Determinants of the over-anticoagulation response during warfarin initiation therapy in Asian patients based on population pharmacokinetic-pharmacodynamic analyses

Leveraging QSP Models for MIPD: A Case Study for Warfarin/INR

Warfarin dosing remains challenging due to substantial inter-individual variability, which can lead to unsafe or ineffective therapy with standard dosing. Model-informed precision dosing (MIPD) can help individualize warfarin dosing, requiring the selection of a suitable model. For models developed from clinical data, the dependence on the study design and population raises questions about generalizability. Quantitative system pharmacology (QSP) models promise better extrapolation abilities; however, their complexity and lack of validation on clinical data raise questions about applicability in MIPD. We have previously derived a mechanistic warfarin/international normalized ratio (INR) model from a blood coagulation QSP model. In this article, we evaluated the predictive performance of the warfarin/INR model in the context of MIPD using an external dataset with INR data from patients starting warfarin treatment. We assessed the accuracy and precision of model predictions, benchmarked against an empirically based reference model. Additionally, we evaluated covariate contributions and assessed the predictive performance separately in the more challenging outpatient data. The warfarin/INR model performed comparably to the reference model across various measures despite not being calibrated with warfarin initiation data. Including CYP2C9 and/or VKORC1 genotypes as covariates improved the prediction quality of the warfarin/INR model, even after assimilating 4 days of INR data. The outpatient INR exhibited higher unexplained variability, and predictions slightly exceeded observed values, suggesting that model adjustments might be necessary when transitioning from an inpatient to an outpatient setting. Overall, this research underscores the potential of QSP-derived models for MIPD, offering a complementary approach to empirical model development.

Warfarin-A natural anticoagulant: A review of research trends for precision medication

BACKGROUND

Warfarin is a widely prescribed anticoagulant in the clinic. It has a more considerable individual variability, and many factors affect its variability. Mathematical models can quantify the quantitative impact of these factors on individual variability.

PURPOSE

The aim is to comprehensively analyze the advanced warfarin dosing algorithm based on pharmacometrics and machine learning models of personalized warfarin dosage.

METHODS

A bibliometric analysis of the literature retrieved from PubMed and Scopus was performed using VOSviewer. The relevant literature that reported the precise dosage of warfarin calculation was retrieved from the database. The multiple linear regression (MLR) algorithm was excluded because a recent systematic review that mainly reviewed this algorithm has been reported. The following terms of quantitative systems pharmacology, mechanistic model, physiologically based pharmacokinetic model, artificial intelligence, machine learning, pharmacokinetic, pharmacodynamic, pharmacokinetics, pharmacodynamics, and warfarin were added as MeSH Terms or appearing in Title/Abstract into query box of PubMed, then humans and English as filter were added to retrieve the literature.

RESULTS

Bibliometric analysis revealed important co-occuring MeShH and index keywords. Further, the United States, China, and the United Kingdom were among the top countries contributing in this domain. Some studies have established personalized warfarin dosage models using pharmacometrics and machine learning-based algorithms. There were 54 related studies, including 14 pharmacometric models, 31 artificial intelligence models, and 9 model evaluations. Each model has its advantages and disadvantages. The pharmacometric model contains biological or pharmacological mechanisms in structure. The process of pharmacometric model development is very time- and labor-intensive. Machine learning is a purely data-driven approach; its parameters are more mathematical and have less biological interpretation. However, it is faster, more efficient, and less time-consuming. Most published models of machine learning algorithms were established based on cross-sectional data sourced from the database.

CONCLUSION

Future research on personalized warfarin medication should focus on combining the advantages of machine learning and pharmacometrics algorithms to establish a more robust warfarin dosage algorithm. Randomized controlled trials should be performed to evaluate the established algorithm of warfarin dosage. Moreover, a more user-friendly and accessible warfarin precision medicine platform should be developed.

