A semi-mechanistic model to predict the effects of liver cirrhosis on drug clearance

Development of a Whole-Body Physiologically Based Pharmacokinetic Approach to Assess the Pharmacokinetics of Drugs in Elderly Individuals

Background

Because of the vulnerability and frailty of elderly adults, clinical drug development has traditionally been biased towards young and middle-aged adults. Recent efforts have begun to incorporate data from paediatric investigations. Nevertheless, the elderly often remain underrepresented in clinical trials, even though persons aged 65 years and older receive the majority of drug prescriptions. Consequently, a knowledge gap exists with regard to pharmacokinetic (PK) and pharmacodynamic (PD) responses in elderly subjects, leaving the safety and efficacy of medicines for this population unclear.

Objectives

The goal of this study was to extend a physiologically based pharmacokinetic (PBPK) model for adults to encompass the full course of healthy aging through to the age of 100 years, to support dose selection and improve pharmacotherapy for the elderly age group.

Methods

For parameterization of the PBPK model for healthy aging individuals, the literature was scanned for anthropometric and physiological data, which were consolidated and incorporated into the PBPK software PK-Sim^®. Age-related changes that occur from 65 to 100 years of age were the main focus of this work. For a sound and continuous description of an aging human, data on anatomical and physiological changes ranging from early adulthood to old age were included. The capability of the PBPK approach to predict distribution and elimination of drugs was verified using the test compounds morphine and furosemide, administered intravenously. Both are cleared by a single elimination pathway. PK parameters for the two compounds in younger adults and elderly individuals were obtained from the literature. Matching virtual populations—with regard to age, sex, anthropometric measures and dosage—were generated. Profiles of plasma drug concentrations over time, volume of distribution at steady state (V_ss) values and elimination half-life (t_½) values from the literature were compared with those predicted by PBPK simulations for both younger adults and the elderly.

Results

For most organs, the age-dependent information gathered in the extensive literature analysis was dense. In contrast, with respect to blood flow, the literature study produced only sparse data for several tissues, and in these cases, linear regression was required to capture the entire elderly age range. On the basis of age-informed physiology, the predicted PK profiles described age-associated trends well. The root mean squared prediction error for the prediction of plasma concentrations of furosemide and morphine in the elderly were improved by 32 and 49 %, respectively, by use of age-informed physiology. The majority of the individual V_ss and t_½ values for the two model compounds, furosemide and morphine, were well predicted in the elderly population, except for long furosemide half-lifes.

Conclusion

The results of this study support the feasibility of using a knowledge-driven PBPK aging model that includes the elderly to predict PK alterations throughout the entire course of aging, and thus to optimize drug therapy in elderly individuals. These results indicate that pharmacotherapy and safety-related control of geriatric drug therapy regimens may be greatly facilitated by the information gained from PBPK predictions.

Electronic supplementary material

The online version of this article (doi:10.1007/s40262-016-0422-3) contains supplementary material, which is available to authorized users.

Cell cultures in drug discovery and development: The need of reliable in vitro-in vivo extrapolation for pharmacodynamics and pharmacokinetics assessment

For ethical and cost-related reasons, use of animals for the assessment of mode of action, metabolism and/or toxicity of new drug candidates has been increasingly scrutinized in research and industrial applications. Implementation of the 3 "Rs"¹; rule (Reduction, Replacement, Refinement) through development of in silico or in vitro assays has become an essential element of risk assessment. Physiologically based pharmacokinetic (PBPK²) modeling is the most potent in silico tool used for extrapolation of pharmacokinetic parameters to animal or human models from results obtained in vitro. Although, many types of in vitro assays are conducted during drug development, use of cell cultures is the most reliable one. Two-dimensional (2D) cell cultures have been a part of drug development for many years. Nowadays, their role is decreasing in favor of three-dimensional (3D) cell cultures and co-cultures. 3D cultures exhibit protein expression patterns and intercellular junctions that are closer to in vivo states in comparison to classical monolayer cultures. Co-cultures allow for examinations of the mutual influence of different cell lines. However, the complexity and high costs of co-cultures and 3D equipment exclude such methods from high-throughput screening (HTS).³In vitro absorption, distribution, metabolism, and excretion assessment, as well as drug-drug interaction (DDI), are usually performed with the use of various cell culture based assays. Progress in in silico and in vitro methods can lead to better in vitro-in vivo extrapolation (IVIVE⁴) outcomes and have a potential to contribute towards a significant reduction in the number of laboratory animals needed for drug research. As such, concentrated efforts need to be spent towards the development of an HTS in vitro platform with satisfactory IVIVE features.

Physiologically Based Pharmacokinetic Modeling for Predicting the Effect of Intrinsic and Extrinsic Factors on Darunavir or Lopinavir Exposure Coadministered With Ritonavir

Management of comorbidities and medications is complex in HIV-1-infected patients. The overall objective of this project was to develop separate physiologically based pharmacokinetic (PBPK) substrate models for the protease inhibitors darunavir and lopinavir. These protease inhibitors are used in the treatment of HIV infection. Both darunavir and lopinavir are coadministered with another medication that inhibits cytochrome (CYP) 3A. The current project focused on PBPK modeling for darunavir and lopinavir coadministered with ritonavir. Darunavir and lopinavir PBPK models that accounted for ritonavir CYP3A inhibition effects (linked PBPK models) were developed. The linked PBPK models were then used to predict the effect on darunavir or lopinavir exposure from CYP modulators. In the next step, the predicted effect of hepatic impairment was evaluated. Additional exploratory analyses predicted CYP3A inhibition effects on darunavir or lopinavir exposure in simulated hepatically impaired subjects. The linked PBPK models reasonably predicted darunavir or lopinavir exposure based on simulations with CYP inhibitors or inducers. Exploratory simulations using the linked darunavir or lopinavir PBPK models indicated CYP3A inhibition may further increase darunavir or lopinavir exposure in patients with hepatic impairment.

