John C. Lipscomb

Scaling Factors for the Extrapolation of In Vivo Metabolic Drug Clearance From In Vitro Data: Reaching a Consensus on Values of Human Micro-somal Protein and Hepatocellularity Per Gram of Liver

Reported predictions of human in vivo hepatic clearance from in vitro data have used a variety of values for the scaling factors human microsomal protein (MPPGL) and hepatocellularity (HPGL) per gram of liver, generally with no consideration of the extent of their inter-individual variability. We have collated and analysed data from a number of sources, to provide weighted meangeo values of human MPPGL and HPGL of 32 mg g-1 (95% Confidence Interval (CI); 29-34 mg.g-1) and 99x10(6) cells.g-1 (95% CI; 74-131 mg.g-1), respectively. Although inter-individual variability in values of MPPGL and HPGL was statistically significant, gender, smoking or alcohol consumption could not be detected as significant covariates by multiple linear regression. However, there was a weak but statistically significant inverse relationship between age and both MPPGL and HPGL. These findings indicate the importance of considering differences between study populations when forecasting in vivo pharmacokinetic behaviour. Typical clinical pharmacology studies, particularly in early drug development, use young, fit, healthy male subjects of around 30 years of age. In contrast, the average age of patients for many diseases is about 60 years of age. The relationship between age and MPPGL observed in this study estimates values of 40 mg.g-1 for a 30 year old individual and 31 mg.g-1 for a 60 year old individual. Investigators may wish to consider the reported covariates in the selection of scaling factors appropriate for the population in which estimates of clearance are being predicted. Further studies are required to clarify the influence of age (especially in paediatric subjects), donor source and ethnicity on values of MPPGL and HPGL. In the meantime, we recommend that the estimates (and their variances) from the current meta-analysis be used when predicting in vivo kinetic parameters from in vitro data.

Guidelines for the communication of Biomonitoring Equivalents: Report from the Biomonitoring Equivalents Expert Workshop

Biomonitoring Equivalents (BEs) are screening tools for interpreting biomonitoring data. However, the development of BEs brings to the public a relatively novel concept in the field of health risk assessment and presents new challenges for environmental risk communication. This paper provides guidance on methods for conveying information to the general public, the health care community, regulators and other interested parties regarding how chemical-specific BEs are derived, what they mean in terms of health, and the challenges and questions related to interpretation and communication of biomonitoring data. Key communication issues include: (i) developing a definition of the BE that accurately captures the BE concept in lay terms, (ii) how to compare population biomonitoring data to BEs, (iii) interpreting biomonitoring data that exceed BEs for a specific chemical, (iv) how to best describe the confidence in chemical-specific BEs, and (v) key requirements for effective communication with health care professionals. While the risk communication literature specific to biomonitoring is sparse, many of the concepts developed for traditional risk assessments apply, including transparency and discussions of confidence and uncertainty. Communication of BEs will require outreach, education, and development of communication materials specific to several audiences including the lay public and health care providers.

In vitro measurements of metabolism for application in pharmacokinetic modeling

Human risk and exposure assessments require dosimetry information. Species-specific tissue dose response will be driven by physiological and biochemical processes. While metabolism and pharmacokinetic data are often not available in humans, they are much more available in laboratory animals; metabolic rate constants can be readily derived in vitro. The physiological differences between laboratory animals and humans are known. Biochemical processes, especially metabolism, can be measured in vitro and extrapolated to account for in vivo metabolism through clearance models or when linked to a physiologically based pharmacological (PBPK) model to describe the physiological processes, such as drug delivery to the metabolic organ. This review focuses on the different organ, cellular, and subcellular systems that can be used to measure in vitro metabolic rate constants and how those data are extrapolated to be used in biologically based modeling. NOTICE: The views expressed in this paper are those of the authors and do not necessarily reflect the views and policies of the U.S. Environmental Protection Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

Covariation of Human Microsomal Protein Per Gram of Liver with Age: Absence of Influence of Operator and Sample Storage May Justify Interlaboratory Data Pooling