Deriving mechanism-based pharmacodynamic models by reducing quantitative systems pharmacology models: An application to warfarin

Quantitative systems pharmacology (QSP) models integrate comprehensive qualitative and quantitative knowledge about pharmacologically relevant processes. We previously proposed a first approach to leverage the knowledge in QSP models to derive simpler, mechanism-based pharmacodynamic (PD) models. Their complexity, however, is typically still too large to be used in the population analysis of clinical data. Here, we extend the approach beyond state reduction to also include the simplification of reaction rates, elimination of reactions, and analytic solutions. We additionally ensure that the reduced model maintains a prespecified approximation quality not only for a reference individual but also for a diverse virtual population. We illustrate the extended approach for the warfarin effect on blood coagulation. Using the model-reduction approach, we derive a novel small-scale warfarin/international normalized ratio model and demonstrate its suitability for biomarker identification. Due to the systematic nature of the approach in comparison with empirical model building, the proposed model-reduction algorithm provides an improved rationale to build PD models also from QSP models in other applications.

Comparison of Maintenance Dose Predictions by Warfarin Dosing Algorithms Based on Chinese and Western Patients

Warfarin has a long record of safe and effective clinical use, and it remains one of the most commonly prescribed drugs for the prevention and treatment of thromboembolic conditions even in the era of direct oral anticoagulants. To address its large interindividual variability and narrow therapeutic window, the Clinical Pharmacogenetics Implementation Consortium has recommended using pharmacogenetic dosing algorithms, such as the ones developed by the International Warfarin Pharmacogenetics Consortium (IWPC) and by Gage et al, to dose warfarin when genotype information is available. In China, dosing algorithms based on local patient populations have been developed and evaluated for predictive accuracy of warfarin maintenance doses. In this study, percentage deviations of doses predicted by 15 Chinese dosing algorithms from that by IWPC and Gage algorithms were systematically evaluated to understand the differences between Chinese and Western algorithms. In general, dose predictions by Chinese dosing algorithms tended to be lower than those predicted by IWPC or Gage algorithms for the most prevalent VKORC1 and CYP2C9 genotypes in the Chinese population. The extent of negative prediction deviation appeared to be largest in the younger age group with smaller body weight. Our findings are consistent with previous reports that Asians have a higher sensitivity to warfarin and require lower doses than Western populations.

A continued learning approach for model-informed precision dosing: updating models in clinical practice

Model-informed precision dosing (MIPD) is a quantitative dosing framework that combines prior knowledge on the drug-disease-patient system with patient data from therapeutic drug/biomarker monitoring (TDM) to support individualized dosing in ongoing treatment. Structural models and prior parameter distributions used in MIPD approaches typically build on prior clinical trials that involve only a limited number of patients selected according to some exclusion/inclusion criteria. Compared to the prior clinical trial population, the patient population in clinical practice can be expected to include also altered behavior and/or increased interindividual variability, the extent of which, however, is typically unknown. Here, we address the question of how to adapt and refine models on the level of the model parameters to better reflect this real-world diversity. We propose an approach for continued learning across patients during MIPD using a sequential hierarchical Bayesian framework. The approach builds on two stages to separate the update of the individual patient parameters from updating the population parameters. Consequently, it enables continued learning across hospitals or study centers, since only summary patient data (on the level of model parameters) need to be shared, but no individual TDM data. We illustrate this continued learning approach with neutrophil-guided dosing of paclitaxel. The present study constitutes an important step towards building confidence in MIPD and eventually establishing MIPD increasingly in everyday therapeutic use.

Anticoagulant rodenticide ingestion: Who will develop coagulopathy?

Introduction:

Development of coagulopathy after anticoagulant rodenticide ingestion varies among patients. This study aimed to identify factors that were associated with coagulopathy after anticoagulant rodenticide ingestion.

Methods:

This was a retrospective cohort study, conducted in the Hong Kong Poison Information Centre. All patients who reported rodenticide exposure and presented to the Accident and Emergency Department from 1 January 2010 to 31 December 2019 were recruited. Coagulopathy was defined as International Normalized Ratio of 1.3 or above.

