A Mathematical Kinetic Model and Network Analysis for Multicomponent Dissolution Relationships during the Extraction of Natural Products

Traditional Chinese Medicine (TCM) has a long history and typical ethnic traits. Astragalus and Angelica are used in a natural product called a buyang huanwu decoctionand are considered to function as both food and medicine; such products are called a “homology of medicine and food”. In this study, we examined the complex extraction kinetics that occur during the preparation of the natural product BYHWD. Mathematical tools, including the Laplace transformation and Fick’s law, were used to set up kinetic equations for different components in a model of the decoction. We selected the five most important bioactive ingredients of the BYHWD to find the most important speed control component. The intensity and capacity process parameters of the model were determined. A kinetic model was used to quantitatively analyze the dissolution restriction mechanism among the major components. Further, a component–effect network relationship was established to study the interactions of different components during extraction, considering the integrative effect of TCM compositions. Finally, using network pharmacology, certain network parameters were determined through topological analysis. The results indicate that Astragaloside IV exerts the strongest control over the dissolution rates of other components. The BYHWD has a short average path and a high clustering coefficient. The theoretical and experimental results can be used to quantitatively simulate and optimize TCM extraction processes.

Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions

Purpose

To build a physiologically based pharmacokinetic (PBPK) model of the clinical OATP1B1/OATP1B3/BCRP victim drug rosuvastatin for the investigation and prediction of its transporter-mediated drug-drug interactions (DDIs).

Methods

The Rosuvastatin model was developed using the open-source PBPK software PK-Sim®, following a middle-out approach. 42 clinical studies (dosing range 0.002–80.0 mg), providing rosuvastatin plasma, urine and feces data, positron emission tomography (PET) measurements of tissue concentrations and 7 different rosuvastatin DDI studies with rifampicin, gemfibrozil and probenecid as the perpetrator drugs, were included to build and qualify the model.

Results

The carefully developed and thoroughly evaluated model adequately describes the analyzed clinical data, including blood, liver, feces and urine measurements. The processes implemented to describe the rosuvastatin pharmacokinetics and DDIs are active uptake by OATP2B1, OATP1B1/OATP1B3 and OAT3, active efflux by BCRP and Pgp, metabolism by CYP2C9 and passive glomerular filtration. The available clinical rifampicin, gemfibrozil and probenecid DDI studies were modeled using in vitro inhibition constants without adjustments. The good prediction of DDIs was demonstrated by simulated rosuvastatin plasma profiles, DDI AUC_last ratios (AUC_last during DDI/AUC_last without co-administration) and DDI C_max ratios (C_max during DDI/C_max without co-administration), with all simulated DDI ratios within 1.6-fold of the observed values.

Conclusions

A whole-body PBPK model of rosuvastatin was built and qualified for the prediction of rosuvastatin pharmacokinetics and transporter-mediated DDIs. The model is freely available in the Open Systems Pharmacology model repository, to support future investigations of rosuvastatin pharmacokinetics, rosuvastatin therapy and DDI studies during model-informed drug discovery and development (MID3).

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-021-03109-6.

Pharmacokinetic/Pharmacodynamic Modelling to Describe the Cholesterol Lowering Effect of Rosuvastatin in People Living with HIV

BACKGROUND

Rosuvastatin is a lipid-lowering agent widely prescribed in people living with HIV, which is actively transported into the liver, making it a potential victim of drug-drug interactions with antiretroviral agents.

OBJECTIVES

The aims of this study were to characterise the pharmacokinetic profile of rosuvastatin and to describe the relationship between rosuvastatin concentrations and non-high-density lipoprotein (HDL)-cholesterol levels in people living with HIV.

METHODS

A population pharmacokinetic model (NONMEM) was developed to quantify the influence of demographics, clinical characteristics and comedications on rosuvastatin pharmacokinetics. This model was combined with an indirect effect model to describe non-HDL-cholesterol measurements.

RESULTS

A two-compartment model with sequential zero- and first-order absorption best fitted the 154 rosuvastatin concentrations provided by 65 people living with HIV. None of the tested covariates significantly influenced rosuvastatin pharmacokinetics. A total of 403 non-HDL cholesterol values were available for pharmacokinetic-pharmacodynamic modelling. Baseline non-HDL cholesterol decreased by 14% and increased by 12% with etravirine and antiretroviral drugs with a known impact on the lipid profile (i.e. protease inhibitors, efavirenz, cobicistat), respectively. The baseline value was surprisingly 43% lower in people living with HIV aged 80 years compared with those aged 40 years. Simulations based on the covariate-free model predicted that, under standard rosuvastatin dosages of 5 mg and 20 mg once daily, 31% and 64% of people living with HIV would achieve non-HDL-cholesterol targets, respectively.

