Benchmark dose-response analyses for multiple endpoints in drug safety evaluation.

Hazard characterization during pharmaceutical development identifies the candidate drug's potential hazards and dose-response relationships. To date, the no-observed-adverse-effect-level (NOAEL) approach has been employed to identify the highest dose which results in no observed adverse effects. The benchmark dose (BMD) modeling approach describes potential dose-response relationships and has been used in diverse regulatory domains, but its applicability for pharmaceutical development has not previously been examined. Thus, we applied BMD-modeling to all endpoints in three sequential in vivo studies in a drug development setting, including biochemistry, hematology, organ pathology and clinical observations. In order to compare the results across such a broad range of effects, we needed to standardize the choice of the critical effect size (CES) for the different endpoints. A CES of 5%, previously suggested by the European Food Safety Authority, was compared with the study NOAEL and with the General Theory of Effect Size, which takes natural variability into account. Compared to the NOAEL approach, the BMD-modeling approach resulted in more informative estimates of the doses leading to effects. The BMD-modeling approach handled well situations where effects occurred below the lowest tested dose and the study's NOAEL, and seems advantageous to characterize the potential toxicity during safety assessment. The results imply a considerable step forward from the perspective of reducing and refining animal experiments, as more information is yielded from the same number of animals and at lower doses. Taken together, employing BMD-modeling as a substitute, or as a complement, to the NOAEL approach seems appropriate.

A Probabilistic Approach to Evaluate the Risk of Decreased Total Triiodothyronine Hormone Levels following Chronic Exposure to PFOS and PFHxS via Contaminated Drinking Water.

BACKGROUND: Extensive exposure to per- and polyfluoroalkyl substances (PFAS) have been observed in many countries. Current deterministic frameworks for risk assessment lack the ability to predict the likelihood of effects and to assess uncertainty. When exposure exceeds tolerable intake levels, these shortcomings hamper risk management and communication. OBJECTIVE: The integrated probabilistic risk assessment (IPRA) combines dose-response and exposure data to estimate the likelihood of adverse effects. We evaluated the usefulness of the IPRA for risk characterization related to decreased levels of total triiodothyronine (T3) in humans following a real case of high exposure to PFAS via drinking water. METHODS: PFAS exposure was defined as serum levels from residents of a contaminated area in Ronneby, Sweden. Median levels were 270 ng/mL [perfluorooctane sulfonic acid (PFOS)] and 229 ng/mL [perfluorohexane sulfonic acid (PFHxS)] for individuals who resided in Ronneby 1 y before the exposure termination. This data was integrated with data from a subchronic toxicity study in monkeys exposed daily to PFOS. Benchmark dose modeling was employed to describe separate dose-effect relationship for males and females, and extrapolation factor distributions were used to estimate the corresponding human benchmark dose. The critical effect level was defined as a 10% decrease in total T3. RESULTS: The median probability of critical exposure, following a combined exposure to PFOS and PFHxS, was estimated to be [2.1% (90% CI: 0.4%-13.1%)]. Gender-based analysis showed that this risk was almost entirely distributed among women, namely [3.9% (90% CI: 0.8%-21.6%)]. DISCUSSION: The IPRA was compared with the traditional deterministic Margin of Exposure (MoE) approach. We conclude that probabilistic risk characterization represents an important step forward in the ability to adequately analyze group-specific health risks. Moreover, quantifying the sources of uncertainty is desirable, as it improves the awareness among stakeholders and will guide future efforts to improve accuracy. https://doi.org/10.1289/EHP6654.

Influence of Distribution of Animals between Dose Groups on Estimated Benchmark Dose and Animal Welfare for Continuous Effects.

The benchmark dose (BMD) approach is increasingly used as a preferred approach for dose-effect analysis, but standard experimental designs are generally not optimized for BMD analysis. The aim of this study was to evaluate how the use of unequally sized dose groups affects the quality of BMD estimates in toxicity testing, with special consideration of the total burden of animal distress. We generated continuous dose-effect data by Monte Carlo simulation using two dose-effect curves based on endpoints with different shape parameters. Eighty-five designs, each with four dose groups of unequal size, were examined in scenarios ranging from low- to high-dose placements and with a total number of animals set to 40, 80, or 200. For each simulation, a BMD value was estimated and compared with the "true" BMD. In general, redistribution of animals from higher to lower dose groups resulted in an improved precision of the calculated BMD value as long as dose placements were high enough to detect a significant trend in the dose-effect data with sufficient power. The improved BMD precision and the associated reduction of the number of animals exposed to the highest dose, where chemically induced distress is most likely to occur, are favorable for the reduction and refinement principles. The result thereby strengthen BMD-aligned design of experiments as a means for more accurate hazard characterization along with animal welfare improvements.

Influence of Distribution of Animals between Dose Groups on Estimated Benchmark Dose and Animal Distress for Quantal Responses.

Increasingly, dose-response data are being evaluated with the benchmark dose (BMD) approach rather than by the less precise no-observed-adverse-effect-level (NOAEL) approach. However, the basis for designing animal experiments, using equally sized dose groups, is still primed for the NOAEL approach. The major objective here was to assess the impact of using dose groups of unequal size on both the quality of the BMD and overall animal distress. We examined study designs with a total number of 200 animals distributed in four dose groups employing quantal data generated by Monte Carlo simulations. Placing more animals at doses close to the targeted BMD provided an estimate of BMD that was slightly better than the standard design with equally sized dose groups. In situations involving a clear dose-response, this translates into fewer animals receiving high doses and thus less overall animal distress. Accordingly, in connection with risk and safety assessment, animal distress can potentially be reduced by distributing the animals appropriately between dose groups without decreasing the quality of the information obtained.

