Design Space Development for the Extraction Process of Danhong Injection Using a Monte Carlo Simulation Method

Gong, Xingchu; Li, Yao; Chen, Huali; Qu, Haibin

doi:10.1371/journal.pone.0128236

Cited by 15 publications

(8 citation statements)

References 31 publications

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“…Actually, the design space approach based on chemical constituents (e.g. contents and yields) has been used to optimize manufacturing process of botanical drugs 4 , 38 . However, establishing a “potency space” may result in better botanical quality control as biological assays are more clinically relevant.…”

Section: Discussionmentioning

confidence: 99%

A multiple biomarker assay for quality assessment of botanical drugs using a versatile microfluidic chip

et al. 2017

Sci Rep

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Quality control is critical for ensuring the safety and effectiveness of drugs. Current quality control method for botanical drugs is mainly based on chemical testing. However, chemical testing alone may not be sufficient as it may not capture all constituents of botanical drugs. Therefore, it is necessary to establish a bioassay correlating with the drug’s known mechanism of action to ensure its potency and activity. Herein we developed a multiple biomarker assay to assess the quality of botanicals using microfluidics, where enzyme inhibition was employed to indicate the drug’s activity and thereby evaluate biological consistency. This approach was exemplified on QiShenYiQi Pills using thrombin and angiotensin converting enzyme as “quality biomarkers”. Our results demonstrated that there existed variations in potency across different batches of the intermediates and preparations. Compared with chromatographic fingerprinting, the bioassay provided better discrimination ability for some abnormal samples. Moreover, the chip could function as “affinity chromatography” to identify bioactive phytochemicals bound to the enzymes. This work proposed a multiple-biomarker strategy for quality assessment of botanical drugs, while demonstrating for the first time the feasibility of microfluidics in this field.

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Section: Discussionmentioning

confidence: 99%

A multiple biomarker assay for quality assessment of botanical drugs using a versatile microfluidic chip

et al. 2017

Sci Rep

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“…Based on the specific goals of CMAs, a Monte-Carlo method was performed using an in-house MATLAB program (R2016a, Version 9.0, The MathWorks Inc., USA) to calculate the design space[ 30 ]. The detailed calculation processes were described in previous work[ 31 ].…”

Section: Methodsmentioning

confidence: 99%

A novel quality by design approach for developing an HPLC method to analyze herbal extracts: A case study of sugar content analysis

Shao

Cao

et al. 2018

PLoS ONE

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The aim of this study was to present a novel analytical quality by design (AQbD) approach for developing an HPLC method to analyze herbal extracts. In this approach, critical method attributes (CMAs) and critical method parameters (CMPs) of the analytical method were determined using the same data collected from screening experiments. The HPLC-ELSD method for separation and quantification of sugars in Codonopsis Radix extract (CRE) samples and Astragali Radix extract (ARE) samples was developed as an example method with a novel AQbD approach. Potential CMAs and potential CMPs were found with Analytical Target Profile. After the screening experiments, the retention time of the D-glucose peak of CRE samples, the signal-to-noise ratio of the D-glucose peak of CRE samples, and retention time of the sucrose peak in ARE samples were considered CMAs. The initial and final composition of the mobile phase, flow rate, and column temperature were found to be CMPs using a standard partial regression coefficient method. The probability-based design space was calculated using a Monte-Carlo simulation method and verified by experiments. The optimized method was validated to be accurate and precise, and then it was applied in the analysis of CRE and ARE samples. The present AQbD approach is efficient and suitable for analysis objects with complex compositions.

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“…The boundaries of the design space would then be chosen such that the overall rate of defects is smaller than a given threshold (e.g., 5%). Several approaches have been proposed to this end, e.g., Monte-Carlo simulations, Bayesian posterior predictive intervals, prediction, and tolerance intervals [7,[70][71][72].…”

Section: Determination Of the Design Space Boundaries-edge Of Failurementioning

confidence: 99%

Working within the Design Space: Do Our Static Process Characterization Methods Suffice?

et al. 2020

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The Process Analytical Technology initiative and Quality by Design paradigm have led to changes in the guidelines and views of how to develop drug manufacturing processes. On this occasion the concept of the design space, which describes the impact of process parameters and material attributes on the attributes of the product, was introduced in the ICH Q8 guideline. The way the design space is defined and can be presented for regulatory approval seems to be left to the applicants, among who at least a consensus on how to characterize the design space seems to have evolved. The large majority of design spaces described in publications seem to follow a “static” statistical experimentation and modeling approach. Given that temporal deviations in the process parameters (i.e., moving within the design space) are of a dynamic nature, static approaches might not suffice for the consideration of the implications of variations in the values of the process parameters. In this paper, different forms of design space representations are discussed and the current consensus is challenged, which in turn, establishes the need for a dynamic representation and characterization of the design space. Subsequently, selected approaches for a dynamic representation, characterization and validation which are proposed in the literature are discussed, also showcasing the opportunity to integrate the activities of process characterization, process monitoring and process control strategy development.

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Design Space Development for the Extraction Process of Danhong Injection Using a Monte Carlo Simulation Method

Cited by 15 publications

References 31 publications

A multiple biomarker assay for quality assessment of botanical drugs using a versatile microfluidic chip

A multiple biomarker assay for quality assessment of botanical drugs using a versatile microfluidic chip

A novel quality by design approach for developing an HPLC method to analyze herbal extracts: A case study of sugar content analysis

Working within the Design Space: Do Our Static Process Characterization Methods Suffice?

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