Trevor N. Johnson

Prediction of the Clearance of Eleven Drugs and Associated Variability in Neonates, Infants and Children

BackgroundPrediction of the exposure of neonates, infants and children to xenobiotics is likely to be more successful using physiologically based pharmacokinetic models than simplistic allometric scaling, particularly in younger children. However, such models require comprehensive information on the ontogeny of anatomical, physiological and biochemical variables; data that are not available from single sources.The Simcyp® software integrates demographic, genetic, physiological and pathological information on adults with in vitro data on human drug metabolism and transport to predict population distributions of drug clearance (CL) and the extent of metabolic drug-drug interactions. The algorithms have now been extended to predict clearance and its variability in paediatric populations by incorporating information on developmental physiology and the ontogeny of specific cytochrome P450s.MethodsValues of the clearance (median and variability) of 11 drugs (midazolam [oral and intravenous], caffeine, carbamazepine, cisapride, theophylline, diclofenac, omeprazole, S-warfarin, phenytoin, gentamicin and vancomycin) were predicted for 2000 virtual subjects (birth to 18 years). In vitro enzyme pharmacokinetic parameters (maximum rate of metabolism [Vmax] and Michaelis-Menten constant [Km]) and in vivo clearance data were obtained from the literature.ResultsIn neonates 70% (7/10) of predicted median clearance values were within 2-fold of the observed values. Corresponding results for infants, children and adolescents were 100% (9/9), 89% (17/19) and 94% (17/18), respectively. Predicted variability (95% confidence interval) was within 2-fold of the observed values in 70% (7/10), 67% (6/9), 63% (12/19) and 55% (10/18) of cases, respectively. The accuracy of the physiologically based model incorporated in the Simcyp® software was superior to that of simple allometry, especially in children <2 years old.ConclusionThe in silico prediction of pharmacokinetic behaviour in paediatric patients is not intended to replace clinical studies. However, it provides a valuable aid to decision-making with regard to first-time dosing in children and study design. The clinical study then becomes ‘confirmatory’ rather than ‘exploratory’.

Changes in liver volume from birth to adulthood: a meta-analysis.

A diversity of equations is available for the estimation of liver volume (LV), derived from studies in populations of ethnically homogeneous individuals and using a variety of methods of measurement. The aim of this study was to integrate all published pediatric data and to define a general equation for estimating LV from birth onward. Data were collated from 5,036 subjects (birth to 18 yr old). Equations were developed based on simple regression against body surface area (BSA) and multiple regression of LV with weight, height, BSA, age, gender, race, methodology, and year of publication as covariates. These equations, together with those reported in the literature, were compared for accuracy of prediction of LV from birth to 18 yr old. The most parsimonious equation to describe LV was selected according to the Akaike information criteria (AIC), precision and bias and following visual inspection of residual errors and observed vs. predicted plots: LV = 0.722 * BSA1.176. The multiple regression models indicated that Japanese have up to 19% larger livers compared to Caucasians for a given body weight. Radiographic and ultrasonic measurements were associated with up to 8% lower estimates of liver size compared to measurements made at autopsy. There was no evidence that gender or the year in which a study was published (1933–1999) influenced the estimation of LV. The general equation was also applied to predict adult LV, and its precision and accuracy was found to be superior to those of 10/11 published adult models. In conclusion, we have developed a more general model to predict LV in pediatric populations and young adults, and have investigated a range of covariates. (Liver Transpl 2005;12:1481–1493.)

Anatomical, Physiological and Metabolic Changes with Gestational Age during Normal Pregnancy A Database for Parameters Required in Physiologically Based Pharmacokinetic Modelling

