Unit operation optimization for the manufacturing of botanical injections using a design space approach: a case study of water precipitation

Design Space Calculation and Continuous Improvement Considering a Noise Parameter: A Case Study of Ethanol Precipitation Process Optimization for Carthami Flos Extract

The optimization of process parameters in the pharmaceutical industry is often carried out according to the Quality by Design (QbD) concept. QbD also emphasizes that continuous improvement should be performed in life cycle management. Process parameters that are difficult to control in actual production can be regarded as noise parameters. In this study, based on the QbD concept, the ethanol precipitation process of Carthami Flos extract was optimized, considering a noise parameter. The density of the concentrated extract, ethanol concentration, the volume ratio of ethanol to concentrated extract, stirring time after ethanol addition, and refrigeration temperature were selected as critical process parameters (CPPs), using a definitive screening design. The mathematical models among CPPs and evaluation indicators were established. Considering that the refrigeration temperature of industrial ethanol precipitation is often difficult to control with seasonal changes, refrigeration temperature was treated as a noise parameter. A calculation method for the design space in the presence of the noise parameter was proposed. The design space was calculated according to the probability of reaching the standards of evaluation indicators. Controlling parameters within the design space was expected to reduce the influence of noise parameter fluctuations on the quality of the ethanol precipitation supernatant. With more data obtained, the design space was updated. In industry, it is also recommended to adopt a similar idea: that is, continuing to collect industrial data and regularly updating mathematical models, which can further update the design space and make it more stable and reliable.

Critical pharmaceutical process identification considering chemical composition, biological activity, and batch-to-batch consistency: A case study of notoginseng total saponins

Objective

Critical pharmaceutical process identification (CPPI) is an important step in the implementation of quality by design concept to traditional Chinese medicines (TCMs). Risk assessment methods are usually used in CPPI. However, risk evaluation is usually subjective. The purpose of this work is to present a more objective CPPI method.

Methods

A CPPI method considering chemical composition, biological activity, and batch-to-batch consistency was presented in this work. The manufacturing process of notoginseng total saponins (NTS) was investigated as an example. The changes of chemical composition, biological activity, and chemical composition consistency after main processes were measured and compared. A significant change of them indicated a critical process.

Results

After extraction process and chromatography process, saponin purity and chemical composition similarity remarkably increased, and saponin content variations decreased. Thrombin inhibitory activity was remarkably decreased after chromatography process. Because of the large influences on NTS quality, extraction process and chromatography process were identified to be critical processes of NTS.

Conclusion

Based on a comprehensive and objective examination of the role of each process, critical pharmaceutical processes can be identified. A similar method can also be applied to other TCM processes.

The development of an herbal material quality control strategy considering the effects of manufacturing processes

Background

Quality by design (QbD) is an advanced drug quality control concept that has been gradually implemented in the optimization of manufacturing processes of Chinese medicines. However, the variation of Chinese medicinal material quality has rarely been considered in published works. Because manufacturing processes may lower the variation introduced through different batches of materials, a material quality control strategy should be developed considering the influences of manufacturing processes.

Methods

In this work, the processes of extraction, concentration, water precipitation, and chromatography for notoginseng total saponin (NTS) production were investigated while considering Panax notoginseng quality variation as a sample. Ten process parameters were studied simultaneously using a definitive screening design. After the process critical quality attributes (CQAs) were determined, critical process parameters (CPPs) and critical material attributes (CMAs) were identified simultaneously. Then, models utilizing the CMAs, CPPs, and process CQAs were developed. The design space was then calculated using a Monte Carlo simulation method with an acceptable probability of 0.90. A material quality control strategy considering the influences of manufacturing processes was proposed.

Results

The ginsenoside Rd purity and total saponin purity in the eluate were identified as process CQAs. The ethanol solution concentration used for extraction, the ethanol solution concentration used for elution, and elution time were identified as CPPs. The extractable dry matter content of Panax notoginseng was one of the CMAs. The extractable contents of notoginsenoside R₁, ginsenoside Rg₁, ginsenoside Rb₁, and ginsenoside Rd were the other CMAs. The inequalities implemented to discriminate the high quality and low quality of Panax notoginseng were developed according to the NTS standard of the Xuesaitong injection. Low quality Panax notoginseng should not be released for NTS production. High quality Panax notoginseng can be treated with feasible manufacturing processing parameters. Verification experiments were carried out successfully for 2 batches of high quality Panax notoginseng.