Results:

One hundred sixty-nine patients were included in the final analysis. The median age was 44 years old. Forty-nine patients developed coagulopathy (International Normalized Ratio ⩾1.3). Univariate analysis (at p < 0.05) showed that age (p = 0.003), ingestion of first-generation anticoagulant rodenticide (p = 0.017), ingestion of more than one pack (p < 0.001), intentional ingestion (p = 0.002), hypoalbuminemia (p < 0.001), elevated alanine aminotransferase level (p = 0.041) and abnormal estimated glomerular filtration rate (p = 0.005) on presentation, and co-ingestion with paracetamol (p = 0.018) were associated with coagulopathy after anticoagulant rodenticide ingestion. Among these, ingestion of more than one pack (p < 0.001; odds ratio = 19.8; 95% confidence interval = 6.78–65.7), ingestion of first-generation anticoagulant rodenticide (p = 0.006; odds ratio = 5.2; 95% confidence interval = 1.96–15.2), hypoalbuminemia (p < 0.001; odds ratio = 22.4; 95% confidence interval = 6.17–99.0) and elevated alanine aminotransferase level on presentation (p = 0.039; odds ratio = 7.11; 95% confidence interval = 1.58–33.1) were statistically significant in the multivariate analysis.

Conclusion:

Ingestion of more than one pack and ingestion of first-generation anticoagulant rodenticides were significantly associated with the development of coagulopathy after anticoagulant rodenticide ingestion. Patients who developed hypoalbuminemia or elevated alanine aminotransferase level as a result of anticoagulant rodenticide ingestion were also significantly associated with the development of coagulopathy.

Snake Venoms in Diagnostic Hemostasis and Thrombosis

Snake venoms have evolved primarily to immobilize and kill prey, and consequently, they contain some of the most potent natural toxins. Part of that armory is a range of hemotoxic components that affect every area of hemostasis, which we have harnessed to great effect in the study and diagnosis of hemostatic disorders. The most widely used are those that affect coagulation, such as thrombin-like enzymes unaffected by heparin and direct thrombin inhibitors, which can help confirm or dispute their presence in plasma. The liquid gold of coagulation activators is Russell's viper venom, since it contains activators of factor X and factor V. It is used in a range of clotting-based assays, such as assessment of factor X and factor V deficiencies, protein C and protein S deficiencies, activated protein C resistance, and probably the most important test for lupus anticoagulants, the dilute Russell's viper venom time. Activators of prothrombin, such as oscutarin C from Coastal Taipan venom and ecarin from saw-scaled viper venom, are employed in prothrombin activity assays and lupus anticoagulant detection, and ecarin has a valuable role in quantitative assays of direct thrombin inhibitors. Snake venoms affecting primary hemostasis include botrocetin from the jararaca, which can be used to assay von Willebrand factor activity, and convulxin from the cascavel, which can be used to detect deficiency of the platelet collagen receptor, glycoprotein VI. This article takes the reader to every area of the diagnostic hemostasis laboratory to appreciate the myriad applications of snake venoms available in diagnostic practice.

Should all patients receive the same prophylaxis? Racial variation in the risk of venous thromboembolism after major abdominal operations

BACKGROUND

Whether prevention strategy for postoperative venous thromboembolism (VTE) should be tailored across racial groups remains unknown.

METHODS

Patients who underwent major abdominal operation in the Nationwide Inpatient Sample (NIS) were examined. Our primary outcome was postoperative VTE, and the secondary outcome was postoperative bleeding. Multivariable logistic regression analyses were performed and validated with the National Surgical Quality Improvement Program (NSQIP) database.

RESULTS

781,888 patients from NIS were analyzed. Overall VTE rate was 2.0%. Compared to White patients, Hispanic (OR 0.85, 95% CI 0.78-0.93, p < 0.01) and Asian patients (OR 0.49, 95% CI 0.40-0.61, p < 0.01) had significantly lower risks for VTE. In contrast, Asian patients had a significantly higher risk of bleeding (OR 1.39, 95% CI 1.24-1.56, p < 0.01). Similar trends were observed in NSQIP.

