Application of quality by design to the manufacture of a multiparticulate prednisone dosage form
- Authors: Manda, Arthur
- Date: 2020-04
- Subjects: Drugs -- Quality control , Drugs -- Design -- Quality control , Drugs -- Dosage forms , Drug development -- Quality control , Pharmaceutical industry -- Quality control , Prednisone , High throughput screening (Drug development)
- Language: English
- Type: text , Thesis , Masters , MSc (Pharmacy)
- Identifier: http://hdl.handle.net/10962/117986 , vital:34583
- Description: For many years, quality by testing was the only approach to guarantee quality of drug products before the Food and Drug Administration launched the concept of current Good Manufacturing Practice. In order to gain more knowledge of the manufacturing process, a new system known as Quality by Design was introduced into the pharmaceutical industry. Quality by Design is based on thorough understanding of how materials, process parameters and interaction thereof impact final product quality. Quality by Design is a systematic approach to product development which ensures that quality is built into a product during product development and not just tested into it. The aim of Quality by Design is to achieve optimum product quality with consistent dosage form performance and minimal risk of failure in patients. The objective of these studies was to implement a Quality by Design approach to establish a design space for the development and manufacture of a safe, effective and stable multi-partite solid oral dosage form for prednisone as an alternative to currently marketed prednisone formulations. Multi-particulate dosage forms offer significant advantages over conventional technologies. In addition to lowering the incidence of gastrointestinal irritation they exhibit a reduced risk of dose dumping and a large surface area which favours dissolution. Furthermore, their free flowing nature facilitates reproducible capsule filling and consequently uniformity of dosing. Different multi-particulate dosage forms exist however a multiple-unit pellet system was investigated during these studies. Quality by Design principles were used to develop and establish a reversed-phase high performance liquid chromatographic method for quantifying prednisone from solid oral dosage forms. A Central Composite Design was used to generate multivariate experiments and to investigate the impact of input variables on the quality and performance of the analytical method. The optimized method was validated according to International Council for Harmonization guidelines and was found to be linear, precise, accurate and specific for the quantitation of prednisone. Pre-formulation studies were conducted and included the assessment of particle size, particle shape, powder flow properties and compatibility studies. Carr’s index, Hausner ratio and the Angle of Repose were used to evaluate powder flow properties and results generated from all studies suggest the need for adding a glidant and lubricant to improve pellet flow. The images generated from Scanning Electron Microscopy were used to analyze particle shape and size. Differential Scanning Calorimetry and Fourier Transform Infrared Spectroscopy were used to evaluate API-excipient compatibility. All excipients investigated were found to be compatible with prednisone and suitable for formulation development studies. Extrusion-spheronization was used to manufacture prednisone pellets. Extrusion-spheronization is a multi-step process involving many factors. Quality risk management tools particularly an Ishikawa Fishbone (cause and effect) diagram and failure mode and effects analysis were used to narrow down potentially significant factors to a reasonable number that could be investigated experimentally. Risk priority numbers were used to quantify risk and factors above a set threshold value were considered to be of high risk. A total of eleven risk factors were identified as high. A Plackett-Burman study was conducted to narrow down the eleven high risk factors to identify the most impactful factors viz., microcrystalline cellulose content, sodium starch glycolate content, extrusion speed and spheronization time. Evaluation of four factors was carried over to optimization studies using a Box-Behnken Design and following identifaction of the optimum process settings and excipient content a design space for the manufacture of a multi-partite dosage form containing prednisone was established.
- Full Text:
- Date Issued: 2020-04
- Authors: Manda, Arthur
- Date: 2020-04
- Subjects: Drugs -- Quality control , Drugs -- Design -- Quality control , Drugs -- Dosage forms , Drug development -- Quality control , Pharmaceutical industry -- Quality control , Prednisone , High throughput screening (Drug development)
- Language: English
- Type: text , Thesis , Masters , MSc (Pharmacy)
- Identifier: http://hdl.handle.net/10962/117986 , vital:34583
- Description: For many years, quality by testing was the only approach to guarantee quality of drug products before the Food and Drug Administration launched the concept of current Good Manufacturing Practice. In order to gain more knowledge of the manufacturing process, a new system known as Quality by Design was introduced into the pharmaceutical industry. Quality by Design is based on thorough understanding of how materials, process parameters and interaction thereof impact final product quality. Quality by Design is a systematic approach to product development which ensures that quality is built into a product during product development and not just tested into it. The aim of Quality by Design is to achieve optimum product quality with consistent dosage form performance and minimal risk of failure in patients. The objective of these studies was to implement a Quality by Design approach to establish a design space for the development and manufacture of a safe, effective and stable multi-partite solid oral dosage form for prednisone as an alternative to currently marketed prednisone formulations. Multi-particulate dosage forms offer significant advantages over conventional technologies. In addition to lowering the incidence of gastrointestinal irritation they exhibit a reduced risk of dose dumping and a large surface area which favours dissolution. Furthermore, their free flowing nature facilitates reproducible capsule filling and consequently uniformity of dosing. Different multi-particulate dosage forms exist however a multiple-unit pellet system was investigated during these studies. Quality by Design principles were used to develop and establish a reversed-phase high performance liquid chromatographic