Conclusions

In this work, a quality control strategy for herbal materials was developed considering the matching of process characteristics and material quality attributes. This strategy is promising for application to other Chinese medicines.

Process characterization strategy for a precipitation step for host cell protein reduction

Process characterization using QbD approaches has rarely been described for precipitation steps used for impurity removal in biopharmaceutical processes. We propose a two‐step approach for process characterization in which the first step focuses on product quality and the second focuses on process performance. This approach provides an efficient, streamlined strategy for the characterization of precipitation steps under the Quality by Design paradigm. This strategy is demonstrated by a case study for the characterization of a precipitation using sodium caprylate to reduce host cell proteins (HCP) during a monoclonal antibody purification process. Process parameters were methodically selected through a risk assessment based on prior development data and scientific knowledge described in the literature. The characterization studies used two multivariate blocks to decouple and distinguish the impact of product quality (e.g., measured HCP of the recovered product from the precipitation) and process performance (e.g., step yield). Robustness of the precipitation step was further demonstrated through linkage studies across the overall purification process. HCP levels could be robustly reduced to ≤100 ppm in the drug substance when the precipitation step operated within an operation space of ≤1% (m/v) sodium caprylate, pH 5.0–6.0, and filter flux ≤300 L/m²‐hr for a load HCP concentration up to 19,000 ppm. This two‐step approach for characterization of precipitation steps has several advantages, including tailoring of the experimental design and scale‐down model to the intended purpose for each step, use of a manageable number of experiments without compromising scientific understanding, and limited time and material consumption.

Chemical analysis, pharmacological activity and process optimization of the proportion of bilobalide and ginkgolides in Ginkgo biloba extract

Variations on the efficacy of commercial Ginkgo biloba preparations have been reported, although all the products follow the same standards. Terpene trilactones (TTLs), including bilobalide (BB) and ginkgolides, are one of the main active components in G. biloba extract and have been received the most attention due to their chemical uniqueness and their importance for quality control. A plenty of studies demonstrated that BB and ginkgolides display differential activities on various biological processes. However, the influence of different ratios of BB and ginkgolides on the efficacy of TTLs has not been detected yet. The aims of this study were: (1) to test whether different ratios of BB and ginkgolides existed in commercial G. biloba preparations; (2) to detect the influence of different ratios of BB and ginkgolides on the in vivo efficacy of TTLs; and (3) to optimize the extraction process of G. biloba to approach the better BB and ginkgolides ratio with the maximum in vivo effects. First, the content and proportion of BB and ginkgolides in various G. biloba preparations were quantified by HPLC-MS analysis. As the results, an obvious fluctuation in the proportion of BB and ginkgolides was observed in the preparations from different commercial suppliers. The ratio was ranged from 0.3 to 0.8. Second, a zebrafish thrombosis model was used to evaluate the antithrombotic effects of different ratios of BB and ginkgolides. The result showed that the proportion of BB and ginkgolides at 1:2 produced the maximum antithrombotic effects. Third, the extraction process of G. biloba was optimized using a design space technique aiming to approach the best BB and ginkgolides ratio obtained from zebrafish experiment. The extraction process was modeled based on the results of Box-Behnken designed experiments. Design space was then calculated using a probability-based method. Within this design space, G. biloba extraction process can be guaranteed to achieve the better BB and ginkgolides ratio with high assurance. Normal operation space for G. biloba extraction process was recommended as ethanol concentration of 50% to 70%, liquid-to-solid ratio of 5.6 mL/g to 7.3 mL/g, and extraction time of 2.2 h to 3.0 h. This work not only suggest that the proportion of BB and ginkgolides should be used as a quality control index in ginkgo preparations besides the content of TTLs, but also provide a way to approach it with the extraction process parameters controlled in the normal operation ranges.