CONCLUSIONS

The high between-subject variability that characterises both rosuvastatin pharmacokinetic and pharmacodynamic profiles remained unexplained after the inclusion of usual covariates. Considering its limited potential for drug-drug interactions with antiretroviral agents and its potent lipid-lowering effect, rosuvastatin prescription appears safe and effective in people living with HIV with hypercholesterolaemia.

CLINICAL TRIAL REGISTRATION NO

NCT03515772.

Comparative and quantitative assessment on statin efficacy and safety: insights into inter-statin and inter-individual variability via dose- and exposure-response relationships

Introduction: Statins are prescribed widely for cholesterol-lowering therapy, but it is known that their efficacy and safety profiles vary, despite the shared pharmacophore and pharmacological target. The immense body of related clinical and preclinical data offers a unique opportunity to explore the possible factors underlying inter-statin and inter-individual variabilities.Area covered: Clinical and preclinical data from various statins were compiled with regard to the efficacy (cholesterol-lowering effect) and safety (muscle toxicity). Based on the compiled data, dose- and exposure-response relationships were explored to obtain mechanistic and quantitative insights into the variations in the efficacy and safety profiles of statins.Expert opinion: Our analyses indicated that the inter-statin variability in the cholesterol-lowering effect may be mainly attributable to variations in potency of inhibition of the pharmacological target, rather than variations in drug exposure at the site of drug action. However, the drug exposure at the sites of drug action (i.e., the liver for efficacy and the muscle for safety) may contribute to the differences in the efficacy and safety observed in individual patients.

Application of the relationship between pharmacokinetics and pharmacodynamics in drug development and therapeutic equivalence: a PEARRL review

Objectives

The objective of this review was to provide an overview of pharmacokinetic/pharmacodynamic (PK/PD) models, focusing on drug-specific PK/PD models and highlighting their value added in drug development and regulatory decision-making.

Key findings

Many PK/PD models, with varying degrees of complexity and physiological understanding have been developed to evaluate the safety and efficacy of drug products. In special populations (e.g. paediatrics), in cases where there is genetic polymorphism and in other instances where therapeutic outcomes are not well described solely by PK metrics, the implementation of PK/PD models is crucial to assure the desired clinical outcome. Since dissociation between the pharmacokinetic and pharmacodynamic profiles is often observed, it is proposed that physiologically based pharmacokinetic and PK/PD models be given more weight by regulatory authorities when assessing the therapeutic equivalence of drug products.

Summary

Modelling and simulation approaches already play an important role in drug development. While slowly moving away from ‘one-size fits all’ PK methodologies to assess therapeutic outcomes, further work is required to increase confidence in PK/PD models in translatability and prediction of various clinical scenarios to encourage more widespread implementation in regulatory decision-making.

The Adherence Rate Threshold is Drug Specific

Introduction

Patient adherence to a medication regimen is usually expressed as an adherence rate, defined as the proportion of prescribed doses actually taken. An adherence rate threshold, above which the therapeutic effect is maintained, is typically assigned an arbitrary value, commonly 0.8.

Objective

Here, we determined the value of the adherence rate threshold objectively in different drugs of the same class, using statins as an example.

Methods

We used pharmacokinetic/pharmacodynamic (PK/PD) modeling to predict serum levels of low-density lipoprotein cholesterol (LDL-C) in patients taking simvastatin 20 mg or atorvastatin 5 mg once daily for 30 days. LDL-C reduction was modeled for adherence rates of 1.0, 0.8, 0.6, 0.4, and 0.2. The results were expressed as the percentage of time spent at the LDL-C goal (< 70 mg/dL). The adherence rate threshold was defined as the minimum adherence rate that resulted in the same amount of time at goal as perfect adherence (i.e., a rate of 1.0).

Results

For simvastatin, an adherence rate of 0.8 resulted in a significant decrease in time at the LDL-C goal compared to perfect adherence (54.8% versus 85.1%; P < 0.001), and rates < 0.8 resulted in progressively less time at goal. For atorvastatin, the rates of 0.8 and 0.6 resulted in essentially the same amount of time at goal as perfect adherence (87.8% and 87.7%, respectively, versus 88.1%; P > 0.05 for both), with less time at goal only occurring at rates ≤ 0.4 (P < 0.001). Thus, the adherence rate thresholds are > 0.8 for simvastatin and between 0.4 and 0.6 for atorvastatin.

