Can oral toxicity data for PFAS inform on toxicity via inhalation?

Per- and poly-fluoroalkyl substances (PFAS) are ubiquitous in the environment and are detected in wildlife and humans. With respect to human exposure, studies have shown that ingestion is the primary route of exposure; however, in certain settings, exposure via inhalation could also be a significant source of exposure. While many studies examined toxicity of PFAS via ingestion, limited information is available for PFAS toxicity via the inhalation route, translating into a lack of exposure guidelines. Consequently, this article examined whether route-to-route extrapolation to derive guidelines for inhalation exposure is appropriate for PFAS. Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) were used as exemplary PFAS given the abundance of toxicity data for these two compounds. Our evaluation determined that available toxicity and toxicokinetic data support route-to-route extrapolation for PFAS in order to derive inhalation-based standards. Results from this analysis suggest that an air concentration of 7.0 × 10⁻⁵ mg/m³ (or 0.07 μg/m³) would be an appropriate RfC for PFOA and PFOS assuming the 2016 EPA RfD of 0.00002 mg/kg-day, whereas use of the interim RfDs proposed in 2022 of 1.5 × 10⁻⁹ and 7.9 × 10⁻⁹ mg/kg would yield much lower RfCs of 5.25 × 10⁻⁹ and 2.77 × 10⁻⁸ mg/m³ (or 5.25 × 10⁻⁶ and 2.77 × 10⁻⁵ μg/m³) for PFOA and PFOS, respectively.     

Evaluating the Risk of Liver Cancer in Humans Exposed to Trichloroethylene Using Physiological Models

Trichloroethylene (TCE) is a widespread environmental pollutant. TCE is classified as a rodent carcinogen by the U.S. Environmental Protection Agency (EPA). Using the rodent cancer bioassay findings and estimates of metabolized dose, the EPA has estimated lifetime exposure cancer risks for humans that ingest TCE in drinking water or inhale TCE. In this study, a physiologically based pharmacokinetic (PB-PK) model for mice was used to simulate selected gavage and inhalation bioassays with TCE. Plausible dose-metrics thought to be linked with the mechanism of action for TCE carcinogenesis were selected. These dose-metrics, adjusted to reflect an average amount per day for a lifetime, were metabolism of TCE (AMET, mg/kg/day) and systemic concentration of TCA (AUCTCA, mg/L/day). These dose-metrics were then used in a linearized multistage model to estimate AMET and AUCTCA values that correspond to liver cancer risks of 1 in 1 million in mice. A human PB-PK model for TCE was then used to predict TCE concentrations in drinking water and air that would provide AMET and AUCTCA values equal to the predicted mice AMET and AUCTCA values that correspond to liver cancer risks of 1 in 1 million. For the dose-metrics, AMET and AUCTCA, the TCE concentrations in air were 10.0 and 0.1 ppb TCE (continuous exposure), respectively, and in water, 7 and 4 μg TCE/L, respectively.     

A Calibrated Human PBPK Model for Benzene Inhalation with Urinary Bladder and Bone Marrow Compartments

A physiologically‐based pharmacokinetic (PBPK) model of benzene inhalation based on a recent mouse model was adapted to include bone marrow (target organ) and urinary bladder compartments. Empirical data on human liver microsomal protein levels and linked CYP2E1 activities were incorporated into the model, and metabolite‐specific conversion rate parameters were estimated by fitting to human biomonitoring data and adjusting for background levels of urinary metabolites. Human studies of benzene levels in blood and breath, and phenol levels in urine were used to validate the rate of human conversion of benzene to benzene oxide, and urinary benzene metabolites from Chinese benzene worker populations provided model validation for rates of human conversion of benzene to muconic acid (MA) and phenylmercapturic acid (PMA), phenol (PH), catechol (CA), hydroquinone (HQ), and benzenetriol (BT). The calibrated human model reveals that while liver microsomal protein and CYP2E1 activities are lower on average in humans compared to mice, the mouse also shows far lower rates of benzene conversion to MA and PMA, and far higher conversion of benzene to BO/PH, and of BO/PH to CA, HQ, and BT. The model also differed substantially from existing human PBPK models with respect to several metabolic rate parameters of importance to interpreting benzene metabolism and health risks in human populations associated with bone marrow doses. The model provides a new methodological paradigm focused on integrating linked human liver metabolism data and calibration using biomonitoring data, thus allowing for model uncertainty analysis and more rigorous validation.     

