Quality-by-Design II: Application of Quantitative Risk Analysis to the Formulation of Ciprofloxacin Tablets (original) (raw)
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AAPS PharmSciTech, 2012
As outlined in the ICH Q8(R2) guidance, identifying the critical quality attributes (CQA) is a crucial part of dosage form development; however, the number of possible formulation and processing factors that could influence the manufacturing of a pharmaceutical dosage form is enormous obviating formal study of all possible parameters and their interactions. Thus, the objective of this study is to examine how quality risk management can be used to prioritize the number of experiments needed to identify the CQA, while still maintaining an acceptable product risk profile. To conduct the study, immediate-release ciprofloxacin tablets manufactured via roller compaction were used as a prototype system. Granules were manufactured using an Alexanderwerk WP120 roller compactor and tablets were compressed on a Stokes B2 tablet press. In the early stages of development, prior knowledge was systematically incorporated into the risk assessment using failure mode and effect analysis (FMEA). The factors identified using FMEA were then followed by a quantitative assessed using a Plackett-Burman screening design. Results show that by using prior experience, literature data, and preformulation data the number of experiments could be reduced to an acceptable level, and the use of FMEA and screening designs such as the Plackett Burman can rationally guide the process of reducing the number experiments to a manageable level.
Journal of Pharmaceutical and Biomedical Analysis, 2018
Pharmaceutical regulatory bodies increasingly require the implementation of systematic approaches in pharmaceutical product development. Quality control methods play a key role in the control strategy of drugs manufacturing to assure their quality. A risk-based approach in the analytical method development is strongly recommended to ensure that the method performances fit the purpose of the method during its entire life-cycle. In the last decade, analytical quality by design (AQbD), as risk management oriented methodology, has been progressively integrated with method development for fulfilling this objective. This approach has successfully allowed the quality to be designed into the analytical processes by obtaining a deep understanding of the procedures. In this paper the AQbD workflow and its application in the development of methods to be used for pharmaceutical quality control have been treated and discussed. Recent publications regarding how AQbD has been applied in separation techniques were reviewed. The different development strategies have been also showcased, highlighting their advantages and disadvantages, in order to give a useful overview.
Journal of Pharmaceutical Innovation, 2010
An important aspect of a quality by design approach to pharmaceutical product formulation and process development is continuous quality verification. This is an innovative way of validating the process where manufacturing performance is continuously monitored, evaluated and adjusted as necessary. For new drug products, the body of knowledge accumulated through the development cycle and formalised via risk assessment forms the natural basis of this activity. This paper shows how multivariate tools can be used as part of a continuous quality verification approach for a new drug product relying on the information that summarises the control strategy, i.e. the subset of critical variables selected via risk assessment and the related proven acceptable ranges determined during developmental studies.
An insight on scientific and risk based approaches for drug product development
Recent regulations, to develop the drug products with scientific and risk based approaches such as QbD (quality by design), AQbD (analytical quality by design) and PAT (process analytical technology) that help to minimize manufacturing and analytical issues during commercialization, has enormous impact on the development of pharmaceutical process. These three scientific and risk-based approaches will minimize the amount of testing and ensures that the drug product (DP) complies with the essential GMP requirements. The implementation of QbD, AQbD and PAT approaches increases the product quality, safety and efficiency. From a manufacturer's perspective, this would mean significant reduction in production cycle times by using online, inline and/or at-line measurements, minimizing rejects, scrap, reprocessing and human errors with complete knowledge of the product. This article illustrates the similarities and contradictions in the 'Traditional Approach' and 'The Scientific & Risk-based Approach' of development and manufacture of DPs.
Journal of Pharmaceutical Innovation, 2008
For good reason, quality by design (QbD) has become a topic of significant interest within the pharmaceutical industry. Whereas regulatory agencies and standardsetting organizations are moving swiftly to establish QbD guidance relevant to the needs of pharmaceutical manufacturing, much of the core science of QbD was established long ago by Dr. Genichi Taguchi and other leaders in the field of quality management. In order for the pharmaceutical industry to fully capitalize on QbD, new methods for quantitatively assessing product quality need to be established. This perspective article presents a risk-based strategy for quality assessment which uses model-based simulation to link variation in drug product parameters and clinical performance. This work is intended to provide background and introduction for a series of manuscripts dealing with QbD based on probabilistic risk assessment.
A Bayesian Approach to Pharmaceutical Product Quality Risk Quantification
Informatica, 2011
The FDA's Quality by Design initiative and associated design space construct (ICH, 2009), have stimulated the use of quantitative methods, mathematical and statistical models, and designed experiments in the process of drug development and manufacture. For a given drug product, the design space may be interpreted as the constrained region of the manufacturing operating variable space within which assurance can be provided that drug product quality specifications will be met. It is now understood, at least conceptually, that this assurance is not deterministic, rather it must be stated in probabilistic terms. In this paper, we report on the use of Bayesian methods to develop a suitable risk metric based on both mathematical and statistical models of the manufacturing processes and product properties. The Bayesian estimation is carried out to determine the joint posterior distribution of the probability of the product meeting quality specifications. The computations are executed using a novel Variational Bayes approximation. In this paper the direct computational approach using this approximation is compared to the widely used but computationally very intensive Markov Chain Monte Carlo method. The approach is illustrated using experimental data and models drawn from a recent QbD study on the drug gabapentin in which the authors were participants.