Scaling of metabolic clearance values from liver microsomal data or recombinantly expressed cytochrome P450 enzymes to predict human hepatic clearance requires knowledge of the amount of microsomal protein per gram of liver (MPPGL). Identification of physiological covariates of MPPGL requires analysis of values from large diverse populations, which necessitates pooling of data from numerous sources. To ensure compatibility between results obtained within and between studies, the impact of interoperator differences and sample storage on values of MPPGL was investigated. With use of triplicate samples from one liver (HL86), no statistically significant difference was detected between values of MPPGL prepared from samples stored at -80°C (23.5 ± 1.2 mg g-1) and those determined using fresh tissue (21.9 ± 0.3 mg g-1). Although there was a significant difference in the yield of microsomal protein obtained from another liver sample (HL43) by three different operators (17 ± 1, 19 ± 2, and 24 ± 1 mg g-1; p = 0.004, analysis of variance), no difference was observed in the estimated MPPGL after application of appropriate correction factors for each operator (28 ± 1, 30 ± 5, and 31 ± 4 mg g-1). The result provided justification for pooling reported values of MPPGL for use in covariate analysis. Investigation of the relationship between age and MPPGL provided preliminary evidence that MPPGL values increase from birth to a maximum of 40 mg g-1 [95% confidence interval for the geometric mean (95% CI meangeo): 37–43 mg g-1 at approximately 28 years followed by a gradual decrease in older age (mean of 29 mg g-1 at 65 years; 95% CI meangeo: 27–32 mg g-1). Accordingly, appropriate age-adjusted scaling factors should be used in extrapolating in vitro clearance values to clinical studies.

Potential health effects of drinking water disinfection by-products using quantitative structure toxicity relationship☆

Disinfection by-products (DBPs) are produced as a result of disinfecting water using various treatment methods. Over the years, chlorine has remained the most popular disinfecting agent due to its ability to kill pathogens. However, in 1974, it was discovered that the superchlorination of drinking water resulted in the production of chloroform and other trihalomethanes. Since then hundreds of additional DBPs have been identified, including haloacetic acids and haloacetonitriles with very little or no toxicological data available, thus necessitating the use of additional methods for hazard estimation. Quantitative Structure Toxicity Relationship (QSTR) is one such method and utilizes a computer-based technology to predict the toxicity of a chemical solely from its molecular attributes. The current research was conducted utilizing the TOPKAT/QSTR software package which is comprised of robust, cross-validated QSTR models for assessing mutagenicity, rodent carcinogenicity (female/male; rat/mouse), developmental toxicity, skin sensitization, lowest-observed-adverse-effect level (LOAEL), fathead minnow LC(50), rat oral LD(50) and Daphia magna EC(50). A total of 252 DBPs were analyzed for the likelihood that they would produce tumors and developmental effects using the carcinogenicity and developmental toxicity submodels of TOPKAT. The model predictions were evaluated to identify generalizations between the functional groups (e.g. alcohols, acids, etc.) and specific toxic endpoints. Developmental toxicity was identified as an endpoint common to the majority of aliphatic mono- and dicarboxylic acids, aliphatic halogenated and non-halogenated ketones, and aliphatic haloacetonitriles. In the case of the carcinogenicity submodels, most aliphatic aldehydes were identified as carcinogens only in the female mouse submodel. The majority of the aliphatic and aromatic dicarboxylic acids were identified as carcinogens in the female rat submodel. All other functional groups examined were largely predicted as non-carcinogens in all the cancer submodels (i.e. male/female rats and mice). The QSTR results should aid in the prioritization for evaluation of toxic endpoints in the absence of in vivo bioassays.

A feasibility study of cumulative risk assessment methods for drinking water disinfection by-product mixtures.

Humans are exposed daily to complex mixtures of chemicals, including drinking water disinfection by-products (DBPs) via oral, dermal, and inhalation routes. Some positive epidemiological and toxicological studies suggest reproductive and developmental effects and cancer are associated with consumption of chlorinated drinking water. Thus, the U.S. Environmental Protection Agency (EPA) conducted research to examine the feasibility of evaluating simultaneous exposures to multiple DBPs via all three exposure routes. A cumulative risk assessment approach was developed for DBP mixtures by combining exposure modeling and physiologically based pharmacokinetic modeling results with a new mixtures risk assessment method, the cumulative relative potency factors (CRPF) approach. Internal doses were estimated for an adult female and an adult male, each of reproductive age, and for a child (age 6 yr) inclusive of oral, dermal, and inhalation exposures. Estimates of the daily internal doses were made for 13 major DBPs, accounting for activity patterns that affect the amount of human contact time with drinking water (e.g., tap water consumed, time spent showering), building characteristics (e.g., household air volumes), and physicochemical properties of the DBPs (e.g., inhalation rates, skin permeability rates, blood:air partition coefficients). A novel cumulative risk assessment method, the CRPF approach, is advanced that integrates the principles of dose addition and response addition to produce multiple-route, chemical mixture risk estimates using total absorbed doses. Research needs to improve this approach are presented.