Chloroform Exposure and the Health Risk Associated with Multiple Uses of Chlorinated Tap Water

Recently, showers have been suspected to be an important source of indoor exposure to volatile organic compounds (VOC). The chloroform dose to an individual from showering was determined based on exhaled breath analysis. The postexposure chloroform breath concentration ranged from 6.0-21 micrograms/m3, while all corresponding background breath concentrations were less than 0.86 micrograms/m3. The internal dose from showering (inhalation plus dermal) was comparable to estimates of the dose from daily water ingestion. The risk associated with a single, 10-min shower was estimated to be 1.22 x 10(-4), while the estimated risk from daily ingestion of tap water ranged from 0.130 x 10(-4) to 1.80 x 10(-4) for 0.15 and 2.0 L, respectively. Since the estimates of chloroform risk from domestic water use for the three exposure routes--ingestion, inhalation, and dermal--are similar, all routes must be used to calculate the total risk when making policy decisions regarding the quality of the municipal water supply.     

The Impact of Cytochrome P450 2E1-Dependent Metabolic Variance on a Risk-Relevant Pharmacokinetic Outcome in Humans

Risk assessments include assumptions about sensitive subpopulations, such as the fraction of the general population that is sensitive and the extent that biochemical or physiological attributes influence sensitivity. Uncertainty factors (UF) account for both pharmacokinetic (PK) and pharmacodynamic (PD) components, allowing the inclusion of risk-relevant information to replace default assumptions about PK and PD variance (uncertainty). Large numbers of human organ donor samples and recent advances in methods to extrapolate in vitro enzyme expression and activity data to the intact human enable the investigation of the impact of PK variability on human susceptibility. The hepatotoxicity of trichloroethylene (TCE) is mediated by acid metabolites formed by cytochrome P450 2E1 (CYP2E1) oxidation, and differences in the CYP2E1 expression are hypothesized to affect susceptibility to TCE's liver injury. This study was designed specifically to examine the contribution of statistically quantified variance in enzyme content and activity on the risk of hepatotoxic injury among adult humans. We combined data sets describing (1) the microsomal protein content of human liver, (2) the CYP2E1 content of human liver microsomal protein, and (3) the in vitro Vmax for TCE oxidation by humans. The 5th and 95th percentiles of the resulting distribution (TCE oxidized per minute per gram liver) differed by approximately sixfold. These values were converted to mg TCE oxidized/h/kg body mass and incorporated in a human PBPK model. Simulations of 8-hour inhalation exposure to 50 ppm and oral exposure to 5 micro g TCE/L in 2 L drinking water showed that the amount of TCE oxidized in the liver differs by 2% or less under extreme values of CYP2E1 expression and activity (here, selected as the 5th and 95th percentiles of the resulting distribution). This indicates that differences in enzyme expression and TCE oxidation among the central 90% of the adult human population account for approximately 2% of the difference in production of the risk-relevant PK outcome for TCE-mediated liver injury. Integration of in vitro metabolism information into physiological models may reduce the uncertainties associated with risk contributions of differences in enzyme expression and the UF that represent PK variability.     

An Approach for Modeling Noncancer Dose Responses with an Emphasis on Uncertainty

This paper presents an approach for characterizing the probability of adverse effects occurring in a population exposed to dose rates in excess of the Reference Dose (RfD). The approach uses a linear threshold (hockey stick) model of response and is based on the current system of uncertainty factors used in setting RfDs. The approach requires generally available toxicological estimates such as No-Observed-Adverse-Effect Levels (NOAELs) or Benchmark Doses and doses at which adverse effects are observed in 50% of the test animals (ED₅₀s). In this approach, Monte Carlo analysis is used to characterize the uncertainty in the dose response slope based on the range and magnitude of the key sources of uncertainty in setting protective doses. The method does not require information on the shape of the dose response curve for specific chemicals, but is amenable to the inclusion of such data. The approach is applied to four compounds to produce estimates of response rates for dose rates greater than the RfD     