CONCLUSIONS

The risk-benefit ratio of postoperative VTE prophylaxis for Asian patients is roughly three times higher than that for White patients, suggesting a tailored approach is necessary.

Warfarin Dosing and Outcomes in Chronic Kidney Disease: A Closer Look at Warfarin Disposition

BACKGROUND

Chronic Kidney Disease (CKD) is a prevalent worldwide health problem. Patients with CKD are more prone to developing cardiovascular complications such as atrial fibrillation and stroke. This warrants the use of oral anticoagulants, such as warfarin, in this population. While the efficacy and safety of warfarin in this setting remain controversial, a growing body of evidence emphasizes that warfarin use in CKD can be problematic. This review discusses 1) warfarin use, dosing and outcomes in CKD patients; and 2) possible pharmacokinetic mechanisms for altered warfarin dosing and response in CKD.

METHODS

Structured search and review of literature articles evaluating warfarin dosing and outcomes in CKD. Data and information about warfarin metabolism, transport, and pharmacokinetics in CKD were also analyzed and summarized.

RESULTS

The literature data suggest that changes in warfarin pharmacokinetics such as protein binding, nonrenal clearance, the disposition of warfarin metabolites may partially contribute to altered warfarin dosing and response in CKD.

CONCLUSION

Although the evidence to support warfarin use in advanced CKD is still unclear, this synthesis of previous findings may help in improving optimized warfarin therapy in CKD settings.

Pharmacokinetics of Tecarfarin and Warfarin in Patients with Severe Chronic Kidney Disease

Chronic kidney disease (CKD) complicates warfarin anticoagulation partially through its effect on CYP2C9 activity. Tecarfarin, a novel vitamin K antagonist, is not metabolized by CYP2C9. To evaluate the effect of CKD on their metabolism, we measured PK parameters of warfarin and tecarfarin in subjects with and without CKD. CKD subjects with estimated glomerular filtration rate < 30 mL/min not on dialysis (n = 13) were matched to healthy volunteers (HVs) (n = 10). Each subject was randomized to either warfarin 10 mg or tecarfarin 30 mg and was later crossed over to the other drug. PK parameters were measured following each drug. Mean plasma concentrations of (S)-warfarin and (R,S)-warfarin were higher (44 and 27%, respectively) in the subjects with CKD than in the healthy subjects. Both of these values fell outside of the 90% confidence interval of equivalence. For tecarfarin, the difference was less than 15% higher. Elimination half-life (t_1/2) increased by 20% for (S)-warfarin and by 8% for (R,S)-warfarin and decreased by 8% for tecarfarin. The mean plasma concentration for tecarfarin's inactive metabolite ATI-5900 increased by approximately eightfold. CKD increased the effect of CYP2C9 genetic variation on (S)-warfarin and (R,S)-warfarin metabolism. Tecarfarin exposure was similar between the HVs and the CKD subjects regardless of CYP2C9 genotype. There were neither serious adverse events (SAEs) nor treatment-emergent adverse events (TEAEs) for any subject in the study. CKD inhibits metabolism of (S)-warfarin and (R,S)-warfarin, but not tecarfarin. The safety of repeated dosing of tecarfarin in CKD patients remains unknown. However, if the PK findings of this single-dose study are present with repeated dosing, tecarfarin may lead to dosing that is more predictable than warfarin in CKD patients who require anticoagulation therapy.

Pharmacokinetic interactions and dosing rationale for antiepileptic drugs in adults and children

AIMS

Population pharmacokinetic modelling has been widely used across many therapeutic areas to identify sources of variability, which are incorporated into models as covariate factors. Despite numerous publications on pharmacokinetic drug-drug interactions (DDIs) between antiepileptic drugs (AEDs), such data are not used to support the dose rationale for polytherapy in the treatment of epileptic seizures. Here we assess the impact of DDIs on plasma concentrations and evaluate the need for AED dose adjustment.

