Reconstructing a Modeling Tool
Industrial Hygienists’ Journey to Improving Company Control Banding
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Health and safety legislation around the world requires that workers be protected from unsafe conditions or exposures that may harm their health. While industrial hygienists may address a range of workplace hazards, including noise, vibration, radiation, thermal stressors, and ergonomic factors, the profession often focuses on exposure to hazardous substances. This has led to the development of exposure assessment approaches intended to quantify inhalation exposures and demonstrate compliance with occupational exposure limits.
Direct measurements of hazardous substances in air, collected from the breathing zones of workers, are generally considered the gold standard for estimating exposures. But as the industrial hygiene community knows, quantitative exposure assessment, or exposure monitoring, is just one component of exposure assessment; professional judgment and qualitative exposure assessment play roles as well, particularly where OELs do not exist yet there may be a need for some form of assessment and control. Several approaches to aid in qualitative exposure assessment—control banding systems and exposure modeling tools, for example—are also available.
Can such tools and models help companies improve the identification of controls prior to exposure monitoring? As industrial hygienists tasked with implementing exposure assessment strategies in our respective organizations, we set out to examine existing tools for qualitative exposure assessment to see how they might be used to improve our companies’ existing control banding systems. Here’s the story of how we came to adapt one of them for application as an internal qualitative assessment tool.
Control banding involves the categorization of hazardous substances into “bands,” which are in turn associated with workplace exposure control approaches like containment or local exhaust ventilation. Control banding approaches were originally developed in the pharmaceutical industry to facilitate exposure risk management for active ingredients with few toxicological data, but these approaches have also been applied more widely as other industries seek a simplified framework for hazardous substance exposure risk management—sometimes in cases where professional industrial hygiene skills are not readily available. Control of Substances Hazardous to Health (COSHH) Essentials from the U.K.’s Health and Safety Executive (HSE) is one example of a control banding approach.
COSHH Essentials matches a given hazard band (based on Globally Harmonized System of Classification and Labeling of Chemicals hazard statements, or H-statements) and an exposure potential (based on a measure of dustiness or volatility) to a control approach. COSHH Essentials facilitates a generic risk assessment to recommend control approaches in one of four categories: general ventilation, engineering controls, containment, and special (this category requires expert advice). The technical basis for COSHH Essentials is described in the HSE publication “COSHH Essentials: Controlling Exposure to Chemicals – A Simple Control Banding Approach” (PDF).
Another example of a publicly available control banding system is the EMKG (known in English as the “Easy-to-Use Workplace Control Scheme for Hazardous Substances” and in German as Einfaches Maßnahmenkonzept Gefahrstoffe), which was developed by the Federal Institute for Occupational Safety and Health, or BAuA, in Germany. Control banding systems like these are considered simple exposure modeling tools that incorporate conservative exposure assumptions and are therefore classified as tier 1 exposure models under the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) regulation framework in Europe.
Control banding systems may be considered action-oriented, qualitative risk assessment tools, but they have some limitations—for instance, they have a tendency toward conservative control recommendations based on generic inputs. Nevertheless, such systems have proven useful in aiding exposure assessment by facilitating a consistent approach that nonexpert assessors may apply.
Examples of results users may encounter in ExCMO regarding IH control strategies. Images are screenshots from ExCMO. Click or tap on the images above for a larger view in your browser.
EXPOSURE MODELING Exposure modeling relies on a more detailed incorporation of the factors that contribute to exposure in a given situation and on a selected underlying principle—for example, a mechanistic model vs. a physical mass balance model. (An article published in 2020 in the International Journal of Environmental Research and Public Health describes the ongoing debate as to the most appropriate scientific basis for exposure models. This debate is outside the scope of this article.) Provided that an exposure modeling approach has a sound scientific basis, it may be considered more sophisticated than control banding approaches.
According to the tiered classification of models under the European Union’s REACH regulation, models that go beyond control banding are classified as tier 2 exposure models. The Advanced REACH Tool is one example. These models typically aim to estimate exposure in a unit useful to the assessor (like ppm or mg/m3) based on exposure scenario information such as the characteristics of the hazardous substance involved, the activity being performed, the worker’s position relative to the exposure source, duration of exposure, ventilation rates, or other control measures present. Such exposure estimates allow assessors to compare results to relevant OELs to determine the level of acceptability of the exposure and may be considered semi-quantitative. In our opinion, exposure modeling has not yet developed sufficiently to replace quantitative assessment; however, exposure models are of interest as tools to make qualitative assessment more consistent.
