Chemical Space Covered by Applicability Domains of Quantitative Structure-Property Relationships and Semiempirical Relationships in Chemical Assessments.

A significant number of chemicals registered in national and regional chemical inventories require assessments of their potential "hazard" concerns posed to humans and ecological receptors. This warrants knowledge of their partitioning and reactivity properties, which are often predicted by quantitative structure-property relationships (QSPRs) and other semiempirical relationships. It is imperative to evaluate the applicability domain (AD) of these tools to ensure their suitability for assessment purpose. Here, we investigate the extent to which the ADs of commonly used QSPRs and semiempirical relationships cover seven partitioning and reactivity properties of a chemical "space" comprising 81,000+ organic chemicals registered in regulatory and academic chemical inventories. Our findings show that around or more than half of the chemicals studied are covered by at least one of the commonly used QSPRs. The investigated QSPRs demonstrate adequate AD coverage for organochlorides and organobromines but limited AD coverage for chemicals containing fluorine and phosphorus. These QSPRs exhibit limited AD coverage for atmospheric reactivity, biodegradation, and octanol-air partitioning, particularly for ionizable organic chemicals compared to nonionizable ones, challenging assessments of environmental persistence, bioaccumulation capability, and long-range transport potential. We also find that a predictive tool's AD coverage of chemicals depends on how the AD is defined, for example, by the distance of a predicted chemical from the centroid of the training chemicals or by the presence or absence of structural features.

Quantitative Structure Use Relationships: Highlights from a technical summit meeting.

The Quantitative Structure Use Relationship (QSUR) Summit, held on November 2-4, 2022, focused on advancing the development, refinement, and use of QSURs to support chemical substance prioritization and risk assessment and mitigation. QSURs utilize chemical structures to predict the function of a chemical within a formulated product or an industrial process. This presumed function can then be used to develop chemical use categories or other information necessary to refine exposure assessments. The invited expert meeting was attended by 38 scientists from Canada, Finland, France, the UK, and the USA, representing government, business, and academia, with expertise in exposure science, chemical engineering, risk assessment, formulation chemistry, and machine learning. Workshop discussions emphasized the importance of collection and sharing of data and quantification of relative chemical quantities to progress QSUR development. Participants proposed collaborative approaches to address key challenges, including mechanisms for aggregating information while still protecting proprietary product composition and other confidential business information. Discussions also led to proposals for applications beyond exposure and risk modeling, including sustainable formulation discovery. In addition, discussions continue to construct, conduct, and circulate case studies tied to various specific problem formulations in which QSURs supply or derive information on chemical functions, concentrations, and exposures.

In Vivo Bioconcentration of 10 Anionic Surfactants in Rainbow Trout Explained by In Vitro Data on Partitioning and S9 Clearance.

Bioconcentration factors (BCFs) in rainbow trout were measured for 10 anionic surfactants with a range of alkyl chain lengths and different polar head groups. The BCFs ranged from 0.04 L kg-1 ww (for C10SO3) to 1370 L kg-1 ww (C16SO3). There was a strong correlation between the log BCF and log membrane lipid-water distribution ratio (DMLW, r2 = 0.96), and biotransformation was identified as the dominant elimination mechanism. The strong positive influence of DMLW on BCF was attributed to two phenomena: (i) increased partitioning from water into the epithelial membrane of the gill, leading to more rapid diffusion across this barrier and more rapid uptake, and (ii) increased sequestration of the surfactant body burden into membranes and other body tissues, resulting in lower freely dissolved concentrations available for biotransformation. Estimated whole-body in vivo biotransformation rate constants kB-BCF are within a factor three of rate constants estimated from S9 in vitro assays for six of the eight test chemicals for which kB-BCF could be determined. A model-based assessment indicated that the hepatic clearance rate of freely dissolved chemicals was similar for the studied surfactants. The dataset will be useful for evaluation of in silico and in vitro methods to assess bioaccumulation.

Bioconcentration of Several Series of Cationic Surfactants in Rainbow Trout.

