The Research Institute for Fragrance Materials’ human repeated insult patch test protocol

Skin Rejuvenation Efficacy and Safety Evaluation of Kaempferia parviflora Standardized Extract (BG100) in Human 3D Skin Models and Clinical Trial

Polymethoxyflavones from Kaempferia parviflora rhizomes have been shown to effectively combat aging in skin cells and tissues by inhibiting senescence, reducing oxidative stress, and enhancing skin structure and function. This study assessed the anti-aging effects and safety of standardized K. parviflora extract (BG100), enriched with polymethoxyflavones including 5,7-dimethoxyflavone, 5,7,4'-trimethoxyflavone, 3,5,7,3',4'-pentamethoxyflavone, 3,5,7-trimethoxyflavone, and 3,5,7,4'-tetramethoxyflavone. We evaluated BG100's impact on skin rejuvenation and antioxidant properties using photoaged human 3D full-thickness skin models. The potential for skin irritation and sensitization was also assessed through studies on reconstructed human epidermis and clinical trials. Additionally, in vitro genotoxicity testing was performed following OECD guidelines. Results indicate that BG100 promotes collagen and hyaluronic acid production, reduces oxidative stress, and minimizes DNA damage in photoaged full-thickness 3D skin models. Furthermore, it exhibited non-irritating and non-sensitizing properties, as supported by tests on reconstructed human epidermis and clinical settings. BG100 also passed in vitro genotoxicity tests, adhering to OECD guidelines. These results underscore BG100's potential as a highly effective and safe, natural anti-aging agent, suitable for inclusion in cosmeceutical and nutraceutical products aimed at promoting skin rejuvenation.

Use of human predictive patch test (HPPT) data for the classification of skin sensitization hazard and potency

Since the 1940s, patch tests in healthy volunteers (Human Predictive Patch Tests, HPPTs) have been used to identify chemicals that cause skin sensitization in humans. Recently, we reported the results of a major curation effort to support the development of OECD Guideline 497 on Defined Approaches (DAs) for skin sensitization (OECD in Guideline No. 497: Defined Approaches on Skin Sensitisation, 2021a. https://doi.org/10.1787/b92879a4-en ). In the course of this work, we compiled and published a database of 2277 HPPT results for 1366 unique test substances (Strickland et al. in Arch Toxicol 97:2825-2837, 2023. https://doi.org/10.1007/s00204-023-03530-3 ). Here we report a detailed analysis of the value of HPPT data for classification of chemicals as skin sensitizers under the United Nations' Globally Harmonized System of Classification and Labelling of Chemicals (GHS). As a result, we propose the dose per skin area (DSA) used for classification by the GHS to be replaced by or complemented with a dose descriptor that may better reflect sensitization incidence [e.g., the DSA causing induction of sensitization in one individual (DSA1+) or the DSA leading to an incidence of induction in 5% of the tested individuals (DSA05)]. We also propose standardized concepts and workflows for assessing individual HPPT results, for integrating multiple HPPT results and for using them in concert with Local Lymph Node Assay (LLNA) data in a weight of evidence (WoE) assessment. Overall, our findings show that HPPT results are often not sufficient for deriving unambiguous classifications on their own. However, where they are, the resulting classifications are reliable and reproducible and can be integrated well with those from other skin sensitization data, such as the LLNA.

Use of guinea pig data to obtain starting points for skin sensitisation risk assessment - A commentary

The increasing drive to understand the likelihood of skin sensitisation from plant protection products (PPPs) in workers and the general public has resulted in recent initiatives to establish a quantitative risk assessment (QRA) methodology applicable to these products and their exposure scenarios. The effective evaluation of skin sensitising substances requires not only the identification of that toxicological hazard, but also determination of relative sensitising potency. Typically, this has been achieved by interpretation of local lymph node assay (LLNA) dose response data, delivering what is known as the EC3 value. This permitted regulatory division of skin sensitisers into defined potency sub-categories, but more importantly enabled derivation of a no expected sensitisation induction level (NESIL) as the point of departure for QRA. However, for many existing substances there is no LLNA data, only older guinea pig results exist. To avoid additional (in vivo) testing, an approach has been outlined to employ guinea pig data and existing regulatory guidelines on the determination of potency sub-categorisation to provide a guinea pig based NESIL. The approach adopts a conservative extrapolation from LLNA NESIL benchmarks to deliver points of departure as the basis for the type of QRA process already in successful use by other industries.