AbstractBackground: Pregnancy is associated with considerable changes in the physiological, anatomical and biochemical attributes in women. These may alter the exposure to xenobiotics between pregnant and non-pregnant women who receive similar doses, with implications for different susceptibility to environmental pollutants or therapeutic agents. Physiologically based pharmacokinetic (PBPK) models together with in vitro in vivo extrapolation (IVIVE) of absorption, distribution, metabolism and excretion (ADME) characteristics may capture the likely changes. However, such models require comprehensive information on the longitudinal variations of PBPK parameter values; a set of data that are as yet not available from a singular source. Aim: The aim of this article was to collect, integrate and analyse the available time-variant parameters that are needed for the PBPK modelling of xenobiotic kinetics in a healthy pregnant population. Methods: A structured literature search was carried out on anatomical, physiological and biochemical parameters likely to change in pregnancy and alter the kinetics of xenobiotics. Collated data were carefully assessed, integrated and analysed for trends with gestational age. Algorithms were generated to describe the changes in parameter values with gestational age. These included changes in maternal weight, the individual organ volumes and blood flows, glomerular filtration rates, and some drug-metabolising enzyme activities. Results: Articles were identified using relevant keywords, quality appraised and data were extracted by two investigators. Some parameters showed no change with gestational age and for others robust data were not available. However, for many parameters significant changes were reported during the course of pregnancy, e.g. cardiac output, protein binding and expression/activity of metabolizing enzymes. The trend for time-variant parameters was not consistent (with respect to direction and mono-tonicity). Hence, various mathematical algorithms were needed to describe individual parameter values. Conclusion: Despite the limitations identified in the availability of some values, the collected data presented in this paper provide a potentially useful singular resource for key parameters needed for PBPK modelling in pregnancy. This facilitates the risk assessment of environmental chemicals and therapeutic drug dose adjustments in the pregnant population.

The problems in scaling adult drug doses to children

Background: Many drugs are unlicensed in children and consequently their doses have been scaled down from those used in adults. Objective: To compare the performance of three scaling models in predicting maintenance doses for children from those used in adults. Methods: Three scaling models based on body weight (BW), body surface area (BSA) and BW0.75 were used to predict maintenance doses across the paediatric age band from the equivalent adult doses for 30 different drugs. The predicted doses were compared with those in the British National Formulary for children 2006 (BNFc). Percentage error and mean squared prediction error were used as a measure of precision, and mean prediction error was used as a measure of bias. Results: In the 1-month and 12-month age groups, the different approaches ranked on their bias (least bias first) were BWBW0.75>BSA. The BSA and BW0.75 methods predicted doses up to 2.86-fold higher than the BNFc in the 1-month and 1-year age group. In the 7-year and 12-year age groups, BW0.75 and BSA performed better than BW for precision and bias, and no predictions were more than 1.8-fold higher than the BNFc. The BW method tended to also under-predict dose across the paediatric age range. Conclusions: Dose scaling should only be used as a last resort for determining a suitable dose in children. No single method was suitable across the entire paediatric age range.

Resurgence in the use of physiologically based pharmacokinetic models in pediatric clinical pharmacology: parallel shift in incorporating the knowledge of biological elements and increased applicability to drug development and clinical practice

Aims and Objectives:  (i) To describe an example of the development work required for building a ‘pediatric physiologically based pharmacokinetic’ (P‐PBPK) model (Simcyp Pediatric ADME Simulator), (ii) to replicate pediatric clinical studies and undertake theoretical studies to show the potential applications of mechanistic PBPK in pediatric drug clinical investigation and practice, with emphasis on pediatric anesthesia.