Analysis of Nonlinear Pharmacokinetics of a Highly Albumin-Bound Compound: Contribution of Albumin-Mediated Hepatic Uptake Mechanism

The cause of nonlinear pharmacokinetics (PK) (more than dose-proportional increase in exposure) of a urea derivative under development (compound A: anionic compound [pKa: 4.4]; LogP: 6.5; and plasma protein binding: 99.95%) observed in a clinical trial was investigated. Compound A was metabolized by CYP3A4, UGT1A1, and UGT1A3 with unbound K_m of 3.3-17.8 μmol/L. OATP1B3-mediated uptake of compound A determined in the presence of human serum albumin (HSA) showed that unbound K_m and V_max decreased with increased HSA concentration. A greater decrease in unbound K_m than in V_max resulted in increased uptake clearance (V_max/unbound K_m) with increased HSA concentration, the so-called albumin-mediated uptake. At 2% HSA concentration, unbound K_m was 0.00657 μmol/L. A physiologically based PK model assuming saturable hepatic uptake nearly replicated clinical PK of compound A. Unbound K_m for hepatic uptake estimated from the model was 0.000767 μmol/L, lower than the in vitro unbound K_m at 2% HSA concentration, whereas decreased K_m with increased concentration of HSA in vitro indicated lower K_m at physiological HSA concentration (4%-5%). In addition, unbound K_m values for metabolizing enzymes were much higher than unbound K_m for OATP1B3, indicating that the nonlinear PK of compound A is primarily attributed to saturated OATP1B3-mediated hepatic uptake of compound A.

Physiologically Based Pharmacokinetic Modeling of Drug Transporters to Facilitate Individualized Dose Prediction

Physiologically based pharmacokinetic modeling is a commonly used strategy in the drug development and regulatory submissions. This commentary provides a critical overview of the current status of physiologically based pharmacokinetic methodologies to predict transporter-mediated pharmacokinetics, in addition to the impact of disease and genetics with respect to local and systemic concentration.

Application of Physiologically Based Pharmacokinetic Modeling to the Understanding of Bosutinib Pharmacokinetics: Prediction of Drug-Drug and Drug-Disease Interactions

Bosutinib is an orally available Src/Abl tyrosine kinase inhibitor indicated for the treatment of patients with Philadelphia chromosome-positive chronic myelogenous leukemia. Bosutinib is predominantly metabolized by CYP3A4 as the primary clearance mechanism. The main objectives of this study were to 1) develop physiologically based pharmacokinetic (PBPK) models of bosutinib; 2) verify and refine the PBPK models based on clinical study results of bosutinib single-dose drug-drug interaction (DDI) with ketoconazole and rifampin, as well as single-dose drug-disease interaction (DDZI) in patients with renal and hepatic impairment; 3) apply the PBPK models to predict DDI outcomes in patients with weak and moderate CYP3A inhibitors; and 4) apply the PBPK models to predict DDZI outcomes in renally and hepatically impaired patients after multiple-dose administration. Results showed that the PBPK models adequately predicted bosutinib oral exposures in patients after single- and multiple-dose administrations. The PBPK models also reasonably predicted changes in bosutinib exposures in the single-dose DDI and DDZI results, suggesting that the PBPK models were sufficiently developed and verified based on the currently available data. Finally, the PBPK models predicted 2- to 4-fold increases in bosutinib exposures by moderate CYP3A inhibitors, as well as comparable increases in bosutinib exposures in renally and hepatically impaired patients between single- and multiple-dose administrations. Given the challenges in conducting numerous DDI and DDZI studies of anticancer drugs in patients, we believe that the PBPK models verified in our study would be valuable to reasonably predict bosutinib exposures under various scenarios that have not been tested clinically.

Non-alcoholic fatty liver disease (NAFLD) - pathogenesis, classification, and effect on drug metabolizing enzymes and transporters

Non-alcoholic fatty liver disease (NAFLD) is a spectrum of liver disorders. It is defined by the presence of steatosis in more than 5% of hepatocytes with little or no alcohol consumption. Insulin resistance, the metabolic syndrome or type 2 diabetes and genetic variants of PNPLA3 or TM6SF2 seem to play a role in the pathogenesis of NAFLD. The pathological progression of NAFLD follows tentatively a "three-hit" process namely steatosis, lipotoxicity and inflammation. The presence of steatosis, oxidative stress and inflammatory mediators like TNF-α and IL-6 has been implicated in the alterations of nuclear factors such as CAR, PXR, PPAR-α in NAFLD. These factors may result in altered expression and activity of drug metabolizing enzymes (DMEs) or transporters. Existing evidence suggests that the effect of NAFLD on CYP3A4, CYP2E1 and MRP3 is more consistent across rodent and human studies. CYP3A4 activity is down-regulated in NASH whereas the activity of CYP2E1 and the efflux transporter MRP3 is up-regulated. However, it is not clear how the majority of CYPs, UGTs, SULTs and transporters are influenced by NAFLD either in vivo or in vitro. The alterations associated with NAFLD could be a potential source of drug variability in patients and could have serious implications for the safety and efficacy of xenobiotics. In this review, we summarize the effects of NAFLD on the regulation, expression and activity of major DMEs and transporters. We also discuss the potential mechanisms underlying these alterations.

Drug metabolism and liver disease: a drug-gene-environment interaction

Despite the central role of the liver in drug metabolism, surprisingly there is lack of certainty in anticipating the extent of modification of the clearance of a given drug in a given patient. The intent of this review is to provide a conceptual framework in considering the impact of liver disease on drug disposition and reciprocally the impact of drug disposition on liver disease. It is proposed that improved understanding of the situation is gained by considering the issue as a special example of a drug-gene-environment interaction. This requires an integration of knowledge of the drug's properties, knowledge of the gene products involved in its metabolism, and knowledge of the pathophysiology of its disposition. This will enhance the level of predictability of drug disposition and toxicity for a drug of interest in an individual patient. It is our contention that advances in pharmacology, pharmacogenomics, and hepatology, together with concerted interests in the academic, regulatory, and pharmaceutical industry communities provide an ideal immediate environment to move from a qualitative reactive approach to quantitative proactive approach in individualizing patient therapy in liver disease.