A database of human predictive patch test data for skin sensitization

Critical to the evaluation of non-animal tests are reference data with which to assess their relevance. Animal data are typically used because they are generally standardized and available. However, when regulatory agencies aim to protect human health, human reference data provide the benefit of not having to account for possible interspecies variability. To support the evaluation of non-animal approaches for skin sensitization assessment, we collected data from 2277 human predictive patch tests (HPPTs), i.e., human repeat insult patch tests and human maximization tests, for skin sensitization from 1555 publications. We recorded protocol elements and positive or negative outcomes, developed a scoring system to evaluate each test for reliability, and calculated traditional and non-traditional dose metrics. We also traced each test result back to its original report to remove duplicates. The resulting database, which contains information for 1366 unique substances, was characterized for physicochemical properties, chemical structure categories, and protein binding mechanisms. This database is publicly available on the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods website and in the Integrated Chemical Environment to serve as a resource for additional evaluation of alternative methods and development of new approach methodologies for skin sensitization assessments.

Assessing the risk of induction of skin sensitization to plant protection products: A quantitative approach

Exposure to skin sensitizers is common and regulated in many industry sectors. For cosmetics, a risk-based approach has been implemented, focused on preventing the induction of sensitization. First, a No Expected Sensitization Induction Level (NESIL) is derived, then modified by Sensitization Assessment Factors (SAFs) to derive an Acceptable Exposure Level (AEL). The AEL is used in risk assessment, being compared with an estimated exposure dose, specific to the exposure scenario. Since in Europe there is increased concern regarding exposure towards potentially sensitizing pesticides via spray drift, we explore how existing practice can be modified to allow Quantitative Risk Assessment (QRA) of pesticides for bystanders and residents. NESIL derivation by the Local Lymph Node Assay (LLNA), the globally required in vivo assay for this endpoint, is reviewed alongside consideration of appropriate SAFs. Using a case study, the principle that the NESIL in μg/cm² can be derived by multiplying LLNA EC3% figure by a factor of 250 is adopted. The NESIL is then reduced by an overall SAF of 25 to establish an exposure level below which there is minimal bystander and resident risk. Whilst this paper focuses on European risk assessment and management, the approach is generic and universally applicable.

Reference Chemical Potency List (RCPL): A new tool for evaluating the accuracy of skin sensitisation potency measurements by New Approach Methodologies (NAMs)

Considerable progress has been made in the design of New Approach Methodologies (NAMs) for the hazard identification of skin sensitising chemicals. However, effective risk assessment requires accurate measurement of sensitising potency, and this has proven more difficult to achieve without recourse to animal tests. One important requirement for the development and adoption of novel approaches for this purpose is the availability of reliable databases for determining the accuracy with which sensitising potency can be predicted. Some previous approaches have relied on comparisons with potency estimates based on either human or animal (local lymph node assay) data. In contrast, we here describe the development of a carefully curated Reference Chemical Potency List (RCPL) which is based on consideration of the best available human and animal data. The RCPL is comprised of 33 readily available chemicals that span a wide range of chemistry and sensitising potency, and contain examples of both direct and indirect (pre- and pro-) haptens. For each chemical a potency value (PV) was derived, and chemicals ranked according to PV without the use of potency categories. It is proposed that the RCPL provides an effective resource for assessment of the accuracy with which NAMs can measure skin sensitising potency.