Cationic surfactants have a strong affinity to sorb to phospholipid membranes and thus possess an inherent potential to bioaccumulate, but there are few measurements of bioconcentration in fish. We measured the bioconcentration of 10 alkylamines plus two quaternary ammonium compounds in juvenile rainbow trout at pH 7.6, and repeated the measurements at pH 6.2 for 6 of these surfactants. The BCF of the amines with chain lengths ≤ C14 was positively correlated with chain length, increasing ∼0.5 log units per carbon. Their BCF was also pH dependent and approximately proportional to the neutral fraction of the amine in the water. The BCFs of the quaternary ammonium compounds showed no pH dependence and were >2 orders of magnitude less than for amines of the same chain length at pH 7.6. This indicates that systemic uptake of permanently charged cationic surfactants is limited. The behavior of the quaternary ammonium compounds and the two C16 amines studied was consistent with previous observations that these surfactants accumulate primarily to the gills and external surfaces of the fish. At pH 7.6 the BCF exceeded 2000 L kg-1 for 4 amines with chains ≥ C13, showing that bioconcentration can be considerable for some longer chained cationic surfactants.

Clarifying Temporal Trend Variability in Human Biomonitoring of Polybrominated Diphenyl Ethers through Mechanistic Modeling.

Human biomonitoring data collected from individuals of the same age sampled in different years provide within-age temporal trends, which are often employed to evaluate the effectiveness of chemical regulatory policies. For polybrominated diphenyl ethers (PBDEs), this within-age temporal trend has been observed to vary between congeners and age groups. We systematically explore the mechanisms responsible for such variability through simulating human exposure via multiple exposure pathways to PBDEs released from multiple lifecycle stages. Our simulation indicates that, after new use of PBDEs is banned, emissions to the outdoor environment from use and waste disposal outlast those to the indoor environment from the indoor use phase, leading to slower decline rates in the contamination of food items sourced from the outdoor environment than that from indoors. Compared with indoor exposure pathways, the consumption of contaminated food contributes more to the exposure (i) to more hydrophobic, recalcitrant congeners, and (ii) of adults than children, which results in slower rates of decline in the within-age temporal trend of those congeners and in adults. The within-age temporal trend is influenced to a lesser extent by the elimination of PBDEs from the human body, e.g., differences in biotransformation potential of congeners, growth dilution, and pre- and postnatal exposures by children.

Tissue Distribution of Several Series of Cationic Surfactants in Rainbow Trout (Oncorhynchus mykiss) Following Exposure via Water.

Bioaccumulation assessment is important for cationic surfactants in light of their use in a wide variety of consumer products and industrial processes. Because they sorb strongly to natural surfaces and to cell membranes, their bioaccumulation behavior is expected to differ from other classes of chemicals. Divided over two mixtures, we exposed rainbow trout to water containing 10 alkyl amines and 2 quaternary alkylammonium surfactants for 7 days, analyzed different fish tissues for surfactant residues, and calculated the tissues' contribution to fish body burden. Mucus, skin, gills, liver, and muscle each contributed at least 10% of body burden for the majority of the test chemicals. This indicates that both sorption to external surfaces and systemic uptake contribute to bioaccumulation. In contrast to the analogue alkylamine bases, the permanently charged quaternary ammonium compounds accumulated mostly in the gills and were nearly absent in internal tissues, indicating that systemic uptake of the charged form of cationic surfactants is very slow. Muscle-blood distribution coefficients were close to 1 for all alkyl amines, whereas liver-blood distribution coefficients ranged from 13 to 90, suggesting that the dominant considerations for sorption in liver are different from those in blood and muscle. The significant fraction of body burden on external surfaces can have consequences for bioaccumulation assessment.

Examining Uncertainty in In Vitro-In Vivo Extrapolation Applied in Fish Bioconcentration Models.

In vitro biotransformation rates were determined for 30 chemicals, mostly fragrance ingredients, using trout liver S9 fractions (RT-S9) and incorporated into in vitro-in vivo extrapolation (IVIVE) models to predict bioconcentration factors (BCFs). Predicted BCFs were compared against empirical BCFs to explore potential major uncertainties involved in the in vitro methods and IVIVE models: (i) in vitro chemical test concentrations; (ii) different gill uptake rate constant calculations (k1); (iii) protein binding (different calculations and measurement of the fraction of unbound chemical, fU); (iv) species differences; and (v) extrahepatic biotransformation. Predicted BCFs were within 0.5 log units for 44% of the chemicals compared to empirical BCFs, whereas 56% were overpredicted by >0.5 log units. This trend of overprediction was reduced by alternative k1 calculations to 32% of chemicals being overpredicted. Moreover, hepatic in vitro rates scaled to whole body biotransformation rates (kB) were compared against in vivo kB estimates. In vivo kB was underestimated for 79% of the chemicals. Neither lowering the test concentration, nor incorporation of new measured fU values, nor species matching avoided the tendency to overpredict BCFs indicating that further improvements to the IVIVE models are needed or extrahepatic biotransformation plays an underestimated role.