OUR CONSIDERATIONS We began our project to improve upon the more traditional control banding systems used in pharmaceuticals with two key questions: first, could exposure modeling for inhalation exposure be integrated into our in-company exposure assessment approaches? And second, could some of the functionality provided by existing control banding systems—especially the ability for nonexperts to qualitatively identify appropriate engineering control measures—be maintained?
We approached these questions by first surveying available exposure modeling tools. Among the considerations important to us were the scientific basis of a model, the degree of validation with real-world exposure monitoring data, applicability across various types of exposure scenarios, acceptability under regulatory frameworks, and—crucially—whether a model and its underlying algorithm were publicly published and available. Modeling tools of interest included the commercially available Stoffenmanager, ECETOC’s Targeted Risk Assessment (TRA), the Advanced REACH Tool (ART), and AIHA’s IHMOD spreadsheet, all of which are available online. ART interested us the most because it was a more sophisticated tier 2 model and the development of its algorithm is published in the scientific literature along with several validation and model comparison studies. Its application in the pharmaceutical industry was of particular relevance to our project.
THE ADVANCED REACH TOOL ART is a mechanistic model based on a source-receptor approach that aims to describe the transport of a hazardous substance in air from the source to the receptor. It considers several independent modifying factors, including the substance emission potential, activity emission potential, localized controls, segregation, personal enclosure, surface contamination, and dispersion. While chemical and physical laws, along with empirical data from literature, were used in establishing the model, it’s important to note that its development also included an element of expert judgment with peer review by leading experts from industry, research institutes, and public authorities. The original algorithm was calibrated with more than 2,000 occupational exposure measurements and has been further validated and compared in several follow-up publications. In general, validation studies indicated sufficient conservatism in modeled exposure estimates compared to occupational exposure measurements when higher decision statistics and confidence intervals were selected (the 90th percentile and 90 percent confidence interval, for example), and a general tendency to overestimate lower exposures while underestimating higher exposures. One validation study comparing ART estimates to data from the pharmaceutical industry indicated a tendency toward underestimating exposures, although it was based on a relatively small dataset. (Readers who wish to understand more about ART’s development and validation can find further reading in the box below.)
The existing ART algorithm only allows for the assessment of vapors, mists, and dusts, and estimates exposure over a task-based duration, expressing results in mg/m3. Since the model generates an underlying exposure distribution for each estimate, it also allows for the selection of a decision statistic (for example, the 95th percentile) along with confidence intervals. Since exposure estimates are based on the task, ART further allows calculation of time-weighted average estimates based on the assumption of zero exposure over the remainder of the working shift or by combining several exposure activities into one estimate. Finally, ART allows the integration of occupational exposure data through Bayesian inference to refine and improve accuracy of modeled exposure estimates.
ART is publicly available online.
A NEW TOOL Based on our understanding of ART’s development and limitations, we decided to jointly develop a new tool, reconstructing ART’s algorithm for application as an in-company qualitative assessment tool. The Exposure Control Modeling Tool, or ExCMO for short, was developed so that users can choose between two pathways when it comes to input parameters. For the first pathway, Industrial Hygiene Control Strategies (IHCS), ExCMO estimates the 95th percentile of the exposure distribution and compares it with the relevant OEL. The output displayed is the most appropriate control strategy that is expected to maintain the generated exposure below the OEL. If the user selects the second pathway, Exposure Assessment, ExCMO generates the exposure estimates at different percentiles (the 50th, 75th, 90th, 95th, and 99th percentiles) surrounded by different confidence intervals (70, 75, 80, 90, and 95 percent CI). ExCMO was programmed to enable calculation of the 70 percent CI, which is not included in the original ART.
Since ExCMO is based on ART’s algorithm, it was important to verify that we had correctly reconstructed the original algorithm by comparing results from the two tools using identical input parameters. We established through internal validation runs to a degree we judged appropriate that ExCMO could be considered an accurate replication of ART. However, ExCMO departs from the original ART in some important ways specific to our intended application:
Increased usability. In ExCMO, all exposure scenario inputs are organized on a single input page. When using the original ART, users must navigate through various pages, which we felt could potentially lead to poor adoption. The simplified design of ExCMO is intended to increase the speed and ease with which an exposure scenario can be assessed.