Decision making in next generation risk assessment for skin allergy: Using historical clinical experience to benchmark risk

Our aim is to develop and apply next generation approaches to skin allergy risk assessment that do not require new animal test data and better quantify uncertainties. Quantitative risk assessment for skin sensitisation uses safety assessment factors to extrapolate from the point-of-departure to an acceptable human exposure level. It is currently unclear whether these safety assessment factors are appropriate when using non-animal test data to derive a point-of departure. Our skin allergy risk assessment model Defined Approach uses Bayesian statistics to infer a human-relevant metric of sensitiser potency with explicit quantification of uncertainty, using any combination of human repeat insult patch test, local lymph node assay, direct peptide reactivity assay, KeratinoSens™, h-CLAT or U-SENS™ data. Here we describe the incorporation of benchmark exposures pertaining to use of consumer products with clinical data supporting a high/low risk categorisation for skin sensitisation. Margins-of-exposure (potency estimate to consumer exposure level ratio) are regressed against the benchmark risk classifications, enabling derivation of a risk metric defined as the probability that an exposure is low risk. This approach circumvents the use of safety assessment factors and provides a simple and transparent mechanism whereby clinical experience can directly feed-back into risk assessment decisions.

Next generation risk assessment for skin allergy: Decision making using new approach methodologies

Our aim is to develop and apply next generation approaches to skin allergy risk assessment (SARA) that do not require new animal test data and better quantify uncertainties. Significant progress has been made in the development of New Approach Methodologies (NAMs), non-animal test methods, for assessment of skin sensitisation and there is now focus on their application to derive potency information for use in Next Generation Risk Assessment (NGRA). The SARA model utilises a Bayesian statistical approach to infer a human-relevant metric of sensitiser potency and a measure of risk associated with a given consumer exposure based upon any combination of human repeat insult patch test, local lymph node, direct peptide reactivity assay, KeratinoSens™, h-CLAT or U-SENS™ data. Here we have applied the SARA model within our weight of evidence NGRA framework for skin allergy to three case study materials in four consumer products. Highlighting how to structure the risk assessment, apply NAMs to derive a point of departure and conclude on consumer safety risk. NGRA based upon NAMs were, for these exposures, at least as protective as the historical risk assessment approaches. Through such case studies we are building our confidence in using NAMs for skin allergy risk assessment.

Weight of Evidence Approach for Skin Sensitization Potency Categorization of Fragrance Ingredients

Reliable human potency data are necessary for conducting quantitative risk assessments, as well as development and validation of new nonanimal methods for skin sensitization assessments. Previously, human skin sensitization potency of fragrance materials was derived primarily from human data or the local lymph node assay.

Assessment of the skin sensitization potential of fragrance ingredients using the U-SENS™ assay

The U-SENS™ assay was developed to address the third key event of the skin sensitization adverse outcome pathway (AOP) and is described in OECD test guideline 442E, Annex II. A dataset of 68 fragrance ingredients comprised of 7 non-sensitizers and 61 sensitizers was tested in the U-SENS™ assay. The potential for fragrance ingredients to activate dendritic cells, measured by U-SENS™, was compared to the sensitization potential determined by weight of evidence (WoE) from historical data. Of the non-sensitizers, 4 induced CD86 cell surface marker ≥1.5-fold while 3 did not. Of the sensitizers, 50 were predicted to be positive in U-SENS™, while the remaining 11 were negative. Positive and negative predictive values (PPV and NPV) of U-SENS™ were 93% and 21%, respectively. No specific chemical property evaluated could account for misclassified ingredients. Assessment of parent and metabolite protein binding alerts in silico suggests that parent chemical metabolism may play a role in CD86 activation in U-SENS™. Combining the U-SENS™ assay in a "2 out of 3" defined approach with the direct peptide reactivity assay (DPRA) and KeratinoSens™ predicted sensitization hazard with PPV and NPV of 97% and 24%, respectively. Combining complementary in silico and in vitro methods to the U-SENS™ assay should be integrated to define the hazard classification of fragrance ingredients, since a single NAM cannot replace animal-based methods.

Derivation of the no expected sensitization induction level for dermal quantitative risk assessment of fragrance ingredients using a weight of evidence approach

Some fragrance ingredients may have the potential to induce skin sensitization in humans but can still be safely formulated into consumer products. Quantitative Risk Assessment (QRA) for dermal sensitization is required to determine safe levels at which potential skin sensitizers can be incorporated into consumer products. The no expected sensitization induction level or NESIL is the point of departure for the dermal QRA. Sensitization assessment factors are applied to the NESIL to determine acceptable exposure levels at which no skin sensitization induction would be expected in the general population. This paper details the key steps involved in deriving a weight of evidence (WoE) NESIL for a given fragrance ingredient using all existing data, including in vivo, in vitro, and in silico. Read-across can be used to derive a NESIL for a group of structurally similar materials when data are insufficient. When sufficient target and read-across data are lacking, exposure waiving threshold (the DST) may be used. We outline the process as it currently stands at the Research Institute for Fragrance Materials Inc. (RIFM) and provide examples, but it is dynamic and is bound to change with evolving science as new approach methodologies (NAMs) are actively incorporated.