How are Humans Exposed to Organic Chemicals Released to Indoor Air?

Humans are exposed to organic chemicals released to indoor air through near-field exposure routes such as air inhalation and nondietary dust ingestion as well as far-field exposure routes such as consumption of food. Here, we explore the relative importance of near- and far-field exposure routes and its variability between chemicals, age groups, and subpopulations, by modeling aggregate human exposure to indoor-released chemicals with diverse partitioning behavior and degradability. Our model results indicate that if chemicals are assumed to be perfectly persistent, dietary and nondietary ingestion dominates human exposure to hydrophobic chemicals of relatively low volatility (with an octanol-air partition coefficient KOA > 106.5 and an octanol-water partition coefficient KOW < 1011), whereas inhalation of indoor air dominates human exposure to volatile chemicals. Other exposure routes, for example, dermal absorption and drinking water, make a relatively small contribution to human exposure. Reduced chemical persistence in environmental media and biota lowers the contribution of dietary ingestion. For most chemicals other than those with a KOA between 109 and 1012 and a KOW between 106 and 109 (e.g., polybrominated diphenyl ethers), the relative importance of near- and far-field exposure routes is primarily governed by chemical partitioning and degradability rather than age- and population-dependent human exposure factors.

Development and Evaluation of a Combined Bioenergetics and Organic Chemical Mass-Balance Bioaccumulation Model for Fish.

This study describes the development and evaluation of a new bioenergetically balanced bioaccumulation (3B) model for organic chemicals in fish. The 3B model is developed from a large database of routine metabolic (oxygen consumption) rates composed of a range of species, body mass, and temperatures. The chemical uptake and elimination rates of the 3B model are compared against those from three existing bioaccumulation models. A time-variant version of the 3B model is evaluated against measured concentrations of five polychlorinated biphenyls in different-size fish depurated over the course of a year, during which water temperature changed by 22 °C. The "generic" species 3B model predicts fish concentrations to within a factor of 3 of the measured data for the majority of observations ( n = 438) and outperforms a previously published "species-specific" bioenergetics model. Bioenergetics aspects of the 3B model are further evaluated by comparing predicted feeding rates and growth rates to measured rates obtained from diverse laboratory conditions ( n 572). While bioenergetics performance is acceptable, the 3B model seems to generally perform better when ingestion rates are calculated from growth rates rather than vice versa. For field applications, parametrization of the activity multiplier remains a key uncertainty underlying the bioenergetics calculations.

Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways.

Prioritizing the potential risk posed to human health by chemicals requires tools that can estimate exposure from limited information. In this study, chemical structure and physicochemical properties were used to predict the probability that a chemical might be associated with any of four exposure pathways leading from sources-consumer (near-field), dietary, far-field industrial, and far-field pesticide-to the general population. The balanced accuracies of these source-based exposure pathway models range from 73 to 81%, with the error rate for identifying positive chemicals ranging from 17 to 36%. We then used exposure pathways to organize predictions from 13 different exposure models as well as other predictors of human intake rates. We created a consensus, meta-model using the Systematic Empirical Evaluation of Models framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. The consensus model yields an R2 of ∼0.8. We extrapolate to predict relevant pathway(s), median intake rate, and credible interval for 479 926 chemicals, mostly with minimal exposure information. This approach identifies 1880 chemicals for which the median population intake rates may exceed 0.1 mg/kg bodyweight/day, while there is 95% confidence that the median intake rate is below 1 µg/kg BW/day for 474572 compounds.

Revisiting the Contributions of Far- and Near-Field Routes to Aggregate Human Exposure to Polychlorinated Biphenyls (PCBs).