Default modeling inputs. ExCMO features certain model inputs as defaults to reduce the number of inputs required per assessment. In this case, the underlying ART algorithm was not adapted; for ExCMO’s intended application as a qualitative tool in pharmaceutical manufacturing, it made sense to set defaults for specific input requirements. (One example has to do with the input for drop height. When assessing transfer of powders, ART includes an option for powders falling with a drop height exceeding 0.5 meters. This is unlikely in our industry since best practices for powder handling in pharmaceutical operations dictate drop heights of less than 0.5 meters. Therefore, ExCMO by default calculates exposure estimates based on a drop height of less than 0.5 meters.)
Maintaining control-banding-like output. ExCMO’s IHCS pathway was developed based on concepts borrowed from control banding, specifically in expressing the results of modeling in terms of recommended engineering control measures. Local control options available in the ART algorithm are ordered based on assigned control efficiency multipliers and grouped into distinct categories to which we assigned further descriptors (for example, Control Strategy 2, described as “open handling,” is named “Local Exhaust Ventilation” in ExCMO).
Additional engineering control options. ExCMO has two additional control options that represent common control systems utilized in pharmaceuticals: “horizontal/laminar down flow booth (enclosing source) with screen and glove ports” and “closed restricted access barrier system.” We used our professional judgment to assign control efficiency multipliers based on similarities to other control options available in ART. For example, we applied the ART multiplier for “low specification glovebox” to the “closed restricted access barrier system” in ExCMO.
Like the original ART, ExCMO also has the ability to integrate exposure measurements through Bayesian integration. This function allows real data from a similar exposure scenario to be incorporated into the modeling estimate.
ADVANTAGES AND LIMITATIONS From our perspective, some advantages of using the exposure modeling approach stem from a comparison to historic control banding systems. For instance, the ART algorithm allows model predictions to be sensitive to the percentage of hazardous material present in a mixture, a typical scenario we encounter when assessing exposures in pharmaceutical operations. Since this sensitivity was not possible with control banding, control recommendations were potentially overly conservative. Another example has to do with the ability to apply the time-weighted average concept in predicting required engineering controls. Whenever an exposure scenario is consistent in duration and there is high confidence that no further exposure will occur during the remainder of the workday, exposure modeling enables the selection of control options that are more appropriate to the risk. These examples demonstrate the potential for ExCMO to reduce unnecessary conservatism compared to previous control banding systems. A further advantage over control banding is the tool’s ability to estimate exposures for products suspended or dissolved in non-volatile liquids.
In our view, exposure modeling is often discussed in academic literature, but less often systematically applied in industry. In addition, several validation studies indicate differing conclusions on model accuracy. Because of this, one limitation for practicing industrial hygienists likely relates to the level of understanding and trust in the outputs that models generate; however, we believe this is solved through framing existing tools like ExCMO as qualitative tools for the time being. A further limitation associated with the use of ExCMO is that the tool requires a valid OEL since the OEL is the key parameter used to determine recommended engineering control measures or for the purposes of estimating compliance. When an OEL does not exist, we recommend applying the NIOSH occupational exposure banding process to estimate OEL ranges that may be applicable. It’s also important to consider the need for training to ensure that assessors have an appropriate understanding of the meaning of different model input options to generate reasonable exposure estimates.
ExCMO is a success at our companies because it simplifies a fairly complicated exposure model into a user-friendly tool for use by our environmental health and safety professionals—most of whom are not certified industrial hygienists. The tool also provides a unified way of assessing our organizations’ chemical exposures. Our stakeholders appreciate that ExCMO is a more sophisticated type of assessment that produces an output they can understand, especially for engineering controls, and workers like seeing the results directly. One challenge for us has been overcoming the learning curve for the primary users of ExCMO, particularly teaching them how and when to apply different inputs for exposure scenarios. This requires training, both in terms of a basic theoretic understanding and practical application.
OUR EXPERIENCE ExCMO is an in-company tool intended to enhance qualitative exposure assessment approaches, including the identification of risk-appropriate engineering controls. The tool incorporates several industry- and company-specific settings; however, ExCMO is in principle based on the scientific work of the exposure scientists and organizations involved in developing ART.