Conclusion

These results indicate that a value of 0.8 cannot be applied universally.

Pharmacokinetics and Pharmacodynamics of Meloxicam in East Asian Populations: The Role of Ethnicity on Drug Response

We aimed to reanalyze the differences in the pharmacokinetics (PKs) of meloxicam in East Asian populations based on a population approach using previously published data and to investigate the factors found in population PK analysis that affect the pharmacodynamics (PDs) of meloxicam. Population PK analysis was performed in 119 healthy male subjects (30 Japanese, 30 Chinese, 29 Korean, and 30 white) under strictly controlled trial conditions with regulated meals and a single lot of the drug. We found that CYP2C9 genotype and lean body mass were statistically significant predictors of clearance and volume of distribution, respectively. A statistical significant difference in the PK parameters between ethnic groups could not be identified. Simulations using PK/PD models showed that CYP2C9 genotype is the factor that affects the PDs of meloxicam. The genetic polymorphisms highlighted in this study would be beneficial for conducting clinical trials in East Asians with similar genetic backgrounds.

Highlighting Vitamin D Receptor-Targeted Activities of 1α,25-Dihydroxyvitamin D3 in Mice via Physiologically Based Pharmacokinetic-Pharmacodynamic Modeling

We expanded our published physiologically based pharmacokinetic model (PBPK) on 1α,25-dihydroxyvitamin D₃ [1,25(OH)₂D₃], ligand of the vitamin D receptor (VDR), to appraise VDR-mediated pharmacodynamics in mice. Since 1,25(OH)₂D₃ kinetics was best described by a segregated-flow intestinal model (SFM) that described a low/partial intestinal (blood/plasma) flow to enterocytes, with feedback regulation of its synthesis (Cyp27b1) and degradation (Cyp24a1) enzymes, this PBPK(SFM) model was expanded to describe the VDR-mediated changes (altered/basal mRNA expression) of target genes/responses with the indirect response model. We examined data on 1) renal Trpv5 (transient receptor potential cation channel, subfamily V member 5) and Trpv6 and intestinal Trpv6 (calcium channels) for calcium absorption; 2) liver 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (Hmgcr) and cytochrome 7α-hydroxylase (Cyp7a1) for cholesterol synthesis and degradation, respectively; and 3) renal and brain Mdr1 (multidrug-resistance protein that encodes the P-glycoprotein) for digoxin disposition after repetitive intraperitoneal doses of 120 pmol 1,25(OH)₂D₃ Fitting, performed with modeling software, yielded reasonable prediction of a dominant role of intestinal Trpv6 in calcium absorption, circadian rhythm that is characterized by simple cosine models for Hmgcr and Cyp7a1 on liver cholesterol, and brain and renal Mdr1 on tissue efflux of digoxin. Fitted parameters on the E_max, EC₅₀, and turnover rate constants of VDR-target genes [zero-order production (k_in) and first-order degradation (k_out) rate constants] showed low coefficients of variation and acceptable median prediction errors (4.5%-40.6%). Sensitivity analyses showed that the E_max and EC₅₀ values are key parameters that could influence the pharmacodynamic responses. In conclusion, the PBPK(SFM)-pharmacodynamic model successfully characterized VDR gene activation and serves as a useful tool to predict the therapeutic effects of 1,25(OH)₂D₃.

From PK/PD to QSP: Understanding the Dynamic Effect of Cholesterol-Lowering Drugs on Atherosclerosis Progression and Stratified Medicine

Current computational and mathematical tools are demonstrating the high value of using systems modeling approaches (e.g. Quantitative Systems Pharmacology) to understand the effect of a given compound on the biological and physiological mechanisms related to a specific disease. This review provides a short survey of the evolution of the mathematical approaches used to understand the effect of particular cholesterol-lowering drugs, from pharmaco-kinetic (PK) / pharmaco-dynamic (PD) models, through physiologically based pharmacokinetic models (PBPK) to QSP. These mathematical models introduce more mechanistic information related to the effect of these drugs on atherosclerosis progression and demonstrate how QSP could open new ways for stratified medicine in this field.