The general population is exposed to polychlorinated biphenyls (PCBs) by consuming food from far-field contaminated agricultural and aquatic environments, and inhalation and nondietary ingestion in near-field indoor or residential environments. Here, we seek to evaluate the relative importance of far- and near-field routes by simulating the time-variant aggregate exposure of Swedish females to PCB congeners from 1930 to 2030. We rely on a mechanistic model, which integrates a food-chain bioaccumulation module and a human toxicokinetic module with dynamic substance flow analysis and nested indoor-urban-rural environmental fate modeling. Confidence in the model is established by successfully reproducing the observed PCB concentrations in Swedish human milk between 1972 and 2016. In general, far-field routes contribute most to total PCB uptake. However, near-field exposure is notable for (i) children and teenagers, who have frequent hand-to-mouth contact, (ii) cohorts born in earlier years, e.g., in 1956, when indoor environments were severely contaminated, and (iii) lighter chlorinated congeners. The relative importance of far- and near-field exposure in a cross-section of individuals of different age sampled at the same time is shown to depend on the time of sampling. The transition from the dominance of near- to far-field exposure that has happened for PCBs may also occur for other chemicals used indoors.

A Model for Risk-Based Screening and Prioritization of Human Exposure to Chemicals from Near-Field Sources.

Exposure- and risk-based assessments for chemicals used indoors or applied to humans (i.e., in near-field environments) necessitate an aggregate exposure pathway framework that aligns chemical exposure information from use sources to internal dose and eventually to their potential for health effects. Such a source-to-effect continuum is advocated to balance the complexity of human exposure and the insufficiency of relevant data for thousands of existing and emerging chemicals. Here, we introduce the Risk Assessment, IDentification And Ranking-Indoor and Consumer Exposure (RAIDAR-ICE) model, which establishes an integrated framework to evaluate human exposure due to indoor use and direct application of chemicals to humans. As a model evaluation, RAIDAR-ICE faithfully reproduces exposure estimates inferred from biomonitoring data for 37 chemicals with direct and indirect near-field sources. RAIDAR-ICE generates different rankings for 131 chemicals based on different exposure- and risk-based assessment metrics, demonstrating its versatility for diverse chemical screening goals. When coupled with a far-field RAIDAR model, the near-field RAIDAR-ICE model enables assessment of aggregate human exposure. Overall, RAIDAR-ICE is a powerful tool for high-throughput screening and prioritization of human exposure to neutral organic chemicals used indoors.

Which Molecular Features Affect the Intrinsic Hepatic Clearance Rate of Ionizable Organic Chemicals in Fish?

Greater knowledge of biotransformation rates for ionizable organic compounds (IOCs) in fish is required to properly assess the bioaccumulation potential of many environmentally relevant contaminants. In this study, we measured in vitro hepatic clearance rates for 50 IOCs using a pooled batch of liver S9 fractions isolated from rainbow trout (Oncorhynchus mykiss). The IOCs included four types of strongly ionized acids (carboxylates, phenolates, sulfonates, and sulfates), three types of strongly ionized bases (primary, secondary, tertiary amines), and a pair of quaternary ammonium compounds (QACs). Included in this test set were several surfactants and a series of beta-blockers. For linear alkyl chain IOC analogues, biotransformation enzymes appeared to act directly on the charged terminal group, with the highest clearance rates for tertiary amines and sulfates and no clearance of QACs. Clearance rates for C12-IOCs were higher than those for C8-IOC analogues. Several analogue series with multiple alkyl chains, branched alkyl chains, aromatic rings, and nonaromatic rings were evaluated. The likelihood of multiple reaction pathways made it difficult to relate all differences in clearance to specific molecular features the tested IOCs. Future analysis of primary metabolites in the S9 assay is recommended to further elucidate biotransformation pathways for IOCs in fish.

Improving plant bioaccumulation science through consistent reporting of experimental data.