Tolerability profile of topical cannabidiol and palmitoylethanolamide: a compilation of single-centre randomized evaluator-blinded clinical and in vitro studies in normal skin

BACKGROUND

An increasing number of studies have investigated the adverse effect profile of oral cannabinoids; however, few studies have provided sufficient data on the tolerability of topical cannabinoids in human participants.

AIM

To assess the tolerability profile of several commercial topical formulations containing cannabidiol (CBD) and palmitoylethanolamide (PEA) on the skin of healthy human participants.

METHODS

Three human clinical trials and one in vitro study were conducted. The potential for skin irritation, sensitization and phototoxicity of several products, were assessed via patch testing on healthy human skin. The products assessed included two formulations containing CBD and PEA, one containing hemp seed oil and four concentrations of CBD alone. Ocular toxicity was tested using a traditional hen's egg chorioallantoic membrane model with three CBD, PEA and hemp seed oil formulations.

RESULTS

There was no irritation or sensitization of the products evident via patch testing on healthy participants. Additionally, mild phototoxicity of a hemp seed oil product was found at the 48-h time point compared with the negative control. The in vitro experiment demonstrated comparable effects of cannabinoid products with historically nonirritating products.

CONCLUSION

These specific formulations of CBD- and PEA-containing products are nonirritating and nonsensitizing in healthy adults, and further encourage similar research assessing their long-term safety and efficacy in human participants with dermatological diseases. There are some limitations to the study: (i) external validity may be limited as formulations from a single manufacturer were used for this study, while vast heterogeneity exists across unregulated, commercial CBD products on the market; and (ii) products were assessed only on normal, nondiseased human skin, and therefore extrapolation to those with dermatological diseases cannot be assumed.

Draize human repeat insult patch test (HRIPT): Seven decades of pitfalls and progress

Allergic contact dermatitis, a Type IV delayed hypersensitivity reaction, can result in dermatologic signs/symptoms for patients/workers. The likelihood of this phenomenon has been estimated/predicted for numerous chemicals/drugs by animal model and human patch testing protocols developed over the last century. Karl Landsteiner initiated testing with guinea pig studies; further studies based on his initial concept were in continual development. John Draize extended Landsteiner's guinea pig studies (which led to development of blood transfusions) to a human assay documenting irritant and allergic contact dermatitis potential - for drugs, chemicals, mixtures and products. We performed a literature search of major Draize derived protocols of the human repeat insult patch test (HRIPT). Our results reveal minor and major differences between protocols and lack of international standardization. Key clarification and principles post-Draize modified and improved usefulness of the HRIPT. Without a standard method of performing the HRIPT, it is problematic to generalize results of studies summarized here. Furthermore, we suggest a potential standardization procedure/protocol combining the work of the most satisfactory HRIPT methods. As the HRIPT constitutes a key parameter in current quantitative risk assessment for chemicals/drugs, such standardization should aid potential prediction of allergic contact dermatitis potential.

Fragrance Skin Sensitization Evaluation and Human Testing: 30-Year Experience

Background

The human repeated insult patch test (HRIPT) has a history of use in the fragrance industry as a component of safety evaluation, exclusively to confirm the absence of skin sensitization at a defined dose.

Objective

The aim of the study was to document the accumulated experience from more than 30 years of conducting HRIPTs.

Methods

A retrospective collation of HRIPT studies carried out to a consistent protocol was undertaken, with each study comprising a minimum of 100 volunteers.

