2020
DOI: 10.1039/d0ra04111d
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Pharmacokinetic–pharmacodynamic modeling for Moutan Cortex/Moutan Cortex charcoal and the contributions of the chemical component using support vector regression with particle swarm optimization

Abstract: Moutan Cortex (MC) and Moutan Cortex charcoal (MCC) are two kinds of Chinese medicinal materials and effective substances are still unclear. A PK-PD model for MC/MCC is proposed using the support vector regression with particle swarm optimization.

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Cited by 4 publications
(3 citation statements)
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“…These two compounds demonstrated rich plasma exposure in BHH rats after processing, so it can be inferred that processing may promote the absorption of the blood coagulant component (5‐HMF and gallic acid) and inhibit absorption of the blood circulation components (oxypaeoniflora, quercetin and 3, 8‐dihydroxy‐2‐ methylchromone), which clarifies the effect of processing on the action of drugs in the body. In addition, The pharmacokinetic–pharmacodynamic experiments of RMC/PMC also suggest that benzoic acid and quercetin may be the main pharmacological substances for RMC to promote blood circulation in RMC, and gallic acid and 5‐HMF may be the main effective substances for hemostasis in PMC (Pan, Zhou, Zhou, Huang, & Meng, 2020), which verified the pharmacokinetic results. Moreover, 1 H NMR‐based metabonomic revealed the protective effect of PMC on BHH rats.…”
Section: Resultssupporting
confidence: 56%
“…These two compounds demonstrated rich plasma exposure in BHH rats after processing, so it can be inferred that processing may promote the absorption of the blood coagulant component (5‐HMF and gallic acid) and inhibit absorption of the blood circulation components (oxypaeoniflora, quercetin and 3, 8‐dihydroxy‐2‐ methylchromone), which clarifies the effect of processing on the action of drugs in the body. In addition, The pharmacokinetic–pharmacodynamic experiments of RMC/PMC also suggest that benzoic acid and quercetin may be the main pharmacological substances for RMC to promote blood circulation in RMC, and gallic acid and 5‐HMF may be the main effective substances for hemostasis in PMC (Pan, Zhou, Zhou, Huang, & Meng, 2020), which verified the pharmacokinetic results. Moreover, 1 H NMR‐based metabonomic revealed the protective effect of PMC on BHH rats.…”
Section: Resultssupporting
confidence: 56%
“…We inferred that the reason why PLSR attained both the positive–negative correlation and contribution rate, but PCA only acquired the latter may be associated with that difference. Due to the complexity of model and the small sample size, the application of BPNN may result in over-fitting [ 34 ]. The adoption of cross-validation in PLSR effectively avoided the over-fitting, meanwhile, PLSR may exhibit better applicability to the research with a modest amount of sample [ 35 , 36 ].…”
Section: Discussionmentioning
confidence: 99%
“…46 To do this, they used a bootstrap method upon point estimates obtained by a derivative‐based nonlinear least squares (NLS) approach or GA. Their comparison showed that the parameter estimates obtained by GA are quite unbiased compared to those obtained by NLS. Recently, Pan et al 47 developed a support vector regression model with PSO (PSO‐SVR) to simultaneously characterize the PKs and PDs of Moutan Cortex and Moutan Cortex charcoal widely used in traditional Chinese medicine. In PSO‐SVR, PSO was used to find parameters that fit the chemical component to the drug efficacy by optimizing the support vector regression model.…”
Section: Parameter Estimation Via Psomentioning
confidence: 99%