METHODS

Models describing the pharmacokinetics of carbamazepine, clobazam, clonazepam, lamotrigine, levetiracetam, oxcarbazepine, phenobarbital, phenytoin, topiramate, valproic acid and zonisamide in adult and paediatric patients were collected from the published literature and implemented in NONMEM v7.2. Taking current clinical practice into account, we explore simulation scenarios to characterize AED exposure in virtual patients receiving mono- and polytherapy. Steady-state, maximum and minimum concentrations were selected as parameters of interest for this analysis.

RESULTS

Our simulations show that DDIs can cause major changes in AED concentrations both in adults and children. When more than one AED is used, even larger changes are observed in the concentrations of the primary drug, leading to significant differences in steady-state concentration between mono- and polytherapy for most AEDs. These results suggest that currently recommended dosing algorithms and titration procedures do not ensure attainment of appropriate therapeutic concentrations.

CONCLUSIONS

The effect of DDIs on AED exposure cannot be overlooked. Clinical guidelines must consider such covariate effects and ensure appropriate dosing recommendations for adult and paediatric patients who require combination therapy.

Correlations between the enantio- and regio-selective metabolisms of warfarin

AIM

To clarify whether the activities of multiple CYPs associated with warfarin metabolism would be correlated with each other.

METHODS

Oral clearances (CLpo) of warfarin enantiomers were estimated in 378 Chinese, Caucasians and African-Americans. The partial metabolic clearances (CLm) for 7-hydroxywarfarin enantiomers were also measured. In addition, CLpo and CLm were determined in a patient on warfarin and rifampicin.

RESULTS

Correlations between CLpo for warfarin enantiomers existed across the three populations. In addition, there was a significant correlation between the CLm for 7-hydroxylation of warfarin enantiomers. Under induced conditions by rifampicin, there were significant correlations between the enantio- and regio-selective metabolisms of warfarin.

CONCLUSION

Metabolic activities of CYP2C9, CYP1A2 and CYP3A4 may be regulated by common transcriptional mechanism(s).

Theory-based pharmacokinetics and pharmacodynamics of S- and R-warfarin and effects on international normalized ratio: influence of body size, composition and genotype in cardiac surgery patients

AIMS

The aims of this study are to apply a theory-based mechanistic model to describe the pharmacokinetics (PK) and pharmacodynamics (PD) of S- and R-warfarin.

METHODS

Clinical data were obtained from 264 patients. Total concentrations for S- and R-warfarin were measured by ultra-high performance liquid tandem mass spectrometry. Genotypes were measured using pyrosequencing. A sequential population PK parameter with data method was used to describe the international normalized ratio (INR) time course. Data were analyzed with NONMEM. Model evaluation was based on parameter plausibility and prediction-corrected visual predictive checks.

RESULTS

Warfarin PK was described using a one-compartment model. CYP2C9 *1/*3 genotype had reduced clearance for S-warfarin, but increased clearance for R-warfarin. The in vitro parameters for the relationship between prothrombin complex activity (PCA) and INR were markedly different (A = 0.560, B = 0.386) from the theory-based values (A = 1, B = 0). There was a small difference between healthy subjects and patients. A sigmoid E_max PD model inhibiting PCA synthesis as a function of S-warfarin concentration predicted INR. Small R-warfarin effects was described by competitive antagonism of S-warfarin inhibition. Patients with VKORC1 AA and CYP4F2 CC or CT genotypes had lower C50 for S-warfarin.

CONCLUSION

A theory-based PKPD model describes warfarin concentrations and clinical response. Expected PK and PD genotype effects were confirmed. The role of predicted fat free mass with theory-based allometric scaling of PK parameters was identified. R-warfarin had a minor effect compared with S-warfarin on PCA synthesis. INR is predictable from 1/PCA in vivo.