Cell Proliferation and Formaldehyde-Induced Respiratory Carcinogenesis

Formaldehyde is a nasal carcinogen in the rat but the cancer risk this chemical poses for humans remains to be determined. Formaldehyde induces nonlinear, concentration-dependent increases in nasal epithelial cell proliferation and DNA-protein cross-link formation following short-term exposure. Presented in this review are results from a mechanistically based formaldehyde inhalation study in which an important endpoint was the measurement of cell proliferation indices in target sites for nasal tumor induction. Male Fischer 344 rats were exposed to 0, 0.7, 2, 6, 10, or 15 ppm formaldehyde for up to 2 years (6 hr/day, 5 day/week). Statistically significant increases in cell proliferation were confined to the 10 and 15 ppm groups, which remained elevated throughout the study. The concentration-dependent increases in cell proliferation correlated strongly with the tumor response curve, supporting the proposal that sustained increases in cell proliferation are an important component of formaldehyde carcinogenesis. The nonlinearity observed in formaldehyde-induced rodent nasal cancer is consistent with a high-concentration effect of regenerative cell proliferation of the target organ coupled with the genotoxic effects of formaldehyde. Cell kinetic data from these studies provide important information that may be utilized in the assessment of risk for humans exposed to formaldehyde.     

Using Physiologically-Based Pharmacokinetic Modeling to Address Nonlinear Kinetics and Changes in Rodent Physiology and Metabolism Due to Aging and Adaptation in Deriving Reference Values for Propylene Glycol Methyl Ether and Propylene Glycol Methyl Ether Acetate

Reference values, including an oral reference dose (RfD) and an inhalation reference concentration (RfC), were derived for propylene glycol methyl ether (PGME), and an oral RfD was derived for its acetate (PGMEA). These values were based on transient sedation observed in F344 rats and B6C3F1 mice during a two‐year inhalation study. The dose‐response relationship for sedation was characterized using internal dose measures as predicted by a physiologically‐based pharmacokinetic (PBPK) model for PGME and its acetate. PBPK modeling was used to account for changes in rodent physiology and metabolism due to aging and adaptation, based on data collected during Weeks 1, 2, 26, 52, and 78 of a chronic inhalation study. The peak concentration of PGME in richly perfused tissues (i.e., brain) was selected as the most appropriate internal dose measure based on a consideration of the mode of action for sedation and similarities in tissue partitioning between brain and other richly perfused tissues. Internal doses (peak tissue concentrations of PGME) were designated as either no‐observed‐adverse‐effect levels (NOAELs) or lowest‐observed‐adverse‐effect levels (LOAELs) based on the presence or the absence of sedation at each time point, species, and sex in the two‐year study. Distributions of the NOAEL and LOAEL values expressed in terms of internal dose were characterized using an arithmetic mean and standard deviation, with the mean internal NOAEL serving as the basis for the reference values, which was then divided by appropriate uncertainty factors. Where data were permitting, chemical‐specific adjustment factors were derived to replace default uncertainty factor values of 10. Nonlinear kinetics, which was predicted by the model in all species at PGME concentrations exceeding 100 ppm, complicate interspecies, and low‐dose extrapolations. To address this complication, reference values were derived using two approaches that differ with respect to the order in which these extrapolations were performed: (1) default approach of interspecies extrapolation to determine the human equivalent concentration (PBPK modeling) followed by uncertainty factor application, and (2) uncertainty factor application followed by interspecies extrapolation (PBPK modeling). The resulting reference values for these two approaches are substantially different, with values from the latter approach being seven‐fold higher than those from the former approach. Such a striking difference between the two approaches reveals an underlying issue that has received little attention in the literature regarding the application of uncertainty factors and interspecies extrapolations to compounds where saturable kinetics occur in the range of the NOAEL. Until such discussions have taken place, reference values based on the former approach are recommended for risk assessments involving human exposures to PGME and PGMEA.     

