the compounds was assessed, at three to five concentrations, with each excipient in two different models: Caco-2 cell monolayers, and in situ rat intestinal perfusion. No substantial increases in the permeability of any of the compounds were observed in the presence of any of the tested excipients in either of the models, with the exception of disruption of Caco-2 cell monolayer integrity by sodium lauryl sulfate at 0.1 mg/ml and higher. CONCLUSION: The results suggest that the absorption of these four BCS Class III compounds would not be greatly affected by the tested excipients. This may have implications in supporting biowaivers for BCS Class III compounds in general.

Industry view on the relative importance of "clonality" of biopharmaceutical-producing cell lines.

Recently, several health authorities have requested substantial detail from sponsor firms regarding the practices employed to generate the production cell line for recombinant DNA-(rDNA) derived biopharmaceuticals. Two possible inferences from these regulatory agency questions are that (1) assurance of "clonality" of the production cell line is of major importance to assessing the safety and efficacy of the product and (2), without adequate proof of "clonality", additional studies of the cell line and product are often required to further ensure the product's purity and homogeneity. Here we address the topic of "clonality" in the broader context of product quality assurance by current technologies and practices, as well as discuss some of the relevant science and historical perspective. We agree that the clonal derivation of a production cell line is one factor with potential impact, but it is only one of many factors. Further, we believe that regulatory emphasis should be primarily placed on ensuring product quality of the material actually administered to patients, and on ensuring process consistency and implementing appropriate control strategies through the life cycle of the products.

Nanoparticulate Impurities in Pharmaceutical-Grade Sugars and their Interference with Light Scattering-Based Analysis of Protein Formulations.

PURPOSE: In the present study we investigated the root-cause of an interference signal (100-200 nm) of sugar-containing solutions in dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) and its consequences for the analysis of particles in biopharmaceutical drug products. METHODS: Different sugars as well as sucrose of various purity grades, suppliers and lots were analyzed by DLS and NTA before and (only for sucrose) after treatment by ultrafiltration and diafiltration. Furthermore, Fourier transform infrared (FTIR) microscopy, scanning electron microscopy coupled energy-dispersive X-ray spectroscopy (SEM-EDX), and fluorescence spectroscopy were employed. RESULTS: The intensity of the interference signal differed between sugar types, sucrose of various purity grades, suppliers, and batches of the same supplier. The interference signal could be successfully eliminated from a sucrose solution by ultrafiltration (0.02 µm pore size). Nanoparticles, apparently composed of dextrans, ash components and aromatic colorants that were not completely removed during the sugar refinement process, were found responsible for the interference and were successfully purified from sucrose solutions. CONCLUSIONS: The interference signal of sugar-containing solutions in DLS and NTA is due to the presence of nanoparticulate impurities. The nanoparticles present in sucrose were identified as agglomerates of various impurities originating from raw materials.

Review of the current use and evaluation of cell substrates for producing biologicals in selected countries.

In 2010, the WHO guidance document for the evaluation of cell substrates for producing biologicals was replaced with updated recommendations and in May 2013 an implementation workshop on the new recommendations was held in Beijing, China. As part of this workshop, a survey of the use and evaluation of cell substrates for producing biologicals was undertaken and the information obtained was updated in June 2014. The purpose of survey was to capture the status of national requirements related to cell substrates in various countries with particular emphasis on whether or not the updated WHO recommendations had been, or were to be, incorporated into national requirements. This paper reports the outcome of the survey and is based on information provided by regulators in eleven countries. Since the publication of the updated WHO recommendations, several activities such as the implementation workshop and publications have been undertaken by the WHO. The aim of these activities, including the publication of this article, is to contribute to the implementation of WHO recommendations so as to reduce regulatory gaps between national requirements and globally agreed expectations.

Analytical procedure validation and the quality by design paradigm.

Since the adoption of the ICH Q8 document concerning the development of pharmaceutical processes following a quality by design (QbD) approach, there have been many discussions on the opportunity for analytical procedure developments to follow a similar approach. While development and optimization of analytical procedure following QbD principles have been largely discussed and described, the place of analytical procedure validation in this framework has not been clarified. This article aims at showing that analytical procedure validation is fully integrated into the QbD paradigm and is an essential step in developing analytical procedures that are effectively fit for purpose. Adequate statistical methodologies have also their role to play: such as design of experiments, statistical modeling, and probabilistic statements. The outcome of analytical procedure validation is also an analytical procedure design space, and from it, control strategy can be set.