Pharmacokinetics of the New Hepatitis C Virus NS3 Protease Inhibitor Narlaprevir following Single-Dose Use with or without Ritonavir in Patients with Liver Cirrhosis

In this study we sought to evaluate narlaprevir (NVR) pharmacokinetics (PK) after a single dose with or without ritonavir (RTV) in cirrhotic versus healthy subjects. NVR at 200 mg was administered to 8 healthy and 8 cirrhotic subjects, and NVR at 100 mg with RTV at 100 mg was administered to 8 healthy and 8 cirrhotic subjects. PK analysis was performed. The geometric mean maximum concentration of a drug in serum (Cmax) and the area under the concentration-time curve from 0 to infinity (AUC0-∞) were 563.1 ng/ml and 4,701.8 ng · h/ml in cirrhotic patients versus 364.8 ng/ml and 1,917.1 ng · h/ml in healthy volunteers, respectively. The geometric mean ratios of the PK parameters of cirrhotic subjects to healthy volunteers were 1.54-fold (90% confidence interval [CI] = 1.05 to 2.27) for Cmax and 2.45-fold (90% CI = 1.56 to 3.85) for AUC0-∞ The geometric mean Cmax and AUC0-∞ in cirrhotic and healthy subjects were similar: 1,225.7 ng/ml for Cmax and 15,213.1 ng · h/ml for AUC0-∞ in cirrhotic subjects and 1,178.9 ng/ml for Cmax and 14,257.2 ng · h/ml for AUC0-∞ in healthy volunteers. The corresponding geometric mean ratios were 1.04 (90% CI = 0.67 to 1.62) for Cmax and 1.07 (90% CI = 0.72 to 1.58) for AUC0-∞ Higher exposures in cirrhotic subjects were safe and well tolerated. We found that NVR exposures after a 200-mg single dose were higher in cirrhotic subjects than in healthy subjects and that a 100-mg single dose of NVR boosted with RTV at 100 mg resulted in no significant PK differences between cirrhotic and healthy subjects.

Transporter Expression in Liver Tissue from Subjects with Alcoholic or Hepatitis C Cirrhosis Quantified by Targeted Quantitative Proteomics

Although data are available on the change of expression/activity of drug-metabolizing enzymes in liver cirrhosis patients, corresponding data on transporter protein expression are not available. Therefore, using quantitative targeted proteomics, we compared our previous data on noncirrhotic control livers (n = 36) with the protein expression of major hepatobiliary transporters, breast cancer resistance protein (BCRP), bile salt export pump (BSEP), multidrug and toxin extrusion protein 1 (MATE1), multidrug resistance-associated protein (MRP)2, MRP3, MRP4, sodium taurocholate-cotransporting polypeptide (NTCP), organic anion-transporting polypeptides (OATP)1B1, 1B3, 2B1, organic cation transporter 1 (OCT1), and P-glycoprotein (P-gp) in alcoholic (n = 27) and hepatitis C cirrhosis (n = 30) livers. Compared with control livers, the yield of membrane protein from alcoholic and hepatitis C cirrhosis livers was significantly reduced by 56 and 67%, respectively. The impact of liver cirrhosis on transporter protein expression was transporter-dependent. Generally, reduced protein expression (per gram of liver) was found in alcoholic cirrhosis livers versus control livers, with the exception that the expression of MRP3 was increased, whereas no change was observed for MATE1, MRP2, OATP2B1, and P-gp. In contrast, the impact of hepatitis C cirrhosis on protein expression of transporters (per gram of liver) was diverse, showing an increase (MATE1), decrease (BSEP, MRP2, NTCP, OATP1B3, OCT1, and P-gp), or no change (BCRP, MRP3, OATP1B1, and 2B1). The expression of hepatobiliary transporter protein differed in different diseases (alcoholic versus hepatitis C cirrhosis). Finally, incorporation of protein expression of OATP1B1 in alcoholic cirrhosis into the Simcyp physiologically based pharmacokinetics cirrhosis module improved prediction of the disposition of repaglinide in liver cirrhosis patients. These transporter expression data will be useful in the future to predict transporter-mediated drug disposition in liver cirrhosis patients.

Modeling and Experimental Studies of Obeticholic Acid Exposure and the Impact of Cirrhosis Stage

Obeticholic acid (OCA), a semisynthetic bile acid, is a selective and potent farnesoid X receptor (FXR) agonist in development for the treatment of chronic nonviral liver diseases. Physiologic pharmacokinetic models have been previously used to describe the absorption, distribution, metabolism, and excretion (ADME) of bile acids. OCA plasma levels were measured in healthy volunteers and cirrhotic subjects. A physiologic pharmacokinetic model was developed to quantitatively describe the ADME of OCA in patients with and without hepatic impairment. There was good agreement between predicted and observed increases in systemic OCA exposure in subjects with mild, moderate, and severe hepatic impairment, which were 1.4‐, 8‐, and 13‐fold relative to healthy volunteers. Predicted liver exposure for subjects with mild, moderate, and severe hepatic impairment were increased only 1.1‐, 1.5‐, and 1.7‐fold. In subjects with cirrhosis, OCA exposure in the liver, the primary site of pharmacological activity along with the intestine, is increased marginally (∼2‐fold).

A Prediction Model of Drug Exposure in Cirrhotic Patients According to Child-Pugh Classification

BACKGROUND AND OBJECTIVE

Prediction of drug clearance in liver cirrhosis patients is currently based on in vitro-in vivo extrapolation and physiologically-based pharmacokinetic models. No static model for this purpose has been described. The objectives of this study were to (1) derive a static model for predicting drug exposure in cirrhotic patients, and (2) to evaluate the model on a large set of published data.

METHODS

The impact of cirrhosis was characterized by the ratio of the total and unbound drug area under the concentration-time curve (AUC) in cirrhotic patients to the AUC measured in healthy subjects These ratios were predicted for Child-Pugh classes A, B, and C. The AUC ratios observed in published data were compared with AUC ratios predicted by the model.

RESULTS

Among 171 drugs examined, 83 published AUC ratios for 45 drugs in cirrhotic patients were available for analysis. The mean ± standard deviation relative prediction error for the total and unbound AUC ratios was 0.22 ± 0.58 and 0.24 ± 0.56, respectively. There were four outliers among the 83 predicted values. Simulations showed that the prediction error was negligible provided that the hepatic extraction coefficient was less than 0.8.

CONCLUSIONS

For mild and moderate cirrhosis (classes A and B), the predicted unbound AUC ratio is typically approximately 2 and 3.5, respectively, for most drugs. In the absence of data in cirrhotic patients, the drug dose might be empirically reduced by these factors. In severe cirrhosis (class C), our model may help clinicians to adjust their prescriptions.

Building a 3D Virtual Liver: Methods for Simulating Blood Flow and Hepatic Clearance on 3D Structures

In this paper, we develop a spatio-temporal modeling approach to describe blood and drug flow, as well as drug uptake and elimination, on an approximation of the liver. Extending on previously developed computational approaches, we generate an approximation of a liver, which consists of a portal and hepatic vein vasculature structure, embedded in the surrounding liver tissue. The vasculature is generated via constrained constructive optimization, and then converted to a spatial grid of a selected grid size. Estimates for surrounding upscaled lobule tissue properties are then presented appropriate to the same grid size. Simulation of fluid flow and drug metabolism (hepatic clearance) are completed using discretized forms of the relevant convective-diffusive-reactive partial differential equations for these processes. This results in a single stage, uniformly consistent method to simulate equations for blood and drug flow, as well as drug metabolism, on a 3D structure representative of a liver.