Conclusions

The HRIPT outcomes from 154 studies on 134 substances using 16,512 volunteers were obtained. Most studies confirmed that at the selected induction/challenge dose, sensitization was not induced. In 0.12% of subjects (n = 20), there was induction of allergy. However, in the last 11 years, only 3 (0.03%) of 9854 subjects became sensitized, perhaps because of improved definition of a safe HRIPT dose from the local lymph node assay and other skin sensitization methodologies, as well as more rigorous application of the standard protocol after publication in 2008. This experience with HRIPTs demonstrates that de novo sensitization induction is rare and becoming rarer, but it plays an important role as an indicator that toxicological predictions from nonhuman test methods (in vivo and in vitro methods) can be imperfect.

Updating exposure assessment for skin sensitization quantitative risk assessment for fragrance materials

In 2008, a proposal for assessing the risk of induction of skin sensitization to fragrance materials Quantitative Risk Assessment 1 (QRA1) was published. This was implemented for setting maximum limits for fragrance materials in consumer products. However, there was no formal validation or empirical verification after implementation. Additionally, concerns remained that QRA1 did not incorporate aggregate exposure from multiple product use and included assumptions, e.g. safety assessment factors (SAFs), that had not been critically reviewed. Accordingly, a review was undertaken, including detailed re-evaluation of each SAF together with development of an approach for estimating aggregate exposure of the skin to a potential fragrance allergen. This revision of QRA1, termed QRA2, provides an improved method for establishing safe levels for sensitizing fragrance materials in multiple products to limit the risk of induction of contact allergy. The use of alternative non-animal methods is not within the scope of this paper. Ultimately, only longitudinal clinical studies can verify the utility of QRA2 as a tool for the prevention of contact allergy to fragrance materials.

RIFM fragrance ingredient safety assessment, phenylacetaldehyde, CAS Registry Number 122-78-1

The existing information supports the use of this material as described in this safety assessment. The material (phenylacetaldehyde) was evaluated for genotoxicity, repeated dose toxicity, developmental and reproductive toxicity, local respiratory toxicity, phototoxicity, skin sensitization, and environmental safety. Data show that phenylacetaldehyde is not genotoxic and provide a calculated margin of exposure (MOE) > 100 for the repeated dose and developmental and reproductive toxicity endpoints. Data from phenylacetaldehyde provided a No Expected Sensitization Induction Level (NESIL) of 590 μg/cm² for the skin sensitization endpoint. The local respiratory toxicity endpoint was completed using the threshold of toxicological concern (TTC) for a Cramer Class I material, and the exposure to phenylacetaldehyde was below the TTC (0.03 mg/kg/day, 0.03 mg/kg/day, and 1.4 mg/day, respectively). The phototoxicity/photoallergenicity endpoint was completed based on data and ultraviolet (UV) spectra; phenylacetaldehyde is not expected to be phototoxic/photoallergenic. The environmental endpoints were evaluated; phenylacetaldehyde was not found to be persistent, bioaccumulative, and toxic (PBT) as per the International Fragrance Association (IFRA) environmental standards and its risk quotients, based on its current volume of use in Europe and North America (i.e., Predicted Environmental Concentration/Predicted No Effect Concentration [PEC/PNEC]) are <1.

International regulatory requirements for skin sensitization testing

Skin sensitization test data are required or considered by chemical regulation authorities around the world. These data are used to develop product hazard labeling for the protection of consumers or workers and to assess risks from exposure to skin-sensitizing chemicals. To identify opportunities for regulatory uses of non-animal replacements for skin sensitization tests, the needs and uses for skin sensitization test data must first be clarified. Thus, we reviewed skin sensitization testing requirements for seven countries or regions that are represented in the International Cooperation on Alternative Test Methods (ICATM). We noted the type of skin sensitization data required for each chemical sector and whether these data were used in a hazard classification, potency classification, or risk assessment context; the preferred tests; and whether alternative non-animal tests were acceptable. An understanding of national and regional regulatory requirements for skin sensitization testing will inform the development of ICATM's international strategy for the acceptance and implementation of non-animal alternatives to assess the health hazards and risks associated with potential skin sensitizers.

Fragrances Categorized According to Relative Human Skin Sensitization Potency

Background

The development of non-animal alternatives for skin sensitization potency prediction is dependent upon the availability of a sufficient dataset whose human potency is well characterized. Previously, establishment of basic categorization criteria for 6 defined potency categories, allowed 131 substances to be allocated into them entirely on the basis of human information.