Optimization of a Coupling Process for Insulin Degludec According to a Quality by Design (QbD) Paradigm

This case study described a successful application of the quality by design (QbD) principles to a coupling process development of insulin degludec. Failure mode effects analysis (FMEA) risk analysis was first used to recognize critical process parameters (CPPs). Five CPPs, including coupling temperature (Temp), pH of desB30 solution (pH), reaction time (Time), desB30 concentration (Conc), and molar equivalent of ester per mole of desB30 insulin (MolE), were then investigated using a fractional factorial design. The curvature effect was found significant, indicating the requirement of second-order models. Afterwards, a central composite design was built with an augmented star and center points study. Regression models were developed for the CPPs to predict the purity and yield of predegludec using above experimental data. The R² and adjusted R² were higher than 96 and 93% for the two models respectively. The Q² values were more than 80% indicating a good predictive ability of models. MolE was found to be the most significant factor affecting both yield and purity of predegludec. Temp, pH, and Conc were also significant for predegludec purity, while Time appeared to remarkably influence the yield model. The multi-dimensional design space and normal operating region (NOR) with a robust setpoint were determined using a probability-based Monte-Carlo simulation method. The verified experimental results showed that the design space was reliable and effective. This study enriches the understanding of acetylation process and is instructional to other complicated operations in biopharmaceutical engineering.

Chromatographic elution process design space development for the purification of saponins in Panax notoginseng extract using a probability-based approach

A Monte Carlo method was used to develop the design space of a chromatographic elution process for the purification of saponins in Panax notoginseng extract. During this process, saponin recovery ratios, saponin purity, and elution productivity are determined as process critical quality attributes, and ethanol concentration, elution rate, and elution volume are identified as critical process parameters. Quadratic equations between process critical quality attributes and critical process parameters were established using response surface methodology. Then probability-based design space was computed by calculating the prediction errors using Monte Carlo simulations. The influences of calculation parameters on computation results were investigated. The optimized calculation condition was as follows: calculation step length of 0.02, simulation times of 10 000, and a significance level value of 0.15 for adding or removing terms in a stepwise regression. Recommended normal operation region is located in ethanol concentration of 65.0-70.0%, elution rate of 1.7-2.0 bed volumes (BV)/h and elution volume of 3.0-3.6 BV. Verification experiments were carried out and the experimental values were in a good agreement with the predicted values. The application of present method is promising to develop a probability-based design space for other botanical drug manufacturing process.

Design space development for the extraction process of Danhong injection using a Monte Carlo simulation method

A design space approach was applied to optimize the extraction process of Danhong injection. Dry matter yield and the yields of five active ingredients were selected as process critical quality attributes (CQAs). Extraction number, extraction time, and the mass ratio of water and material (W/M ratio) were selected as critical process parameters (CPPs). Quadratic models between CPPs and CQAs were developed with determination coefficients higher than 0.94. Active ingredient yields and dry matter yield increased as the extraction number increased. Monte-Carlo simulation with models established using a stepwise regression method was applied to calculate the probability-based design space. Step length showed little effect on the calculation results. Higher simulation number led to results with lower dispersion. Data generated in a Monte Carlo simulation following a normal distribution led to a design space with a smaller size. An optimized calculation condition was obtained with 10000 simulation times, 0.01 calculation step length, a significance level value of 0.35 for adding or removing terms in a stepwise regression, and a normal distribution for data generation. The design space with a probability higher than 0.95 to attain the CQA criteria was calculated and verified successfully. Normal operating ranges of 8.2-10 g/g of W/M ratio, 1.25-1.63 h of extraction time, and two extractions were recommended. The optimized calculation conditions can conveniently be used in design space development for other pharmaceutical processes.

Optimization of the ethanol recycling reflux extraction process for saponins using a design space approach

A solvent recycling reflux extraction process for Panax notoginseng was optimized using a design space approach to improve the batch-to-batch consistency of the extract. Saponin yields, total saponin purity, and pigment yield were defined as the process critical quality attributes (CQAs). Ethanol content, extraction time, and the ratio of the recycling ethanol flow rate and initial solvent volume in the extraction tank (RES) were identified as the critical process parameters (CPPs) via quantitative risk assessment. Box-Behnken design experiments were performed. Quadratic models between CPPs and process CQAs were developed, with determination coefficients higher than 0.88. As the ethanol concentration decreases, saponin yields first increase and then decrease. A longer extraction time leads to higher yields of the ginsenosides Rb1 and Rd. The total saponin purity increases as the ethanol concentration increases. The pigment yield increases as the ethanol concentration decreases or extraction time increases. The design space was calculated using a Monte-Carlo simulation method with an acceptable probability of 0.90. Normal operation ranges to attain process CQA criteria with a probability of more than 0.914 are recommended as follows: ethanol content of 79-82%, extraction time of 6.1-7.1 h, and RES of 0.039-0.040 min-1. Most of the results of the verification experiments agreed well with the predictions. The verification experiment results showed that the selection of proper operating ethanol content, extraction time, and RES within the design space can ensure that the CQA criteria are met.