Caffeine, a common active adulterant of cocaine, enhances the reinforcing effect of cocaine and its motivational value

RATIONALE

Caffeine is one of the psychoactive substances most widely used as an adulterant in illicit drugs, such as cocaine. Animal studies have demonstrated that caffeine is able to potentiate several cocaine actions, although the enhancement of the cocaine reinforcing property by caffeine is less reported, and the results depend on the paradigms and experimental protocols used.

OBJECTIVES

We examined the ability of caffeine to enhance the motivational and rewarding properties of cocaine using an intravenous self-administration paradigm in rats. Additionally, the role of caffeine as a primer cue during extinction was evaluated.

METHODS

In naïve rats, we assessed (1) the ability of the cocaine (0.250-0.125 mg/kg/infusion) and caffeine (0.125-0.0625 mg/kg/infusion) combination to maintain self-administration in fixed ratio (FR) and progressive ratio (PR) schedules of reinforcement compared with cocaine or caffeine alone and (2) the effect of caffeine (0.0625 mg/kg/infusion) in the maintenance of responding in the animals exposed to the combination of the drugs during cocaine extinction.

RESULTS

Cocaine combined with caffeine and cocaine alone was self-administered on FR and PR schedules of reinforcement. Interestingly, the breaking point determined for the cocaine + caffeine group was significantly higher than the cocaine group. Moreover, caffeine, that by itself did not maintain self-administration behavior in naïve rats, maintained drug-seeking behavior of rats previously exposed to combinations of cocaine + caffeine.

CONCLUSIONS

Caffeine enhances the reinforcing effects of cocaine and its motivational value. Our results highlight the role of active adulterants commonly used in cocaine-based illicit street drugs.

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

Dose selection is one of the key decisions made during drug development in pediatrics. There are regulatory initiatives that promote the use of model-based drug development in pediatrics. Pharmacometrics or quantitative clinical pharmacology enables development of models that can describe factors affecting pharmacokinetics and/or pharmacodynamics in pediatric patients. This manuscript describes some examples in which pharmacometric analysis was used to support approval and labeling in pediatrics. In particular, the role of pharmacokinetic (PK) comparison of pediatric PK to adults and utilization of dose/exposure-response analysis for dose selection are highlighted. Dose selection for esomeprazole in pediatrics was based on PK matching to adults, whereas for adalimumab, exposure-response, PK, efficacy, and safety data together were useful to recommend doses for pediatric Crohn's disease. For vigabatrin, demonstration of similar dose-response between pediatrics and adults allowed for selection of a pediatric dose. Based on model-based pharmacokinetic simulations and safety data from darunavir pediatric clinical studies with a twice-daily regimen, different once-daily dosing regimens for treatment-naïve human immunodeficiency virus 1-infected pediatric subjects 3 to <12 years of age were evaluated. The role of physiologically based pharmacokinetic modeling (PBPK) in predicting pediatric PK is rapidly evolving. However, regulatory review experiences and an understanding of the state of science indicate that there is a lack of established predictive performance of PBPK in pediatric PK prediction. Moving forward, pharmacometrics will continue to play a key role in pediatric drug development contributing toward decisions pertaining to dose selection, trial designs, and assessing disease similarity to adults to support extrapolation of efficacy.

A physiologically based pharmacokinetic drug-disease model to predict carvedilol exposure in adult and paediatric heart failure patients by incorporating pathophysiological changes in hepatic and renal blood flows

Background and Objective

Chronic diseases are associated with pathophysiological changes that could have profound impacts on drug pharmacokinetic behaviour, with a potential need to modify the administered drug therapy. It is important to acknowledge that most patients with chronic illnesses do not have a single, predominant condition but suffer from multiple comorbidities. The rapid advancement in physiologically based pharmacokinetic (PBPK) modelling, as well as the increasing quantitative knowledge of disease-related pathophysiological changes, facilitate building of drug–disease models. However, there are only a few published examples of PBPK models incorporating the pathophysiological changes that occur with chronic diseases. The objective of this study was to develop PBPK models that incorporate the haemodynamic changes in hepatic and renal blood flows occurring in chronic heart failure (CHF) and to evaluate these changes in adults and children, using carvedilol as a model drug.

Methods

After a comprehensive literature search to select the model input parameters, two PBPK models were developed. Model 1 was based on human liver and intestinal microsome clearances, and model 2 was based on clearance by specific cytochrome P450 enzymes. After evaluation of both models in healthy adults, the reduced hepatic and renal blood flows were incorporated into the developed models to predict carvedilol exposure in the adult CHF population. The adult carvedilol models were scaled down to children by using Simcyp^® (Simcyp Ltd, Sheffield, UK). In order to show the impact of reduced organ blood flows on carvedilol disposition, the predictions in the CHF population were made with and without reductions in organ blood flows.

Results

The predictions made by both models in healthy adults were comparable and within the 2-fold error range. In adults with CHF, the mean observed/predicted ratio [ratio_(Obs/Pred)] for oral clearance (CL/F) without reductions in organ blood flows was outside the 2-fold error range, i.e. 0.34 (95 % confidence interval [CI] 0.31–0.37), with use of both models. The mean CL/F ratio_(Obs/Pred) values after incorporation of reduced organ blood flows were 1.0 (95 % CI 0.92–1.08) and 0.95 (95 % CI 0.88–1.03) with use of models 1 and 2, respectively. The mean ratio_(Obs/Pred) values for the pharmacokinetic parameters were not improved after incorporation of reduced blood flows in paediatric patients, except in those above 17 years of age, who were categorized according to the New York Heart Association classification of CHF, where the CL/F ratio_(Obs/Pred) values in two patients were closer to unity.

Conclusion

There was a strong connection between a decrease in hepatic clearance of carvedilol and an increase in the severity of CHF, especially in adults and in paediatric patients above 17 years of age. The incorporated reductions in hepatic and renal blood flows occurring in moderate and severe CHF patients resulted in improved predictions of carvedilol exposure. The developed models can be extended to predict exposures of drugs with high hepatic extraction in the CHF population.

Electronic supplementary material

The online version of this article (doi:10.1007/s40262-015-0253-7) contains supplementary material, which is available to authorized users.

Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer

Aims

Use of the anti‐tumour antibiotic actinomycin D is associated with development of hepatotoxicity, particularly in young children. A paucity of actinomycin D pharmacokinetic data make it challenging to develop a sound rationale for defining dosing regimens in younger patients. The study aim was to develop a physiologically based pharmacokinetic (PBPK) model using a combination of data from the literature and generated from experimental analyses.

Methods

Assays to determine actinomycin D Log P, blood:plasma partition ratio and ABCB1 kinetics were conducted. These data were combined with physiochemical properties sourced from the literature to generate a compound file for use within the modelling‐simulation software Simcyp (version 14 release 1). For simulation, information was taken from two datasets, one from 117 patients under the age of 21 and one from 20 patients aged 16–48.

Results

The final model incorporated clinical renal and biliary clearance data and an additional systemic clearance value. The mean AUC_0‐26h of simulated subjects was within 1.25‐fold of the observed AUC_0‐26h (84 ng h ml⁻¹ simulated vs. 93 ng h ml⁻¹ observed). For the younger age ranges, AUC predictions were within two‐fold of observed values, with simulated data from six of the eight age/dose ranges falling within 15% of observed data. Simulated values for actinomycin D AUC_0‐26h and clearance in infants aged 0–12 months ranged from 104 to 115 ng h ml⁻¹ and 3.5–3.8 l h⁻¹, respectively.

Conclusions

The model has potential utility for prediction of actinomycin D exposure in younger patients and may help guide future dosing. However, additional independent data from neonates and infants is needed for further validation. Physiological differences between paediatric cancer patients and healthy children also need to be further characterized and incorporated into PBPK models.

Human Ontogeny of Drug Transporters: Review and Recommendations of the Pediatric Transporter Working Group

The critical importance of membrane-bound transporters in pharmacotherapy is widely recognized, but little is known about drug transporter activity in children. In this white paper, the Pediatric Transporter Working Group presents a systematic review of the ontogeny of clinically relevant membrane transporters (e.g., SLC, ABC superfamilies) in intestine, liver, and kidney. Different developmental patterns for individual transporters emerge, but much remains unknown. Recommendations to increase our understanding of membrane transporters in pediatric pharmacotherapy are presented.

Pharmacokinetics and safety of co-administered paritaprevir plus ritonavir, ombitasvir, and dasabuvir in hepatic impairment

BACKGROUND & AIMS

Paritaprevir, ombitasvir, and dasabuvir are direct-acting antivirals for treatment of chronic hepatitis C virus (HCV) infection. The aim of this study was to characterize the effects of mild, moderate, and severe hepatic impairment on the pharmacokinetics of these drugs.

METHODS

HCV-negative subjects with normal hepatic function (n=7) or mild (Child-Pugh A, n=6), moderate (Child-Pugh B, n=6), or severe (Child-Pugh C, n=5) hepatic impairment received a single-dose of the combination of paritaprevir plus ritonavir (paritaprevir/r, 200/100 mg), ombitasvir (25 mg), and dasabuvir (400 mg). Plasma samples were collected through 144 hours after administration for pharmacokinetic assessments.

RESULTS

Paritaprevir, ombitasvir, dasabuvir, and ritonavir exposures (maximal plasma concentration, C(max), and area under the concentration-time curve, AUC) were minimally affected in subjects with mild or moderate hepatic impairment. Differences in exposures between healthy controls and subjects with mild or moderate hepatic impairment were less than 35%, except for 62% higher paritaprevir AUC in subjects with moderate hepatic impairment. Paritaprevir and dasabuvir AUC were significantly higher in subjects with severe hepatic impairment (950% and 325%, respectively). However, ombitasvir AUC was 54% lower and ritonavir AUC was comparable. Adverse events included eye stye, insomnia, and pain from an infiltrated intravenous line.

CONCLUSIONS

The changes observed in paritaprevir, ritonavir, ombitasvir, and dasabuvir exposures in subjects with mild or moderate hepatic impairment do not necessitate dose adjustment. Subjects with severe hepatic impairment had substantially higher paritaprevir and dasabuvir exposures.

Organ Impairment-Drug-Drug Interaction Database: A Tool for Evaluating the Impact of Renal or Hepatic Impairment and Pharmacologic Inhibition on the Systemic Exposure of Drugs

The organ impairment and drug–drug interaction (OI-DDI) database is the first rigorously assembled database of pharmacokinetic drug exposure data from publicly available renal and hepatic impairment studies presented together with the maximum change in drug exposure from drug interaction inhibition studies. The database was used to conduct a systematic comparison of the effect of renal/hepatic impairment and pharmacologic inhibition on drug exposure. Additional applications are feasible with the public availability of this database.

A Mechanistic Pharmacokinetic Model for Liver Transporter Substrates Under Liver Cirrhosis Conditions

Liver cirrhosis is a disease characterized by the loss of functional liver mass. Physiologically based pharmacokinetic (PBPK) modeling was applied to interpret and predict how the interplay among physiological changes in cirrhosis affects pharmacokinetics. However, previous PBPK models under cirrhotic conditions were developed for permeable cytochrome P450 substrates and do not directly apply to substrates of liver transporters. This study characterizes a PBPK model for liver transporter substrates in relation to the severity of liver cirrhosis. A published PBPK model structure for liver transporter substrates under healthy conditions and the physiological changes for cirrhosis are combined to simulate pharmacokinetics of liver transporter substrates in patients with mild and moderate cirrhosis. The simulated pharmacokinetics under liver cirrhosis reasonably approximate observations. This analysis includes meta-analysis to obtain system-dependent parameters in cirrhosis patients and a top-down approach to improve understanding of the effect of cirrhosis on transporter-mediated drug disposition under cirrhotic conditions.