method for quantifying prednisone from solid oral dosage forms. A Central Composite Design was used to generate multivariate experiments and to investigate the impact of input variables on the quality and performance of the analytical method. The optimized method was validated according to International Council for Harmonization guidelines and was found to be linear, precise, accurate and specific for the quantitation of prednisone. Pre-formulation studies were conducted and included the assessment of particle size, particle shape, powder flow properties and compatibility studies. Carr’s index, Hausner ratio and the Angle of Repose were used to evaluate powder flow properties and results generated from all studies suggest the need for adding a glidant and lubricant to improve pellet flow. The images generated from Scanning Electron Microscopy were used to analyze particle shape and size. Differential Scanning Calorimetry and Fourier Transform Infrared Spectroscopy were used to evaluate API-excipient compatibility. All excipients investigated were found to be compatible with prednisone and suitable for formulation development studies. Extrusion-spheronization was used to manufacture prednisone pellets. Extrusion-spheronization is a multi-step process involving many factors. Quality risk management tools particularly an Ishikawa Fishbone (cause and effect) diagram and failure mode and effects analysis were used to narrow down potentially significant factors to a reasonable number that could be investigated experimentally. Risk priority numbers were used to quantify risk and factors above a set threshold value were considered to be of high risk. A total of eleven risk factors were identified as high. A Plackett-Burman study was conducted to narrow down the eleven high risk factors to identify the most impactful factors viz., microcrystalline cellulose content, sodium starch glycolate content, extrusion speed and spheronization time. Evaluation of four factors was carried over to optimization studies using a Box-Behnken Design and following identifaction of the optimum process settings and excipient content a design space for the manufacture of a multi-partite dosage form containing prednisone was established.
- Full Text:
- Date Issued: 2020-04
An artificial neural network approach to predict the effects of formulation and process variables on prednisone release from a multipartite system
- Manda, Arthur, Walker, Roderick B, Khamanga, Sandile M
- Authors: Manda, Arthur , Walker, Roderick B , Khamanga, Sandile M
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/183237 , vital:43933 , xlink:href="https://doi.org/10.3390/pharmaceutics11030109"
- Description: The impact of formulation and process variables on the in-vitro release of prednisone from a multiple-unit pellet system was investigated. Box-Behnken Response Surface Methodology (RSM) was used to generate multivariate experiments. The extrusion-spheronization method was used to produce pellets and dissolution studies were performed using United States Pharmacopoeia (USP) Apparatus 2 as described in USP XXIV. Analysis of dissolution test samples was performed using a reversed-phase high-performance liquid chromatography (RP-HPLC) method. Four formulation and process variables viz., microcrystalline cellulose concentration, sodium starch glycolate concentration, spheronization time and extrusion speed were investigated and drug release, aspect ratio and yield were monitored for the trained artificial neural networks (ANN). To achieve accurate prediction, data generated from experimentation were used to train a multi-layer perceptron (MLP) using back propagation (BP) and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) 57 training algorithm until a satisfactory value of root mean square error (RMSE) was observed. The study revealed that the in-vitro release profile of prednisone was significantly impacted by microcrystalline cellulose concentration and sodium starch glycolate concentration. Increasing microcrystalline cellulose concentration retarded dissolution rate whereas increasing sodium starch glycolate concentration improved dissolution rate. Spheronization time and extrusion speed had minimal impact on prednisone release but had a significant impact on extrudate and pellet quality. This work demonstrated that RSM can be successfully used concurrently with ANN for dosage form manufacture to permit the exploration of experimental regions that are omitted when using RSM alone.
- Full Text:
- Date Issued: 2019
- Authors: Manda, Arthur , Walker, Roderick B , Khamanga, Sandile M
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/183237 , vital:43933 , xlink:href="https://doi.org/10.3390/pharmaceutics11030109"
- Description: The impact of formulation and process variables on the in-vitro release of prednisone from a multiple-unit pellet system was investigated. Box-Behnken Response Surface Methodology (RSM) was used to generate multivariate experiments. The extrusion-spheronization method was used to produce pellets and dissolution studies were performed using United States Pharmacopoeia (USP) Apparatus 2 as described in USP XXIV. Analysis of dissolution test samples was performed using a reversed-phase high-performance liquid chromatography (RP-HPLC) method. Four formulation and process variables viz., microcrystalline cellulose concentration, sodium starch glycolate concentration, spheronization time and extrusion speed were investigated and drug release, aspect ratio and yield were monitored for the trained artificial neural networks (ANN). To achieve accurate prediction, data generated from experimentation were used to train a multi-layer perceptron (MLP) using back propagation (BP) and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) 57 training algorithm until a satisfactory value of root mean square error (RMSE) was observed. The study revealed that the in-vitro release profile of prednisone was significantly impacted by microcrystalline cellulose concentration and sodium starch glycolate concentration. Increasing microcrystalline cellulose concentration retarded dissolution rate whereas increasing sodium starch glycolate concentration improved dissolution rate. Spheronization time and extrusion speed had minimal impact on prednisone release but had a significant impact on extrudate and pellet quality. This work demonstrated that RSM can be successfully used concurrently with ANN for dosage form manufacture to permit the exploration of experimental regions that are omitted when using RSM alone.
- Full Text:
- Date Issued: 2019
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