Objectives

To supplement the original dataset with an extended range of fragrance substances.

Methods

A more fully described version of the original criteria was used to assess 89 fragrance chemicals, allowing their allocation into one of the 6 potency categories.

Results

None of the fragrance substances were assigned to the most potent group, category 1, whereas 11 were category 2, 22 were category 3, 37 were category 4, and 19 were category 5. Although none were identified as non-sensitizing, note that substances in category 5 also do not pass the threshold for regulatory classification.

Conclusions

The combined datasets of >200 substances placed into potency categories solely on the basis of human data provides an essential resource for the elaboration and evaluation of predictive non-animal methods.

Prediction of skin sensitization potency using machine learning approaches

The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes. Input variables for our models included six physicochemical properties and data from three non-animal test methods: direct peptide reactivity assay; human cell line activation test; and KeratinoSens™ assay. Models were built to predict three potency categories using four machine learning approaches and were validated using external test sets and leave-one-out cross-validation. A one-tiered strategy modeled all three categories of response together while a two-tiered strategy modeled sensitizer/non-sensitizer responses and then classified the sensitizers as strong or weak sensitizers. The two-tiered model using the support vector machine with all assay and physicochemical data inputs provided the best performance, yielding accuracy of 88% for prediction of LLNA outcomes (120 substances) and 81% for prediction of human test outcomes (87 substances). The best one-tiered model predicted LLNA outcomes with 78% accuracy and human outcomes with 75% accuracy. By comparison, the LLNA predicts human potency categories with 69% accuracy (60 of 87 substances correctly categorized). These results suggest that computational models using non-animal methods may provide valuable information for assessing skin sensitization potency. Copyright © 2017 John Wiley & Sons, Ltd.

QSAR models of human data can enrich or replace LLNA testing for human skin sensitization

Skin sensitization is a major environmental and occupational health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. We have compiled, curated, analyzed, and compared the available human and LLNA data. Using these data, we have developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. The overall concordance between murine LLNA and human skin sensitization responses for a set of 135 unique chemicals was low (R = 28-43%), although several chemical classes had high concordance. We have succeeded to develop predictive QSAR models of all available human data with the external correct classification rate of 71%. A consensus model integrating concordant QSAR predictions and LLNA results afforded a higher CCR of 82% but at the expense of the reduced external dataset coverage (52%). We used the developed QSAR models for virtual screening of CosIng database and identified 1061 putative skin sensitizers; for seventeen of these compounds, we found published evidence of their skin sensitization effects. Models reported herein provide more accurate alternative to LLNA testing for human skin sensitization assessment across diverse chemical data. In addition, they can also be used to guide the structural optimization of toxic compounds to reduce their skin sensitization potential.

Multivariate models for prediction of human skin sensitization hazard

One of the Interagency Coordinating Committee on the Validation of Alternative Method's (ICCVAM) top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary to produce skin sensitization suggests that no single alternative method will replace the currently accepted animal tests. ICCVAM is evaluating an integrated approach to testing and assessment based on the adverse outcome pathway for skin sensitization that uses machine learning approaches to predict human skin sensitization hazard. We combined data from three in chemico or in vitro assays - the direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens™ assay - six physicochemical properties and an in silico read-across prediction of skin sensitization hazard into 12 variable groups. The variable groups were evaluated using two machine learning approaches, logistic regression and support vector machine, to predict human skin sensitization hazard. Models were trained on 72 substances and tested on an external set of 24 substances. The six models (three logistic regression and three support vector machine) with the highest accuracy (92%) used: (1) DPRA, h-CLAT and read-across; (2) DPRA, h-CLAT, read-across and KeratinoSens; or (3) DPRA, h-CLAT, read-across, KeratinoSens and log P. The models performed better at predicting human skin sensitization hazard than the murine local lymph node assay (accuracy 88%), any of the alternative methods alone (accuracy 63-79%) or test batteries combining data from the individual methods (accuracy 75%). These results suggest that computational methods are promising tools to identify effectively the potential human skin sensitizers without animal testing. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.