Approaches for Applications of Physiologically Based Pharmacokinetic Models in Risk Assessment

Physiologically based pharmacokinetic (PBPK) models are particularly useful for simulating exposures to environmental toxicants for which, unlike pharmaceuticals, there is often little or no human data available to estimate the internal dose of a putative toxic moiety in a target tissue or an appropriate surrogate. This article reviews the current state of knowledge and approaches for application of PBPK models in the process of deriving reference dose, reference concentration, and cancer risk estimates. Examples drawn from previous U.S. Environmental Protection Agency (EPA) risk assessments and human health risk assessments in peer-reviewed literature illustrate the ways and means of using PBPK models to quantify the pharmacokinetic component of the interspecies and intraspecies uncertainty factors as well as to conduct route to route, high dose to low dose and duration extrapolations. The choice of the appropriate dose metric is key to the use of the PBPK models for the various applications in risk assessment. Issues related to whether uncertainty factors are most appropriately applied before or after derivation of human equivalent dose (or concentration) continue to be explored. Scientific progress in the understanding of life stage and genetic differences in dosimetry and their impacts on variability in susceptibility, as well as ongoing development of analytical methods to characterize uncertainty in PBPK models, will make their use in risk assessment increasingly likely. As such, it is anticipated that when PBPK models are used to express adverse tissue responses in terms of the internal target tissue dose of the toxic moiety rather than the external concentration, the scientific basis of, and confidence in, risk assessments will be enhanced.

Physiologically-Based Pharmacokinetic (PBPK) Models in Toxicity Testing and Risk Assessment

Physiologically-based pharmacokinetic (PBPK) modeling offers a scientifically-sound framework for integrating mechanistic data on absorption, distribution, metabolism and elimination to predict the time-course of parent chemical, metabolite(s) or biomarkers in the exposed organism. A major advantage of PBPK models is their ability to forecast the impact of specific mechanistic processes and determinants on the tissue dose. In this regard, they facilitate integration of data obtained with in vitro and in silico methods, for making predictions of the tissue dosimetry in the whole animal, thus reducing and/or refining the use of animals in pharmacokinetic and toxicity studies. This chapter presents the principles and practice of PBPK modeling, as well as the application of these models in toxicity testing and health risk assessments.

Differences Between Human and Rat Intestinal and Hepatic Bisphenol-A Glucuronidation and the Influence of Alamethicin on In vitro Kinetic Measurements

The extent to which membrane-disrupting agents, such as alamethicin, may alter cofactor transport and influence in vitro kinetic measurements of glucuronidation is a major concern regarding the characterization and extrapolation of inter- and intraspecies pharmacokinetics of bisphenol A (BPA). An additional concern is the omission of a BPA intestinal metabolism component in current pharmacokinetic models used to assess oral exposure. In this study, BPA glucuronidation in native hepatic microsomes from female rat and female human liver displayed higher Vmax values than that in males. In the presence of alamethicin, all hepatic Vmax values increased; however, this increase was disproportionately greater in males and gender differences were no longer observed. Female rats exhibited a much higher Km than all other species and genders; the addition of alamethicin had little influence on Km values for any of the test systems. The dissimilar Km measured for female rat suggests that different UDP-glucuronosyltransferase (UGT) enzyme(s) are involved in BPA glucuronidation. The presence of different UGTs in female rat was confirmed using Hill coefficients measured from diclofenac-mediated chemical inhibition assays within hepatic microsomes and purified human UGT2B7 and UGT2B15. Mixed-gender human intestinal microsomes showed little BPA glucuronidation reactivity compared with those from male rat intestine. Male rat intestinal microsomes in the presence of alamethicin exhibited a Vmax that was nearly 30-fold higher than that for mixed human microsomes. The species and gender metabolic differences we observed between rat and human liver and intestine provide key information for delineating BPA pharmacokinetics needed for human health risk assessment.

Variance of Microsomal Protein and Cytochrome P450 2E1 and 3A Forms in Adult Human Liver.

Differences in the pharmacokinetics of xenobiotics among humans makes them differentially susceptible to risk. Differences in enzyme content can mediate pharmacokinetic differences. Microsomal protein is often isolated from liver to characterize enzyme content and activity, but no measures exist to extrapolate these data to the intact liver. Measures were developed from up to 60 samples of adult human liver to characterize the content of microsomal protein and cytochrome P450 (CYP) enzymes. Statistical evaluations are necessary to estimate values far from the mean value. Adult human liver contains 52.9 ± 1.476 mg microsomal protein per g; 2587 ± 1.84 pmoles CYP2E1 per g; and 5237 ± 2.214 pmols CYP3A per g (geometric mean ± geometric standard deviation). These values are useful for identifying and testing susceptibility as a function of enzyme content when used to extrapolate in vitro rates of chemical metabolism for input to physiologically based pharmacokinetic models which can then be exercised to quantify the effect of variance in enzyme expression on risk-relevant pharmacokinetic outcomes.