Physiologically based pharmacokinetic modeling for sequential metabolism: effect of CYP2C19 genetic polymorphism on clopidogrel and clopidogrel active metabolite pharmacokinetics

Clopidogrel is a prodrug that needs to be converted to its active metabolite (clopi-H4) in two sequential cytochrome P450 (P450)-dependent steps. In the present study, a dynamic physiologically based pharmacokinetic (PBPK) model was developed in Simcyp for clopidogrel and clopi-H4 using a specific sequential metabolite module in four populations with phenotypically different CYP2C19 activity (poor, intermediate, extensive, and ultrarapid metabolizers) receiving a loading dose of 300 mg followed by a maintenance dose of 75 mg. This model was validated using several approaches. First, a comparison of predicted-to-observed area under the curve (AUC)0-24 obtained from a randomized crossover study conducted in four balanced CYP2C19-phenotype metabolizer groups was performed using a visual predictive check method. Second, the interindividual and intertrial variability (on the basis of AUC0-24 comparisons) between the predicted trials and the observed trial of individuals, for each phenotypic group, were compared. Finally, a further validation, on the basis of drug-drug-interaction prediction, was performed by comparing observed values of clopidogrel and clopi-H4 with or without dronedarone (moderate CYP3A4 inhibitor) coadministration using a previously developed and validated physiologically based PBPK dronedarone model. The PBPK model was well validated for both clopidogrel and its active metabolite clopi-H4, in each CYP2C19-phenotypic group, whatever the treatment period (300-mg loading dose and 75-mg last maintenance dose). This is the first study proposing a full dynamic PBPK model able to accurately predict simultaneously the pharmacokinetics of the parent drug and of its primary and secondary metabolites in populations with genetically different activity for a metabolizing enzyme.

Evaluation of the likelihood of a selective CHK1 inhibitor (LY2603618) to inhibit CYP2D6 with desipramine as a probe substrate in cancer patients

LY2603618 is a selective inhibitor of deoxyribonucleic acid damage checkpoint kinase 1 (CHK1) and has been in development for the enhancement of chemotherapeutic agents. The study described was to assess the potential interaction between LY2603618 and cytochrome P450 isoform 2D6 (CYP2D6) substrate desipramine in patients with cancer. Before clinical investigation, in silico simulations (using Simcyp®) were conducted. An open-label, two-period, fixed-sequence study was planned in 30 patients with advanced or metastatic cancers, in which a 50 mg oral dose of desipramine was administered alone and in combination with 275 mg of LY2603618 (i.v. infusion). An interim analysis was planned after 15 patients completed both periods. Ratios of geometric least squares means (LSMs) of primary pharmacokinetic (PK) parameters and 90% repeated confidence intervals (RCIs) between desipramine plus LY2603618 and desipramine alone were calculated. Lack of an interaction was declared if the 90% RCI fell between 0.8 and 1.25. The LSM ratios (90% RCI) for areas under the plasma concentration-time curve from time zero to tlast (AUC[0-tlast]) and to infinity (AUC[0-∞]) and maximum plasma concentration (Cmax) were 1.14 (1.04, 1.25), 1.09 (0.99, 1.21) and 1.16 (1.05, 1.29). In silico simulations were predictive of clinical results. Single doses of 275 mg LY2603618 administered with 50 mg desipramine were generally well tolerated. In conclusion, no clinically significant interaction was observed between LY2603618 and desipramine in patients with cancer. In silico predictions of clinical results demonstrated that mechanistic and physiologically based PK approaches may inform clinical study design in cancer patients.

Pharmacokinetic of antiepileptic drugs in patients with hepatic or renal impairment

Many factors influence choice of antiepileptic drugs (AEDs), including efficacy of the drug for the indication (epilepsy, neuropathic pain, affective disorder, migraine), tolerability, and toxicity. The first-generation AEDs and some newer AEDs are predominately eliminated by hepatic metabolism. Other recent AEDs are eliminated by renal excretion of unchanged drug or a combination of hepatic metabolism and renal excretion. The effect of renal and hepatic disease on the dosing will depend on the fraction of the AED eliminated by hepatic and/or renal excretion, the metabolic isozymes involved, as well as the extent of protein binding, if therapeutic drug monitoring is used. For drugs that are eliminated by renal excretion, methods of estimating creatinine clearance can be used to determine dose adjustments. For drugs eliminated by hepatic metabolism, there are no specific markers of liver function that can be used to provide guidance in dosage adjustments. Based on studies with probe drugs, the hepatic metabolic enzymes are differentially affected depending on the cause and severity of hepatic disease, which can aid in predicting dose adjustment when clinical data are not available. Several AEDs are also associated with laboratory markers of mild hepatic dysfunction and, rarely, more severe hepatic injury. In contrast, the risk of renal injury from AEDs is generally low. In general, co-morbid hepatic or renal diseases influence the decision for the selection of an AED. For some patients dosing changes to their existing AEDs may be appropriate. For others, a change to another AED may be a better option.

Expression of P450 and nuclear receptors in normal and end-stage Chinese livers

AIM: To investigate the expression of P450 enzyme genes by using end-stage liver disease samples and trimmed normal Chinese donor livers.

METHODS: The end-stage liver disease samples [n = 93, including hepatocellular carcinoma (HCC), peri-HCC tissue, hepatitis B virus cirrhosis, alcoholic cirrhosis, and severe cirrhosis] and trimmed normal Chinese donor livers (n = 35) from The Institute of Organ Transplantation in Beijing, China. Total RNA was extracted, purified, and subjected to real-time RT-PCR analysis.

RESULTS: For cytochrome P450 enzymes 1 (CYP1) family, the expression of CYP1A2 was decreased 90% in HCC, 80% in alcoholic cirrhosis, and 65% in severe cirrhosis. For CYP2 family, the expression of CAR was decreased 50% in HCC, but increased 50% in peri-HCC tissues. Similar decreases (about 50%) of CYP2B6, CYP2C9, CYP2C19, CYP2D6 and CYP2E1 were observed in HCC, as compared to peri-HCC tissues and normal livers. CYP2C19 were decreased in all end-stage liver diseases and CYP2E1 also decreased in alcoholic cirrhosis and severe cirrhosis. For CYP3 family, the expression of PXR was decreased 60% in HCC, together with decreases in CYP3A4, CYP3A5, and CYP3A7. In contrast, the expression of CYP3A7 was slightly increased in HBV cirrhosis. The expression of CYP4A11 was decreased 85% in HCC, 7% in alcoholic cirrhosis and severe liver cirrhosis, along with decreases in PPARα. The 93 end-stage livers had much higher inter-individual variations in gene expression than 35 normal livers.

CONCLUSION: The expression of CYP enzyme genes and corresponding nuclear receptors was generally decreased in end-stage liver diseases, and significant differences in gene expression were evident between peri-HCC and HCC.