A Trichloroethylene Risk Assessment Using a Monte Carlo Analysis of Parameter Uncertainty in Conjunction with Physiologically-Based Pharmacokinetic Modeling

A Monte Carlo simulation is incorporated into a risk assessment for trichloroethylene (TCE) using physiologically-based pharmacokinetic (PBPK) modeling coupled with the linearized multistage model to derive human carcinogenic risk extrapolations. The Monte Carlo technique incorporates physiological parameter variability to produce a statistically derived range of risk estimates which quantifies specific uncertainties associated with PBPK risk assessment approaches. Both inhalation and ingestion exposure routes are addressed. Simulated exposure scenarios were consistent with those used by the Environmental Protection Agency (EPA) in their TCE risk assessment. Mean values of physiological parameters were gathered from the literature for both mice (carcinogenic bioassay subjects) and for humans. Realistic physiological value distributions were assumed using existing data on variability. Mouse cancer bioassay data were correlated to total TCE metabolized and area-under-the-curve (blood concentration) trichloroacetic acid (TCA) as determined by a mouse PBPK model. These internal dose metrics were used in a linearized multistage model analysis to determine dose metric values corresponding to 10^-6 lifetime excess cancer risk. Using a human PBPK model, these metabolized doses were then extrapolated to equivalent human exposures (inhalation and ingestion). The Monte Carlo iterations with varying mouse and human physiological parameters produced a range of human exposure concentrations producing a 10^-6 risk.     

A Probabilistic Framework for the Reference Dose (Probabilistic RfD)

Determining the probabilistic limits for the uncertainty factors used in the derivation of the Reference Dose (RfD) is an important step toward the goal of characterizing the risk of noncarcinogenic effects from exposure to environmental pollutants. If uncertainty factors are seen, individually, as "upper bounds" on the dose-scaling factor for sources of uncertainty, then determining comparable upper bounds for combinations of uncertainty factors can be accomplished by treating uncertainty factors as distributions, which can be combined by probabilistic techniques. This paper presents a conceptual approach to probabilistic uncertainty factors based on the definition and use of RfDs by the US. EPA. The approach does not attempt to distinguish one uncertainty factor from another based on empirical data or biological mechanisms but rather uses a simple displaced lognormal distribution as a generic representation of all uncertainty factors. Monte Carlo analyses show that the upper bounds for combinations of this distribution can vary by factors of two to four when compared to the fixed-value uncertainty factor approach. The probabilistic approach is demonstrated in the comparison of Hazard Quotients based on RfDs with differing number of uncertainty factors.     

A Compartmental Model for the Prediction of Breath Concentration and Absorbed Dose of Chloroform After Exposure While Showering

In order to predict the exhaled breath concentration of chloroform in individuals exposed to chloroform while showering, an existing physiologically based pharmacokinetic (PB-PK) model was modified to include a multicompartment, PB-PK model for the skin and a completely mixed shower exposure model. The PB-PK model of the skin included the stratum corneum as the principal resistance to absorption and a viable epidermis which is in dynamic equilibrium with the skin microcirculation. This model was calibrated with measured exhaled breath concentrations of chloroform in individuals exposed while showering with and without dermal absorption. The calibration effort indicated that the expected value of skin-blood partitioning coefficient would be 1.2 when the degree of transfer of chloroform from shower water into shower air was 61%. The stratum corneum permeability coefficient for chloroform was estimated to be within the range of 0.16-0.36 cm/hr and the expected value was 0.2 cm/hr. The estimated ratio of the dermally and inhaled absorbed doses ranged between 0.6 and 2.2 and the expected value was 0.75. These results indicate that for the purposes of risk assessment for dermal exposure to chloroform, a simple steady-state model can be used to predict the degree of dermal absorption and that a reasonable value of skin permeability coefficient for chloroform used in this model would be 0.2 cm/hr. Further research should be conducted to compare the elimination of chloroform via exhaled breath when different exposure routes are being compared. The model results from this study suggest that multiple measurements of exhaled breath concentrations after exposure may be necessary when making comparisons of breath concentrations that involve different exposure routes.     

Uncertainties in Pharmacokinetic Modeling for Perchloroethylene. I. Comparison of Model Structure, Parameters, and Predictions for Low-Dose Metabolism Rates for Models Derived by Different Authors