Enabling personalized cancer medicine decisions: The challenging pharmacological approach of PBPK models for nanomedicine and pharmacogenomics (Review)

The existing tumor heterogeneity and the complexity of cancer cell biology critically demand powerful translational tools with which to support interdisciplinary efforts aiming to advance personalized cancer medicine decisions in drug development and clinical practice. The development of physiologically based pharmacokinetic (PBPK) models to predict the effects of drugs in the body facilitates the clinical translation of genomic knowledge and the implementation of in vivo pharmacology experience with pharmacogenomics. Such a direction unequivocally empowers our capacity to also make personalized drug dosage scheme decisions for drugs, including molecularly targeted agents and innovative nanoformulations, i.e. in establishing pharmacotyping in prescription. In this way, the applicability of PBPK models to guide individualized cancer therapeutic decisions of broad clinical utility in nanomedicine in real-time and in a cost-affordable manner will be discussed. The latter will be presented by emphasizing the need for combined efforts within the scientific borderlines of genomics with nanotechnology to ensure major benefits and productivity for nanomedicine and personalized medicine interventions.

A quantitative approach to analysing cortisol response in the horse

The cortisol response to glucocorticoid intervention has, in spite of several studies in horses, not been fully characterized with regard to the determinants of onset, intensity and duration of response. Therefore, dexamethasone and cortisol response data were collected in a study applying a constant rate infusion regimen of dexamethasone (0.17, 1.7 and 17 μg/kg) to six Standardbreds. Plasma was analysed for dexamethasone and cortisol concentrations using UHPLC-MS/MS. Dexamethasone displayed linear kinetics within the concentration range studied. A turnover model of oscillatory behaviour accurately mimicked cortisol data. The mean baseline concentration range was 34-57 μg/L, the fractional turnover rate 0.47-1.5 1/h, the amplitude parameter 6.8-24 μg/L, the maximum inhibitory capacity 0.77-0.97, the drug potency 6-65 ng/L and the sigmoidicity factor 0.7-30. This analysis provided a better understanding of the time course of the cortisol response in horses. This includes baseline variability within and between horses and determinants of the equilibrium concentration-response relationship. The analysis also challenged a protocol for a dexamethasone suppression test design and indicated future improvement to increase the predictability of the test.

Population pharmacokinetic/pharmacodynamic assessment of pharmacological effect of a selective estrogen receptor β agonist on total testosterone in healthy men

BACKGROUND

LY500307 is a highly selective estrogen receptor β (ERβ) agonist, which loses its selectivity at high dose and leads to undesirable suppression of total testosterone (TT) concentration. The objective of the present analysis was to define the LY500307 dose with minimal effect on TT METHODS: LY500307 and TT concentrations were obtained from a single ascending-dose study in a total of 30 healthy male subjects. LY500307 (in the range of 0.5 to 500 mg) or placebo was administered orally as a single dose on 2 occasions with a 3-week washout period. A population pharmacokinetics/pharmacodynamics (PK/PD) model that integrated Fourier series in an indirect response model was developed to describe the circadian rhythm of TT and the exposure-response relationship of LY500307 on TT.

RESULTS

The maximum TT suppression (Emax ) was approximately 28.6%. The potency (EC50 ) of LY500307 on TT suppression was approximately 1.69 ng/mL with a 95%CI of 0.871 to 4.44 ng/mL. This model could provide inferences on LY500307 dose levels that would result in various magnitudes of TT suppression.

CONCLUSIONS

Population PK/PD modeling is a highly sensitive tool to detect exposure-response relationships on top of the complicated and highly variable circadian rhythm of TT.

Application of a Physiologically Based Pharmacokinetic Model to Predict OATP1B1-Related Variability in Pharmacodynamics of Rosuvastatin

Typically, pharmacokinetic–pharmacodynamic (PK/PD) models use plasma concentration as the input that drives the PD model. However, interindividual variability in uptake transporter activity can lead to variable drug concentrations in plasma without discernible impact on the effect site organ concentration. A physiologically based PK/PD model for rosuvastatin was developed that linked the predicted liver concentration to the PD response model. The model was then applied to predict the effect of genotype-dependent uptake by the organic anion-transporting polypeptide 1B1 (OATP1B1) transporter on the pharmacological response. The area under the plasma concentration–time curve (AUC_0–∞) was increased by 63 and 111% for the c.521TC and c.521CC genotypes vs. the c.521TT genotype, while the PD response remained relatively unchanged (3.1 and 5.8% reduction). Using local concentration at the effect site to drive the PD response enabled us to explain the observed disconnect between the effect of the OATP1B1 c521T>C polymorphism on rosuvastatin plasma concentration and the cholesterol synthesis response.