Population differences in S-warfarin pharmacokinetics among African Americans, Asians and whites: their influence on pharmacogenetic dosing algorithms

Using population pharmacokinetic analysis (PPK), we attempted to identify predictors of S-warfarin clearance (CL(S)) and to clarify population differences in S-warfarin pharmacokinetics among a cohort of 378 African American, Asian and white patients. Significant predictors of CL(S) included clinical (age, body weight and sex) and genotypic (CYP2C9*2,*3 and *8) factors, as well as African American ethnicity, the median CL(S) being 30% lower in the latter than in Asians and whites (170 versus 243 and 250 ml h^-1, P<0.01). The plasma S-warfarin (Cp(S)) time courses following the genotype-based dosing algorithms simulated using the PPK estimates showed African Americans with CYP2C9*1/*1 and any of the VKORC1 genotypes would have an average Cp(S) at steady state 1.5-1.8 times higher than in Asians and whites. These results indicate warfarin dosing algorithms should be evaluated in each respective ethnic population. Further study of a large African American cohort will be necessary to confirm the present findings.

A multi-factorial analysis of response to warfarin in a UK prospective cohort

Background

Warfarin is the most widely used oral anticoagulant worldwide, but it has a narrow therapeutic index which necessitates constant monitoring of anticoagulation response. Previous genome-wide studies have focused on identifying factors explaining variance in stable dose, but have not explored the initial patient response to warfarin, and a wider range of clinical and biochemical factors affecting both initial and stable dosing with warfarin.

Methods

A prospective cohort of 711 patients starting warfarin was followed up for 6 months with analyses focusing on both non-genetic and genetic factors. The outcome measures used were mean weekly warfarin dose (MWD), stable mean weekly dose (SMWD) and international normalised ratio (INR) > 4 during the first week. Samples were genotyped on the Illumina Human610-Quad chip. Statistical analyses were performed using Plink and R.

Results

VKORC1 and CYP2C9 were the major genetic determinants of warfarin MWD and SMWD, with CYP4F2 having a smaller effect. Age, height, weight, cigarette smoking and interacting medications accounted for less than 20 % of the variance. Our multifactorial analysis explained 57.89 % and 56.97 % of the variation for MWD and SMWD, respectively. Genotypes for VKORC1 and CYP2C9*3, age, height and weight, as well as other clinical factors such as alcohol consumption, loading dose and concomitant drugs were important for the initial INR response to warfarin. In a small subset of patients for whom data were available, levels of the coagulation factors VII and IX (highly correlated) also played a role.

Conclusion

Our multifactorial analysis in a prospectively recruited cohort has shown that multiple factors, genetic and clinical, are important in determining the response to warfarin. VKORC1 and CYP2C9 genetic polymorphisms are the most important determinants of warfarin dosing, and it is highly unlikely that other common variants of clinical importance influencing warfarin dosage will be found. Both VKORC1 and CYP2C9*3 are important determinants of the initial INR response to warfarin. Other novel variants, which did not reach genome-wide significance, were identified for the different outcome measures, but need replication.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0255-y) contains supplementary material, which is available to authorized users.

Factors influencing pharmacokinetics of warfarin in African-Americans: implications for pharmacogenetic dosing algorithms

AIM

This study attempted to identify predictors of S-warfarin clearance (CL[S]) and to make a pharmacokinetic evaluation of genotype-based dosing algorithms in African-Americans.

METHODS

Using plasma S-warfarin concentration (Cp[S]) at a steady state and eight SNPs previously shown to influence warfarin dose in African-Americans, CL(S) and its predictors were estimated by population pharmacokinetic analysis in 60 African-Americans. The time courses of Cp(S) following either the loading dose or maintenance dose were simulated using the population pharmacokinetic estimates.

RESULTS

CYP2C9*8 and body surface area or body weight were predictors of CL(S) (-30 and -5% per -0.1 m(2)/-10 kg reduction in CL[S], respectively) in African-Americans. Simulations of Cp(S) showed that Cp(S) at steady state was 1.4-times higher in patients with CYP2C9*8 than in those with CYP2C9*1/*1, irrespective of the algorithm for loading dose or maintenance dose.

CONCLUSION

African-Americans possess independent predictors of CL(S), possibly leading to a prediction error of any dosing algorithm that excludes African-specific variant(s). Original submitted 3 September 2014; Revision submitted 3 November 2014.