In recent years physiologically based pharmacokinetic models have come to play an increasingly important role in risk assessment for carcinogens. The hope is that they can help open the black box between external exposure and carcinogenic effects to experimental observations, and improve both high-dose to low-dose and interspecies projections of risk. However, to date, there have been only relatively preliminary efforts to assess the uncertainties in current modeling results. In this paper we compare the physiologically based pharmacokinetic models (and model predictions of risk-related overall metabolism) that have been produced by seven different sets of authors for perchloroethylene (tetrachloroethylene). The most striking conclusion from the data is that most of the differences in risk-related model predictions are attributable to the choice of the data sets used for calibrating the metabolic parameters. Second, it is clear that the bottom-line differences among the model predictions are appreciable. Overall, the ratios of low-dose human to bioassay rodent metabolism spanned a 30-fold range for the six available human/rat comparisons, and the seven predicted ratios of low-dose human to bioassay mouse metabolism spanned a 13-fold range. (The greater range for the rat/human comparison is attributable to a structural assumption by one author group of competing linear and saturable pathways, and their conclusion that the dangerous saturable pathway constitutes a minor fraction of metabolism in rats.) It is clear that there are a number of opportunities for modelers to make different choices of model structure, interpretive assumptions, and calibrating data in the process of constructing pharmacokinetic models for use in estimating "delivered" or "biologically effective" dose for carcinogenesis risk assessments. We believe that in presenting the results of such modeling studies, it is important for researchers to explore the results of alternative, reasonably likely approaches for interpreting the available data--and either show that any conclusions they make are relatively insensitive to particular interpretive choices, or to acknowledge the differences in conclusions that would result from plausible alternative views of the world.     

Terrorist Population Dynamics Model

A system that includes a number of terrorist cells is considered. The cells can consist of one or more terrorists. The current number of terrorist cells is further denoted by N(t), where t is a current time counted from any appropriate origin. The objective is to find the evolution of the system in terms of N(t) and some interpretable parameters, such as the initial number of the terrorist cells N0=N(0), the cell disabling rate constant lambda (or the cell half-life t1/2), and the rate of formation of new cells P. The cost-effectiveness analysis, performed in the framework of the model, reveals that the effectiveness of disabling a terrorist cell is getting worse after 2-3 half-lives of a cell, which shows that if the anti-terrorist actions have not reached their goal during that time, the respective policy should be considered for revision, using the risk assessment consideration. Another important issue raised concerns balancing the efforts related to counterterrorism actions inside the system and the efforts protecting its borders. The respective data analysis is suggested and illustrated using simulated data.     

Quantitative Cancer Risk Estimation for Formaldehyde

Of primary concern are irreversible effects, such as cancer induction, that formaldehyde exposure could have on human health. Dose-response data from human exposure situations would provide the most solid foundation for risk assessment, avoiding problematic extrapolations from the health effects seen in nonhuman species. However, epidemiologic studies of human formaldehyde exposure have provided little definitive information regarding dose-response. Reliance must consequently be placed on laboratory animal evidence. An impressive array of data points to significantly nonlinear relationships between rodent tumor incidence and administered dose, and between target tissue dose and administered dose (the latter for both rodents and Rhesus monkeys) following exposure to formaldehyde by inhalation. Disproportionately less formaldehyde binds covalently to the DNA of nasal respiratory epithelium at low than at high airborne concentrations. Use of this internal measure of delivered dose in analyses of rodent bioassay nasal tumor response yields multistage model estimates of low-dose risk, both point and upper bound, that are lower than equivalent estimates based upon airborne formaldehyde concentration. In addition, risk estimates obtained for Rhesus monkeys appear at least 10-fold lower than corresponding estimates for identically exposed Fischer-344 rats.     

Routes of Chloroform Exposure and Body Burden from Showering with Chlorinated Tap Water

While there is an awareness of the need to quantify inhalation exposure from showers, the potential for dermal exposure to organic contaminants in showers has not been appreciated or explored. To establish routes of environmental exposure from showers, comparisons of the concentration of chloroform in exhaled breath after a normal shower with municipal tap water were made with those after an inhalation-only exposure. The postexposure chloroform breath concentrations ranged from 6.0-21 micrograms/m3 for normal showers and 2.4 to 10 micrograms/m3 for inhalation-only exposure, while the pre-exposure concentrations were all less than the minimum detection limit of 0.86 micrograms/m3. According to an F-test, the difference between the normal shower and the inhalation-only exposures was considered significant at a probability of p = 0.0001. Based on the difference, the mean internal dose due to dermal exposure was found to be approximately equal to that due to the inhalation exposure. The effect of the showering activities on the concentration of chloroform shower air was examined by comparing air concentrations during a normal shower with the air concentrations obtained when the shower was unoccupied. The F-test showed that there is no significant difference between the two sets of data.     