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

AbstractBackground and Objective: Liver cirrhosis is characterized by a decrease in functional hepatocytes, lowered circulating levels of plasma proteins and alterations in blood flow due to the development of portacaval shunts. Depending on the interplay between these parameters and the characteristics of an administered drug, varying degrees of impaired systemic clearance and first-pass metabolism are anticipated. The Simcyp Population-based ADME Simulator has already been used successfully to incorporate genetic, physiological and demographic attributes of certain subgroups within healthy populations into in vitro-in vivo extrapolation (IVIVE) of xenobiotic clearance. The objective of this study was to extend population models to predict systemic and oral drug clearance in relation to the severity of liver cirrhosis. Methods: Information on demographics, changes in hepatic blood flow, cytochrome P450 enzymes, liver size, plasma protein binding and renal function was incorporated into three separate population libraries. The latter corresponded to Child-Pugh were used to predict tscores A (mild), B (moderate) and C (severe) liver cirrhosis. These libraries, together with mechanistic IVIVE within the Simcyp Simulator, he clearance of intravenous and oral midazolam, oral caffeine, intravenous and oral theophylline, intravenous and oral metoprolol, oral nifedipine, oral quinidine, oral diclofenac, oral sildenafil, and intravenous and oral omeprazole. The simulated patients matched the clinical studies as closely as possible with regard to demographics and Child-Pugh scores. Predicted clearance values in both healthy control and liver cirrhosis populations were compared with observed values, as were the fold increases in clearance values between these populations. Results: There was good agreement (lack of statistically significant difference, two-tailed paired t-test) between observed and predicted clearance ratios, with the exception of those for two studies of intravenous omeprazole. Predicted clearance ratios were within 0.8- to 1.25-fold of observed ratios in 65% of cases (range 0.34- to 2.5-fold). Conclusion: The various drugs that were studied showed different changes in clearance in relation to disease severity, and a ‘one size fits all’ solution does not exist without considering the multiple sources of the changes. Predictions of the effects of liver cirrhosis on drug clearance are of potential value in the design of clinical studies during drug development and, clinically, in the assessment of likely dosage adjustment.

Development of CYP2D6 and CYP3A4 in the first year of life

methadone requirements. We agree that further research is required to investigate this discrepancy between the observations of the two studies, particularly with patient groups receiving comparable daily doses of methadone. In addition, the clinical usefulness of other markers, such as plasma concentrations and pharmacodynamic responses to methadone, should also be considered as a more appropriate reflection of how much methadone is reaching the site of action, as opposed to a daily dose which is influenced to a greater extent by many confounding pharmacokinetic and environmental factors. Multinational prospective clinical trials incorporating pharmacogenomics meeting the ‘‘gold standard of methodology’’ are now required to improve methadone efficacy in a population difficult to treat with substitution pharmacotherapies.

A pregnancy physiologically based pharmacokinetic (p‐PBPK) model for disposition of drugs metabolized by CYP1A2, CYP2D6 and CYP3A4

AIMS Pregnant women are usually not part of the traditional drug development programme. Pregnancy is associated with major biological and physiological changes that alter the pharmacokinetics (PK) of drugs. Prediction of the changes to drug exposure in this group of patients may help to prevent under- or overtreatment. We have used a pregnancy physiologically based pharmacokinetic (p-PBPK) model to assess the likely impact of pregnancy on three model compounds, namely caffeine, metoprolol and midazolam, based on the knowledge of their disposition in nonpregnant women and information from in vitro studies. METHODS A perfusion-limited form of a 13-compartment full-PBPK model (Simcyp® Simulator) was used for the nonpregnant women, and this was extended to the pregnant state by applying known changes to all model components (including the gestational related activity of specific cytochrome P450 enzymes) and through the addition of an extra compartment to represent the fetoplacental unit. The uterus and the mammary glands were grouped into the muscle compartment. The model was implemented in Matlab Simulink and validated using clinical observations. RESULTS The p-PBPK model predicted the PK changes of three model compounds (namely caffeine, metoprolol and midazolam) for CYP1A2, CYP2D6 and CYP3A4 during pregnancy within twofold of observed values. The changes during the third trimester were predicted to be a 100% increase, a 30% decrease and a 35% decrease in the exposure of caffeine, metoprolol and midazolam, respectively, compared with the nonpregnant women. CONCLUSIONS In the absence of clinical data, the in silico prediction of PK behaviour during pregnancy can provide a valuable aid to dose adjustment in pregnant women. The performance of the model for drugs metabolized by a single enzyme to different degrees (high and low extraction) and for drugs that are eliminated by several different routes warrants further study.