In silico evaluation of gadofosveset pharmacokinetics in different population groups using the Simcyp® simulator platform

Purpose

Gadofosveset is a Gd-based contrast agent used for magnetic resonance imaging (MRI). Gadolinium kinetic distribution models are implemented in T1-weighted dynamic contrast-enhanced perfusion MRI for characterization of lesion sites in the body. Physiology changes in a disease state potentially can influence the pharmacokinetics of drugs and to this respect modify the distribution properties of contrast agents. This work focuses on the in silico modelling of pharmacokinetic properties of gadofosveset in different population groups through the application of physiologically-based pharmacokinetic models (PBPK) embedded in Simcyp® population pharmacokinetics platform.

Methods

Physicochemical and pharmacokinetic properties of gadofosveset were introduced into Simcyp® simulator platform and a min-PBPK model was applied. In silico clinical trials were generated simulating the administration of the recommended dose for the contrast agent (i.v., 30 mg/kg) in population cohorts of healthy volunteers, obese, renal and liver impairment, and in a generated virtual oncology population. Results were evaluated regarding basic pharmacokinetic parameters of Cmax, AUC and systemic CL and differences were assessed through ANOVA and estimation of ratio of geometric mean between healthy volunteers and the other population groups.

Results

Simcyp® predicted a mean Cmax = 551.60 mg/l, a mean AUC = 4079.12 mg/L*h and a mean systemic CL = 0.56 L/h for the virtual population of healthy volunteers. Obese population showed a modulation in Cmax and CL, attributed to increased administered dose. In renal and liver impairment cohorts a significant modulation in Cmax, AUC and CL of gadofosveset is predicted. Oncology population exhibited statistical significant differences regarding AUC when compared with healthy volunteers.

Conclusions

This work employed Simcyp® population pharmacokinetics platform in order to compute gadofosveset’s pharmacokinetic profiles through PBPK models and in silico clinical trials and evaluate possible differences between population groups. The approach showed promising results that could provide new insights regarding administration of contrast agents in special population cohorts. In silico pharmacokinetics could further be used for evaluating of possible toxicity, interpretation of MRI PK image maps and development of novel contrast agents.

Application of a physiologically based pharmacokinetic model informed by a top-down approach for the prediction of pharmacokinetics in chronic kidney disease patients

Quantitative prediction of the impact of chronic kidney disease (CKD) on drug disposition has become important for the optimal design of clinical studies in patients. In this study, clinical data of 151 compounds under CKD conditions were extensively surveyed, and alterations in pharmacokinetic parameters were evaluated. In CKD patients, the unbound hepatic intrinsic clearance decreased to a similar extent for drugs eliminated via hepatic metabolism by cytochrome P450, UDP-glucuronosyltransferase, and other mechanisms. Renal clearance showed a similar decrease to glomerular filtration rate, irrespective of the contribution of tubular secretion. The scaling factor (SF) obtained from the interquartile range of the relative change in each parameter was applied to the well-stirred model to predict clearance in patients. Hepatic and renal clearance could be successfully predicted for approximately half and two-thirds, respectively, of the applied compounds, showing the high utility of SFs. SFs were also introduced to a physiologically based pharmacokinetic (PBPK) model, and the plasma concentration profiles of 12 model compounds with different elimination pathways were predicted for CKD patients. The PBPK model combined with SFs provided good predictability for plasma concentration. The developed PBPK model with information on SFs would accelerate translational research in drug development by predicting pharmacokinetics in CKD patients.

Microsomal protein per gram of liver (MPPGL) in paediatric biliary atresia patients

The microsomal protein per gram of liver (MPPGL) is an important scaling factor in the in vitro-in vivo extrapolation of metabolic data obtained in liver microsomes. This study aimed to determine the MPPGL in four biliary atresia patients (0.6-1.6 years old) undergoing liver transplantation, as it is known that the MPPGL is affected by age and possibly by liver disease. Due to the presence of bilirubin in the homogenates and microsomes, the NADPH-cytochrome reductase activity was used to determine the recovery factor, rather than methods using the dithionite difference spectrum. A mean value of 18.73 (± 2.82) mg/g (geometric mean ± SD, n = 4) was observed, which is lower than the expected MPPGL based on the age of the patients (26.60 ± 0.40 mg/g). This suggests a decreased amount of microsomal protein in the livers of biliary atresia patients. Moreover, no differences in MPPGL between different zones of the liver could be detected.

Physiologically based pharmacokinetic modeling framework for quantitative prediction of an herb-drug interaction

Herb-drug interaction predictions remain challenging. Physiologically based pharmacokinetic (PBPK) modeling was used to improve prediction accuracy of potential herb-drug interactions using the semipurified milk thistle preparation, silibinin, as an exemplar herbal product. Interactions between silibinin constituents and the probe substrates warfarin (CYP2C9) and midazolam (CYP3A) were simulated. A low silibinin dose (160 mg/day × 14 days) was predicted to increase midazolam area under the curve (AUC) by 1%, which was corroborated with external data; a higher dose (1,650 mg/day × 7 days) was predicted to increase midazolam and (S)-warfarin AUC by 5% and 4%, respectively. A proof-of-concept clinical study confirmed minimal interaction between high-dose silibinin and both midazolam and (S)-warfarin (9 and 13% increase in AUC, respectively). Unexpectedly, (R)-warfarin AUC decreased (by 15%), but this is unlikely to be clinically important. Application of this PBPK modeling framework to other herb-drug interactions could facilitate development of guidelines for quantitative prediction of clinically relevant interactions.CPT Pharmacometrics Syst. Pharmacol. (2014) 3, e107; doi:10.1038/psp.2013.69; advance online publication 26 March 2014.

Relevance of Liver Failure for Anti-Infective Agents: From Pharmacokinetic Alterations to Dosage Adjustments

The liver is a complex organ with great ability to influence drug pharmacokinetics. Due to its wide array of function, its impairment has the potential to affect bioavailability, enterohepatic circulation, drug distribution, metabolism, clearance, and biliary elimination. These alterations differ widely depending on the cause of the liver failure, if it is acute or chronic in nature, the extent of impairment, and comorbid conditions. In addition, effects on liver functions do not occur in a proportional or predictable manner for escalating degrees of liver impairment. The ability of hepatic alterations to influence PK is also dependent on drug characteristics, such as administration route, chemical properties, protein binding, and extraction ratio, among others. This complexity makes it difficult to predict what these effects have on drugs. Unlike certain classes of agents, efficacy of anti-infectives is most often dependent on fulfilling pharmacokinetic/pharmacodynamic targets, such as C_max/MIC, AUC/MIC, T_>MIC, IC₅₀/EC₅₀, or T>EC₉₅. Loss of efficacy, or conversely, increased risk of toxicity may occur in certain circumstances of liver injury. Although important to consider these potential alterations and their effects on specific anti-infectives, many lack data to constitute specific dosing adjustments, making it important to monitor patients for effectiveness and toxicities of therapy.