Pharmaceutical Quality-by-Design (QbD): Basic Principles
2020
In this era of competition, quality is a prime factor of importance. The principles of quality have been described by the ICH guidelines: Q8 Pharmaceutical development, Q9 Pharmaceutical quality risk management and Q10 Pharmaceutical quality system. Quality-by-design is a recent concept which has been added as an annex to ICH Q8. It is a scientific approach that helps to build in quality into the product rather than mere testing of the final product. For the implementation of QbD various tools are needed to be used which have been described briefly. Risk assessment approaches, process analytical technology tools and mathematical, statistical and continuous improvement tools are important elements of quality by design, which mainly focus on the identification of critical parameters and defining a design space statistically. The basic principles of these three ICH guidelines with regard to quality of pharmaceutical products have been briefly discussed.
Risk Analysis of Controlled Release Tablet Formulation by Six Sigma Technique
Proceedings of The 1st Electronic Conference on Pharmaceutical Sciences, 2011
Failure Mode and Effects Analysis (FMEA) is a procedure which is performed after a failure mode effects analysis to classify each potential failure effect according to its severity and probability of occurrence. FMEA is a systematic proactive method for evaluating a process to identify where and how it might fail and to assess the relative impact of different failures, in order to identify the part of the process that are most in need of change. Subjected a controlled release tablet formulation to a Failure Mode and Effects Analysis, including technical risks as well as risks related to human failure which broke down the formulation into the process steps and identified possible failure modes for each step. Each failure mode was ranked on estimated frequency of occurrence (0), probability that the failure would remain undetected later in the process (D) and severity (S). Human errors turned out to be the most common cause of failure modes. Failure risks were calculated by Risk Priority Number (RPNs) O*D*S. Failure modes with the highest RPN scores were subjected to corrective action and FMEA was repeated. FMEA is particularly useful in evaluating a new process prior to implementation and in assessing the impact of a proposed change to an existing process which depends on product and process understanding. FMEA is most effective when it occurs before a design is released rather than "after the fact". The aim of this paper is to demonstrate an application of process failure mode and effect analysis (process FMEA) as a performance improvement tool, based on a case analysis of process improvement conducted in an early drug discovery project.
Journal of Pharmaceutical Sciences, 2010
The absence of a unanimous, industry-specific definition of quality is, to a certain degree, impeding the progress of ongoing efforts to ''modernize'' the pharmaceutical industry. This work was predicated on requests by Dr. Woodcock (FDA) to re-define pharmaceutical quality in terms of risk by linking production characteristics to clinical attributes. A risk simulation platform that integrates population statistics, drug delivery system characteristics, dosing guidelines, patient compliance estimates, production metrics, and pharmacokinetic, pharmacodynamic, and in vitro-in vivo correlation models to investigate the impact of manufacturing variability on clinical performance of a model extended-release theophylline solid oral dosage system was developed. Manufacturing was characterized by inter-and intra-batch content uniformity and dissolution variability metrics, while clinical performance was described by a probabilistic pharmacodynamic model that expressed the probability of inefficacy and toxicity as a function of plasma concentrations. Least-squares regression revealed that both patient compliance variables, percent of doses taken and dosing time variability, significantly impacted efficacy and toxicity. Additionally, intra-batch content uniformity variability elicited a significant change in risk scores for the two adverse events and, therefore, was identified as a critical quality attribute. The proposed methodology demonstrates that pharmaceutical quality can be recast to explicitly reflect clinical performance. ß
A Semiquantitative Risk Assessment Methodology Fit for Biopharmaceutical Life Cycle Stages
PDA journal of pharmaceutical science and technology , 2020
This paper introduces an innovative risk assessment tool, a semiquantitative risk determination (SQRD) method designed to address risk on the operational and organizational level with a distinct patient safety perspective. Quality Risk Management (ICH Q9) is a systematic process for the assessment, control, communication, and review of risks to the quality of the drug (medicinal) product across the product life cycle. SQRD is a systematic data-driven risk assessment tool. It is of practical significance to have a risk assessment tool that directly links to patient safety attributes. The SQRD methodology has six distinctive steps that are customized to address patient impact and non-patient impact quality attributes. The target was to develop and utilize an advanced risk assessment tool that is reliable, robust, objective, and data-driven. SQRD can be applied to batch production, continuous process, or a hybrid of the two, and at any stage of the product life cycle such as early development, pilot formulation development, process validation, or commercial manufacturing. The output of SQRD can help in shaping and optimizing the product control strategy. The exercise enables systematic mitigation of the identified risks. The proposed SQRD tool systematically evaluates data and scientifically establishes reliable, robust, and efficient risk assessments.