Application of a systems approach to the bottom-up assessment of pharmacokinetics in obese patients: Expected variations in clearance

Background and Objectives: The maintenance dose of a drug is dependent on drug clearance, and thus any biochemical and physiological changes in obesity that affect parameters such as cardiac output, renal function, expression of drug-metabolizing enzymes and protein binding may result in altered clearance compared with that observed in normal-weight subjects (corrected or uncorrected for body weight). Because of the increasing worldwide incidence of obesity, there is a need for more information regarding the optimal dosing of drug therapy to be made available to prescribers. This is usually provided via clinical studies in obese people; however, such studies are not available for all drugs that might be used in obese subjects. Incorporation of the relevant physiological and biochemical changes into predictive bottom-up pharmacokinetic models in order to optimize dosage regimens may offer a logical way forward for the cases where no clinical data exist. The aims of the current report are to apply such a ‘systems approach’ to identify the likelihood of observing variations in the clearance of drugs in obesity and morbid obesity for a set of compounds for which clinical data, as well as the necessary in vitro information, are available, and to provide a framework for assessing other drugs in the future.Methods: The population-specific changes in demographic, physiological and biochemical parameters that are known to be relevant to obese and morbidly obese subjects were collated and incorporated into two separate population libraries. These libraries, together with mechanistic in vitro-in vivo extrapolations (IVIVE) within the Simcyp Population-based Simulator™, were used to predict the clearance of oral alprazolam, oral caffeine, oral chlorzoxazone, oral ciclosporin, intravenous and oral midazolam, intravenous phenytoin, oral theophylline and oral triazolam. The design of the simulated studies was matched as closely as possible with that of the clinical studies. Outcome was measured by the predicted ratio of the clearance of the drug in obese and lean subjects ± its 90% confidence interval, compared with observed values. The overall statistical measures of the performance of the model to detect differences in compound clearance between obese and lean populations were investigated by measuring sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). A power calculation was carried out to investigate the impact of the sample size on the overall outcome of clinical studies.Results: The model was successful in predicting clearance in obese subjects, with the degree to which simulations could mimic the outcome of in vivo studies being greater than 60% for six of the eight drugs. A clear difference in the clearance of chlorzoxazone was correctly picked up via simulation. The overall statistical measures of the performance of the Simcyp Simulator were 100% sensitivity, 66% specificity, 60% PPV and 100% NPV. Studies designed on the basis of the ratio of the absolute values required substantial numbers of participants in order to detect a significant difference, except for phenytoin and chlorzoxazone, where the ratios of the weight-normalized clearances generally showed statistically significant differences with a smaller number of subjects.Conclusion: Extension of a mechanistic predictive pharmacokinetic model to accommodate physiological and biochemical changes associated with obesity and morbid obesity allowed prediction of changes in drug clearance on the basis of in vitro data, with reasonable accuracy across a range of compounds that are metabolized by different enzymes. Prediction of the effects of obesity on drug clearance, normalized by various body size scalars, is of potential value in the design of clinical studies during drug development and in the introduction of dosage adjustments that are likely to be needed in clinical practice.

Age related changes in fractional elimination pathways for drugs: assessing the impact of variable ontogeny on metabolic drug-drug interactions.

The magnitude of any metabolic drug–drug interactions (DDIs) depends on fractional importance of inhibited pathway which may not necessarily be the same in young children when compared to adults. The ontogeny pattern of cytochrome P450 (CYP) enzymes (CYPs 1A2, 2B6, 2C8, 2C9, 2C18/19, 2D6, 2E1, 3A4) and renal function were analyzed systematically. Bootstrap methodology was used to account for variability, and to define the age range over which statistical differences existed between each pair of specific pathways. A number of DDIs were simulated (Simcyp Pediatric v12) for virtual compounds to highlight effects of age on fractional elimination and consequent magnitude of DDI. For a theoretical drug metabolized 50% by each of CYP2D6 and CYP3A4 pathways at birth, co‐administration of ketoconazole (3 mg/kg) resulted in a 1.65‐fold difference between inhibited versus uninhibited AUC compared to 2.4‐fold in 1 year olds and 3.2‐fold in adults. Conversely, neonates could be more sensitive to DDI than adults in certain scenarios. Thus, extrapolation from adult data may not be applicable across all pediatric age groups. The use of pediatric physiologically based pharmacokinetic (p‐PBPK) models may offer an interim solution to uncovering potential periods of vulnerability to DDI where there are no existing clinical data derived from children.