Biomechanics and functionality of hepatocytes in liver cirrhosis

Cirrhosis is a life-threatening condition that is generally attributed to overproduction of collagen fibers in the extracellular matrix that mechanically stiffens the liver. Chronic liver injury due to causes including viral hepatitis, inherited and metabolic liver diseases and external factors such as alcohol abuse can result in the development of cirrhosis. Progression of cirrhosis leads to hepatocellular dysfunction. While extensive studies to understand the complexity underlying liver fibrosis have led to potential application of anti-fibrotic drugs, no such FDA-approved drugs are currently available. Additional studies of hepatic fibrogenesis and cirrhosis primarily have focused on the extracellular matrix, while hepatocyte biomechanics has received limited attention. The role of hepatocyte biomechanics in liver cirrhosis remains elusive, and how the cell stiffness is correlated with biological functions of hepatocytes is also unknown. In this study, we demonstrate that the biomechanical properties of hepatocytes are correlated with their functions (e.g., glucose metabolism), and that hepatic dysfunction can be restored through modulation of the cellular biomechanics. Furthermore, our results indicate the hepatocyte functionality appears to be regulated through a crosstalk between the Rho and Akt signaling. These novel findings may lead to biomechanical intervention of hepatocytes and the development of innovative tissue engineering for clinical treatment to target liver cells rather than exclusively focusing on the extracellular matrix alone in liver cirrhosis.

In vitro-in vivo extrapolation of drug-induced proarrhythmia predictions at the population level

Drug cardiotoxicity is a serious issue for patients, regulators, pharmaceutical companies and health service payers because they are all affected by its consequences. Despite the wide range of data they generate, existing approaches for cardiac safety testing might not be adequate and sufficiently cost-effective, probably as a result of the complexity of the problem. For this reason, translational tools (based on biophysically detailed, mathematical models) allowing for in vitro-in vivo extrapolation are gaining increasing interest. This current review describes approaches that can be used for cardiac safety assessment at the population level, by accounting for various sources of variability including kinetics of the compound of interest.

PBPK models for the prediction of in vivo performance of oral dosage forms

Drug absorption from the gastrointestinal (GI) tract is a highly complex process dependent upon numerous factors including the physicochemical properties of the drug, characteristics of the formulation and interplay with the underlying physiological properties of the GI tract. The ability to accurately predict oral drug absorption during drug product development is becoming more relevant given the current challenges facing the pharmaceutical industry. Physiologically-based pharmacokinetic (PBPK) modeling provides an approach that enables the plasma concentration-time profiles to be predicted from preclinical in vitro and in vivo data and can thus provide a valuable resource to support decisions at various stages of the drug development process. Whilst there have been quite a few successes with PBPK models identifying key issues in the development of new drugs in vivo, there are still many aspects that need to be addressed in order to maximize the utility of the PBPK models to predict drug absorption, including improving our understanding of conditions in the lower small intestine and colon, taking the influence of disease on GI physiology into account and further exploring the reasons behind population variability. Importantly, there is also a need to create more appropriate in vitro models for testing dosage form performance and to streamline data input from these into the PBPK models. As part of the Oral Biopharmaceutical Tools (OrBiTo) project, this review provides a summary of the current status of PBPK models available. The current challenges in PBPK set-ups for oral drug absorption including the composition of GI luminal contents, transit and hydrodynamics, permeability and intestinal wall metabolism are discussed in detail. Further, the challenges regarding the appropriate integration of results from in vitro models, such as consideration of appropriate integration/estimation of solubility and the complexity of the in vitro release and precipitation data, are also highlighted as important steps to advancing the application of PBPK models in drug development. It is expected that the "innovative" integration of in vitro data from more appropriate in vitro models and the enhancement of the GI physiology component of PBPK models, arising from the OrBiTo project, will lead to a significant enhancement in the ability of PBPK models to successfully predict oral drug absorption and advance their role in preclinical and clinical development, as well as for regulatory applications.

Predicting drug-drug interactions: application of physiologically based pharmacokinetic models under a systems biology approach

The development of in vitro-in vivo extrapolation (IVIVE), a 'bottom-up' approach, to predict pharmacokinetic parameters and drug-drug interactions (DDIs) has accelerated mainly due to an increase in the understanding of the multiple mechanisms involved in these interactions and the availability of appropriate in vitro systems that act as surrogates for delineating various elements of the interactions relevant to absorption, distribution, metabolism and elimination. Recent advances in the knowledge of the population variables required for IVIVE (demographic, anatomical, genetic and physiological parameters) have also contributed to the appreciation of the sources of variability and wider use of this approach for different scenarios within the pharmaceutical industry. Initially, the authors present an overview of the integration of IVIVE into 'static' and 'dynamic' models for the quantitative prediction of DDIs. The main purpose of this review is to discuss the application of IVIVE in conjunction with physiologically based pharmacokinetic modeling under a systems biology approach to characterize the potential DDIs in individual patients, including those who cannot be investigated in formal clinical trials for ethical reasons. In addition, we address the issues related to the prediction of complex DDIs involving the inhibition of cytochrome P- and transporter-mediated activities through multiple drugs.

Approaches for dosage individualisation in critically ill patients

INTRODUCTION

Pharmacokinetic variability in critically ill patients is the result of the overlapping of multiple pathophysiological and clinical factors. Unpredictable exposure from standard dosage regimens may influence the outcome of treatment. Therefore, strategies for dosage individualisation are recommended in this setting.

AREAS COVERED

The authors focus on several approaches for dosage individualisation that have been developed, ranging from the well-established therapeutic drug monitoring (TDM) up to the innovative application of pharmacogenomics criteria. Furthermore, the authors summarise the specific population pharmacokinetic models for different drugs developed for critically ill patients to improve the initial dosage selection and the Bayesian forecasting of serum concentrations. The authors also consider the use of Monte Carlo simulation for the selection of dosage strategies.

EXPERT OPINION

Pharmacokinetic/pharmacodynamics (PK/PD) modelling and dosage individualisation methods based on mathematical and statistical criteria will contribute in improving pharmacologic treatment in critically ill patients. Moreover, substantial effort will be necessary to integrate pharmacogenomics criteria into critical care practice. The lack of availability of target biomarkers for dosage adjustment emphasizes the value of TDM which allows a large part of treatment outcome variability to be controlled.