Assigning ethical weights to clinical signs observed during toxicity testing.

Reducing the number of laboratory animals used and refining experimental procedures to enhance animal welfare are fundamental questions to be considered in connection with animal experimentation. Here, we explored the use of cardinal ethical weights for clinical signs and symptoms in rodents by conducting trade-off interviews with members of Swedish Animal Ethics Committees in order to derive such weights for nine typical clinical signs of toxicity. The participants interviewed represent researchers, politically nominated political nominees and representatives of animal welfare organizations. We observed no statistically significant differences between these groups with respect to the magnitude of the ethical weights assigned, though the political nominees tended to assign lower weights. Overall, hunched posture was considered the most severe clinical sign and body weight loss the least severe. The ethical weights assigned varied considerably between individuals, from zero to infinite value, indicating discrepancies in prioritization of reduction and refinement. Cardinal ethical weights may be utilized to include both animal welfare refinement and reduction of animal use in designing as well as in retrospective assessment of animal experiments. Such weights may also be used to estimate ethical costs of animal experiments.

Inhibitory effects on osteoblast differentiation in vitro by the polychlorinated biphenyl mixture Aroclor 1254 are mainly associated with the dioxin-like constituents.

The polychlorinated biphenyl (PCB) mixture Aroclor 1254 alters bone tissue properties. However, the mechanisms responsible for the observed effects have not yet been clarified. This study compared the effect of Aroclor 1254 on the expression of osteoblast differentiation markers in MC3T3-E1 cells with the corresponding effect of the dioxin reference compound 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), and two PCB congeners belonging to the category of non-dioxin-like PCBs. The aim of the study was to quantify the relative influence of dioxin-like and non-dioxin-like PCB-components on osteoblast differentiation. Expression of marker genes for AhR activity and osteoblast differentiation were analyzed, and relative potency (REP) values were derived from Benchmark concentration-effect curves. Expression of alkaline phosphatase and osteocalcin were decreased by both Aroclor 1254 and TCDD exposure, while the PCB-congeners PCB19 and PCB52 slightly induced the expression. The relative potency of Aroclor 1254 for inhibitory effects on osteoblast differentiation marker genes was within the expected range as estimated from the chemical composition of Aroclor 1254. These results are consistent with previously observed bone modulations following in vivo exposure to Aroclor 1254 and TCDD, and demonstrate that the inhibitory effects of Aroclor 1254 on osteoblast differentiation by the dioxin-like constituents are over-riding the contribution of non-dioxin-like PCBs.

Current modeling practice may lead to falsely high benchmark dose estimates.

Benchmark dose (BMD) modeling is increasingly used as the preferred approach to define the point-of-departure for health risk assessment of chemicals. As data are inherently variable, there is always a risk to select a model that defines a lower confidence bound of the BMD (BMDL) that, contrary to expected, exceeds the true BMD. The aim of this study was to investigate how often and under what circumstances such anomalies occur under current modeling practice. Continuous data were generated from a realistic dose-effect curve by Monte Carlo simulations using four dose groups and a set of five different dose placement scenarios, group sizes between 5 and 50 animals and coefficients of variations of 5-15%. The BMD calculations were conducted using nested exponential models, as most BMD software use nested approaches. "Non-protective" BMDLs (higher than true BMD) were frequently observed, in some scenarios reaching 80%. The phenomenon was mainly related to the selection of the non-sigmoidal exponential model (Effect=a·e(b)(·dose)). In conclusion, non-sigmoid models should be used with caution as it may underestimate the risk, illustrating that awareness of the model selection process and sound identification of the point-of-departure is vital for health risk assessment.

The point of transition on the dose-effect curve as a reference point in the evaluation of in vitro toxicity data.

Dose-effect evaluation is an increasingly important step of health risk assessment. The foreseen increase of in vitro methods argues for the development and evaluation of a clearly defined reference points for dose-effect modelling of in vitro data. In the present study, the traditional use of a concentration corresponding to 10% or 50% of the maximal effect (EC10 or EC50) is compared with a strategy, under which, a reference point (Benchmark dose, BMD(T) ) is calculated that represents the dose where the slope of the dose-effect curve changes the most (per unit log-dose) in the low dose region. To illustrate the importance of the reference point, dose-effect data on CYP1A1 enzyme activity for 30 polychlorinated biphenyl (PCB) congeners were evaluated in order to calculate relative potencies, in relation to 2,3,7,8-TCDD, with confidence intervals (CIs). The present study shows that the interpretation of the results as potency and rank orders potentially depends on the choice and definition of the reference point (BMD(T) , EC10 or EC50). This is important as potency ranking may be used as a method for screening and prioritization, in research, in policy development or in pharmaceutical development. The use of the BMD(T) implies a focus on the change of structure in the parameter's dose-response rather than a particular percentage change in the response in such a parameter. In conclusion, the BMD(T) may be used as an alternative base for evaluation of dose-effect relationships in vitro. It offers an objective geometrical definition of a reference point in the low-dose region of the dose-effect curve.