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.

Using tolerance intervals for assessment of pharmaceutical quality.

In quality control of drug products, tolerance intervals are commonly used methods to assure a certain proportion of the products covered within a pre-specified acceptance interval. Depending on the nature of the quality attributes, the corresponding acceptance interval could be one-sided or two-sided. Thus, the tolerance intervals can also be one-sided or two-sided. To better utilize tolerance intervals for quality assurance, we reviewed the computation method and studied their statistical properties in terms of batch acceptance probability in this article. We also illustrate the application of one-sided and two-sided tolerance, as well as two one-sided tests through the examples of dose content uniformity test, delivered dose uniformity test, and dissolution test.

Testing assay linearity over a pre-specified range.

Validation of linearity is a regulatory requirement. Although many methods are proposed, they suffer from several deficiencies including difficulties of setting fit-for-purpose acceptable limits, dependency on concentration levels used in linearity experiment, and challenges in implementation for statistically lay users. In this article, a statistical procedure for testing linearity is proposed. The method uses a two one-sided test (TOST) of equivalence to evaluate the bias that can result from approximating a higher-order polynomial response with a linear function. By using orthogonal polynomials and generalized pivotal quantity analysis, the method provides a closed-form solution, thus making linearity testing easy to implement.

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.

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.

Statistical evaluation of several methods for cut-point determination of immunogenicity screening assay.

The cut point of the immunogenicity screening assay is the level of response of the immunogenicity screening assay at or above which a sample is defined to be positive and below which it is defined to be negative. The Food and Drug Administration Guidance for Industry on Assay Development for Immunogenicity Testing of Therapeutic recommends the cut point to be an upper 95 percentile of the negative control patients. In this article, we assume that the assay data are a random sample from a normal distribution. The sample normal percentile is a point estimate with a variability that decreases with the increase of sample size. Therefore, the sample percentile does not assure at least 5% false-positive rate (FPR) with a high confidence level (e.g., 90%) when the sample size is not sufficiently enough. With this concern, we propose to use a lower confidence limit for a percentile as the cut point instead. We have conducted an extensive literature review on the estimation of the statistical cut point and compare several selected methods for the immunogenicity screening assay cut-point determination in terms of bias, the coverage probability, and FPR. The selected methods evaluated for the immunogenicity screening assay cut-point determination are sample normal percentile, the exact lower confidence limit of a normal percentile (Chakraborti and Li, 2007) and the approximate lower confidence limit of a normal percentile. It is shown that the actual coverage probability for the lower confidence limit of a normal percentile using approximate normal method is much larger than the required confidence level with a small number of assays conducted in practice. We recommend using the exact lower confidence limit of a normal percentile for cut-point determination.

Quality assurance test of delivered dose uniformity of multiple-dose inhaler and dry powder inhaler drug products.

The delivered dose uniformity is one of the most critical requirements for dry powder inhaler (DPI) and metered dose inhaler products. In 1999, the Food and Drug Administration (FDA) issued a Draft Guidance entitled Nasal Spray and Inhalation Solution, Suspension, and Spray Drug Products-Chemistry, Manufacturing and Controls Documentation and recommended a two-tier acceptance sampling plan that is a modification of the United States Pharmacopeia (USP) sampling plan of dose content uniformity (USP34<601>). This sampling acceptance plan is also applied to metered dose inhaler (MDI) and DPI drug products in general. The FDA Draft Guidance method is shown to have a near-zero probability of acceptance at the second tier. In 2000, under the request of The International Pharmaceutical Aerosol Consortium, the FDA developed a two-tier sampling acceptance plan based on two one-sided tolerance intervals (TOSTIs) for a small sample. The procedure was presented in the 2005 Advisory Committee Meeting of Pharmaceutical Science and later published in the Journal of Biopharmaceutical Statistics (Tsong et al., 2008). This proposed procedure controls the probability of the product delivering below a pre-specified effective dose and the probability of the product delivering over a pre-specified safety dose. In this article, we further propose an extension of the TOSTI procedure to single-tier procedure with any number of canisters.

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.