Experimental data and models for plant bioaccumulation of organic contaminants play a crucial role for assessing the potential human and ecological risks associated with chemical use. Plants are receptor organisms and direct or indirect vectors for chemical exposures to all other organisms. As new experimental data are generated they are used to improve our understanding of plant-chemical interactions that in turn allows for the development of better scientific knowledge and conceptual and predictive models. The interrelationship between experimental data and model development is an ongoing, never-ending process needed to advance our ability to provide reliable quality information that can be used in various contexts including regulatory risk assessment. However, relatively few standard experimental protocols for generating plant bioaccumulation data are currently available and because of inconsistent data collection and reporting requirements, the information generated is often less useful than it could be for direct applications in chemical assessments and for model development and refinement. We review existing testing guidelines, common data reporting practices, and provide recommendations for revising testing guidelines and reporting requirements to improve bioaccumulation knowledge and models. This analysis provides a list of experimental parameters that will help to develop high quality datasets and support modeling tools for assessing bioaccumulation of organic chemicals in plants and ultimately addressing uncertainty in ecological and human health risk assessments.

Development and evaluation of a database of dietary bioaccumulation test data for organic chemicals in fish.

Dietary bioaccumulation tests for fish have been conducted for about 40 years. Standardized test guidance has recently been developed. Test metrics of primary scientific and regulatory interest are the whole body depuration rate constant (kT), whole body growth corrected depuration rate constant (kTg), and corresponding chemical half-lives (t1/2 and t1/2g), dietary chemical absorption efficiency (AE), and biomagnification factor (BMF). A database of 3032 measurement end points for 477 discrete organic chemicals including 964 half-lives, 1199 AEs and 869 BMFs from 19 species (primarily trout and carp) was developed from the literature. Biological properties (e.g., organism weight, lipid content) and exposure conditions (e.g., temperature, feeding rate, dietary lipid content, exposure duration) are documented. Test chemicals range in molar mass from 120 to 1423 g·mol(-1) with log octanol-water partition coefficients (KOW) ranging from 0.8 to 14.3; 50% of the database entries are for polychlorinated biphenyls. The measured end points are derived from various protocols and sources of variability are described. The data are evaluated and categorized using proposed data quality (confidence) criteria derived from the standardized test protocol providing initial guidance for data users. Half-lives range from 0.13 to 2600 days; however, approximately 54% have an identifiable source of uncertainty. The data suggest that chemicals absorbed from the gastrointestinal tract with a log KOW ≥ ∼5 and at least as high as ∼9 have biomagnification potential in fish. A mechanistic bioaccumulation model is compared to the measured data and used to illustrate the influence of growth and biotransformation rates on the BMF.

Application of the Activity Framework for Assessing Aquatic Ecotoxicology Data for Organic Chemicals.

Toxicological research in the 1930s gave the first indications of the link between narcotic toxicity and the chemical activity of organic chemicals. More recently, chemical activity has been proposed as a novel exposure parameter that describes the fraction of saturation and that quantifies the potential for partitioning and diffusive uptake. In the present study, more than 2000 acute and chronic algal, aquatic invertebrates and fish toxicity data, as well as water solubility and melting point values, were collected from a series of sources. The data were critically reviewed and grouped by mode of action (MoA). We considered 660 toxicity data to be of acceptable quality. The 328 data which applied to the 72 substances identified as MoA 1 were then evaluated within the activity-toxicity framework: EC50 and LC50 values for all three taxa correlated generally well with (subcooled) liquid solubilities. Acute toxicity was typically exerted within the chemical activity range of 0.01-0.1, whereas chronic toxicity was exerted in the range of 0.001-0.01. These results confirm that chemical activity has the potential to contribute to the determination, interpretation and prediction of toxicity to aquatic organisms. It also has the potential to enhance regulation of organic chemicals by linking results from laboratory tests, monitoring and modeling programs. The framework can provide an additional line of evidence for assessing aquatic toxicity, for improving the design of toxicity tests, reducing animal usage and addressing chemical mixtures.

Risk-Based High-Throughput Chemical Screening and Prioritization using Exposure Models and in Vitro Bioactivity Assays.

We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify relevant use scenarios (e.g., dermal application, indoor emissions). For each chemical and use scenario, exposure models are then used to calculate a chemical intake fraction, or a product intake fraction, accounting for chemical properties and the exposed population. We then combine these intake fractions with use scenario-specific estimates of chemical quantity to calculate daily intake rates (iR; mg/kg/day). These intake rates are compared to oral equivalent doses (OED; mg/kg/day), calculated from a suite of ToxCast in vitro bioactivity assays using in vitro-to-in vivo extrapolation and reverse dosimetry. Bioactivity quotients (BQs) are calculated as iR/OED to obtain estimates of potential impact associated with each relevant use scenario. Of the 180 chemicals considered, 38 had maximum iRs exceeding minimum OEDs (i.e., BQs > 1). For most of these compounds, exposures are associated with direct intake, food/oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models.