A Distributed Parameter Physiologically-Based Pharmacokinetic Model for Dermal and Inhalation Exposure to Volatile Organic Compounds

Estimates of dermal dose from exposures to toxic chemicals are typically derived using models that assume instantaneous establishment of steady-state dermal mass flux. However, dermal absorption theory indicates that this assumption is invalid for short-term exposures to volatile organic chemicals (VOCs). A generalized distributed parameter physiologically-based pharmacokinetic model (DP-PBPK), which describes unsteady state dermal mass flux via a partial differential equation (Fickian diffusion), has been developed for inhalation and dermal absorption of VOCs. In the present study, the DP-PBPK model has been parameterized for chloroform, and compared with two simpler PBPK models of chloroform. The latter are lumped parameter models, employing ordinary differential equations, that do not account for the dermal absorption time lag associated with the accumulation of permeant chemical in tissue represented by permeability coefficients. All three models were evaluated by comparing simulated post-exposure exhaled breath concentration profiles with measured concentrations following environmental chloroform exposures. The DP-PBPK model predicted a time-lag in the exhaled breath concentration profile, consistent with the experimental data. The DP-PBPK model also predicted significant volatilization of chloroform, for a simulated dermal exposure scenario. The end-exposure dermal dose predicted by the DP-PBPK model is similar to that predicted by the EPA recommended method for short-term exposures, and is significantly greater than the end-exposure dose predicted by the lumped parameter models. However, the net dermal dose predicted by the DP-PBPK model is substantially less than that predicted by the EPA method, due to the post-exposure volatilization predicted by the DP-PBPK model. Moreover, the net dermal dose of chloroform predicted by all three models was nearly the same, even though the lumped parameter models did not predict substantial volatilization.     

Physiologically-Based Pharmacokinetic Modeling of Benzene in Humans: A Bayesian Approach

Benzene is myelotoxic and leukemogenic in humans exposed at high doses (>1 ppm, more definitely above 10 ppm) for extended periods. However, leukemia risks at lower exposures are uncertain. Benzene occurs widely in the work environment and also indoor air, but mostly below 1 ppm, so assessing the leukemia risks at these low concentrations is important. Here, we describe a human physiologically-based pharmacokinetic (PBPK) model that quantifies tissue doses of benzene and its key metabolites, benzene oxide, phenol, and hydroquinone after inhalation and oral exposures. The model was integrated into a statistical framework that acknowledges sources of variation due to inherent intra- and interindividual variation, measurement error, and other data collection issues. A primary contribution of this work is the estimation of population distributions of key PBPK model parameters. We hypothesized that observed interindividual variability in the dosimetry of benzene and its metabolites resulted primarily from known or estimated variability in key metabolic parameters and that a statistical PBPK model that explicitly included variability in only those metabolic parameters would sufficiently describe the observed variability. We then identified parameter distributions for the PBPK model to characterize observed variability through the use of Markov chain Monte Carlo analysis applied to two data sets. The identified parameter distributions described most of the observed variability, but variability in physiological parameters such as organ weights may also be helpful to faithfully predict the observed human-population variability in benzene dosimetry.     

Methyl tert Butyl Ether Systemic Toxicity

In male F344 rats exposed in a chronic inhalation study to methyl tertiary butyl ether (MTBE) a treatment related increase in severity of chronic nephropathy and mortality and an increase in hyaline droplets in the kidney were noted. Liver weights were increased in both rats and mice but no histological lesions other than hypertrophy are seen. Transient CNS effects but no indications of permanent nervous system effects were noted. MTBE is not a reproductive or developmental hazard. MTBE is rapidly absorbed. MTBE with some metabolite, tertiary butyl alcohol (TBA) and a little CO₂, are excreted in the air. The urinary excretion products in animals are TBA metabolites, while in humans the urinary excretion products are MTBE and TBA. A comparison of the systemic responses of the possible metabolites TBA and formaldehyde indicate that they are not responsible for toxicity associated with MTBE, except that TBA may be partially responsible for the kidney effects reported. Animals and humans are similar in the uptake and excretion though with some differences in metabolism of MTBE. This supports the use of the animal data as a surrogate for humans.     

A Quality Risk Management Model Approach for Cell Therapy Manufacturing

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell‐based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator‐introduced variations, and affected by heterogeneity of the processed organs/tissues and lot‐dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell‐based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo‐quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.