Model for screening-level assessment of near-field human exposure to neutral organic chemicals released indoors.

Screening organic chemicals for hazard and risk to human health requires near-field human exposure models that can be readily parametrized with available data. The integration of a model of human exposure, uptake, and bioaccumulation into an indoor mass balance model provides a quantitative framework linking emissions in indoor environments with human intake rates (iRs), intake fractions (iFs) and steady-state concentrations in humans (C) through consideration of dermal permeation, inhalation, and nondietary ingestion exposure pathways. Parameterized based on representative indoor and adult human characteristics, the model is applied here to 40 chemicals of relevance in the context of human exposure assessment. Intake fractions and human concentrations (C(U)) calculated with the model based on a unit emission rate to air for these 40 chemicals span 2 and 5 orders of magnitude, respectively. Differences in priority ranking based on either iF or C(U) can be attributed to the absorption, biotransformation and elimination processes within the human body. The model is further applied to a large data set of hypothetical chemicals representative of many in-use chemicals to show how the dominant exposure pathways, iF and C(U) change as a function of chemical properties and to illustrate the capacity of the model for high-throughput screening. These simulations provide hypotheses for the combination of chemical properties that may result in high exposure and internal dose. The model is further exploited to highlight the role human contaminant uptake plays in the overall fate of certain chemicals indoors and consequently human exposure.

Application of mass balance models and the chemical activity concept to facilitate the use of in vitro toxicity data for risk assessment.

Practical, financial, and ethical considerations related to conducting extensive animal testing have resulted in various initiatives to promote and expand the use of in vitro testing data for chemical evaluations. Nominal concentrations in the aqueous phase corresponding to an effect (or biological activity) are commonly reported and used to characterize toxicity (or biological response). However, the true concentration in the aqueous phase can be substantially different from the nominal. To support in vitro test design and aid the interpretation of in vitro toxicity data, we developed a mass balance model that can be parametrized and applied to represent typical in vitro test systems. The model calculates the mass distribution, freely dissolved concentrations, and cell/tissue concentrations corresponding to the initial nominal concentration and experimental conditions specified by the user. Chemical activity, a metric which can be used to assess the potential for baseline toxicity to occur, is also calculated. The model is first applied to a set of hypothetical chemicals to illustrate the degree to which test conditions (e.g., presence or absence of serum) influence the distribution of the chemical in the test system. The model is then applied to set of 1194 real substances (predominantly from the ToxCast chemical database) to calculate the potential range of concentrations and chemical activities under assumed test conditions. The model demonstrates how both concentrations and chemical activities can vary by orders of magnitude for the same nominal concentration.

Estimating screening-level organic chemical half-lives in humans.

Relatively few measured data are available for the thousands of chemicals requiring hazard and risk assessment. The whole body, total elimination half-life (HLT) and the whole body, primary biotransformation half-life (HLB) are key parameters determining the extent of bioaccumulation, biological concentration, and risk from chemical exposure. A one-compartment pharmacokinetic (1-CoPK) mass balance model was developed to estimate organic chemical HLB from measured HLT data in mammals. Approximately 1900 HLs for human adults were collected and reviewed and the 1-CoPK model was parametrized for an adult human to calculate HLB from HLT. Measured renal clearance and whole body total clearance data for 306 chemicals were used to calculate empirical HLB,emp. The HLB,emp values and other measured data were used to corroborate the 1-CoPK HLB model calculations. HLs span approximately 7.5 orders of magnitude from 0.05 h for nitroglycerin to 2 × 10(6) h for 2,3,4,5,2',3',5',6'-octachlorobiphenyl with a median of 7.6 h. The automated Iterative Fragment Selection (IFS) method was applied to develop and evaluate various quantitative structure-activity relationships (QSARs) to predict HLT and HLB from chemical structure and two novel QSARs are detailed. The HLT and HLB QSARs show similar statistical performance; that is, r(2) = 0.89, r(2-ext) = 0.72 and 0.73 for training and external validation sets, respectively, and root-mean-square errors for the validation data sets are 0.70 and 0.75, respectively.