We have incorporated an internal company-specific version of ExCMO into our standard exposure assessment process for qualitative assessment. One of our companies uses it as a standardized approach to estimate exposure risk before deciding when and where to conduct exposure monitoring. At the other, all company sites perform exposure assessments for active pharmaceutical ingredients (APIs) using ExCMO, which allows the company to obtain a uniform view of the level of control for all APIs across its sites. ExCMO is also our companies’ recommended tool for new engineering projects to identify what level of control is required based on the hazards associated with different substances; this helps ensure the appropriate level of control is in place from the beginning of each project.
The ExCMO tool is publicly available online. We encourage readers to test it out, keeping in mind its limitations and the understanding that exposure models can generate uncertain estimates. Remember also that ExCMO is based on ART, which was originally designed for all industries. We made changes to better align ExCMO with pharmaceutical operations, but it is by no means a tool only for our industry.
BRIAN SCHMIDT, MSc OH, MSc Tox, CMFOH, is the global industrial hygiene lead at Takeda Pharmaceuticals International AG in Switzerland.
NATHALIE ARGENTIN, CIH, is the global industrial hygiene lead at Ferring Pharmaceuticals SA in Switzerland.
Acknowledgment: The authors wish to thank the Center for Primary Care and Public Health (Unisanté) in Lausanne, Switzerland, and in particular Dr. Nenad Savic for their collaboration in building the ExCMO tool.
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The Annals of Occupational Hygiene: “Advanced REACH Tool: A Bayesian Model for Occupational Exposure Assessment” (June 2014).
The Annals of Occupational Hygiene: “Advanced Reach Tool (ART): Development of the Mechanistic Model” (November 2011).
Annals of Work Exposures and Health: “A Study of the Validity of Two Exposure Assessment Tools: Stoffenmanager and the Advanced REACH Tool” (June 2017).
Annals of Work Exposures and Health: “Comparing the Advanced REACH Tool’s (ART) Estimates with Switzerland’s Occupational Exposure Data” (October 2017).
Annals of Work Exposures and Health: “Evaluation of Exposure Assessment Tools Under REACH: Part II—Higher Tier Tools” (March 2019).
Annals of Work Exposures and Health: “Validation of Lower Tier Exposure Tools Used for REACH: Comparison of Tools Estimates with Available Exposure Measurements” (October 2017).
International Journal of Environmental Research and Public Health: “Exposure Models for REACH and Occupational Safety and Health Regulations” (January 2020).
Journal of Environmental Monitoring: “Advanced REACH Tool (ART): Calibration of the Mechanistic Model” (2011).
Journal of Environmental Monitoring: “Validation of the Inhalable Dust Algorithm of the Advanced REACH Tool Using a Dataset from the Pharmaceutical Industry” (2011).
TNO: “Development of a Mechanistic Model for the Advanced REACH Tool (ART)” (2013).
The Annals of Occupational Hygiene: “On the Strength and Validity of Hazard Banding” (November 2016).
Annals of Work Exposures and Health: “Accuracy Evaluation of Three Modelling Tools for Occupational Exposure Assessment” (April 2017).
Annals of Work Exposures and Health: “An Assessment of the Robustness of the COSHH-Essentials (C-E) Target Airborne Concentration Ranges 15 Years on, and Their Usefulness for Determining Control Measures” (2017).
Annals of Work Exposures and Health: “ART, Stoffenmanager, and TRA: A Systematic Comparison of Exposure Estimates Using the TREXMO Translation System” (January 2018).
Annals of Work Exposures and Health: “Between-User Reliability of Tier 1 Exposure Assessment Tools Used Under REACH” (October 2017).
Annals of Work Exposures and Health: “Evaluation of Tier One Exposure Assessment Models (ETEAM): Project Overview and Methods” (October 2017).
Chimica Oggi – Chemistry Today: “History, Implementation and Evolution of the Pharmaceutical Hazard Categorization and Control System” (2006).
European Chemicals Agency: “Occupational Exposure Assessment” in Guidance on Information Requirements and Chemical Safety Assessment, chapter R.14 (August 2016).
Federal Institute for Occupational Safety and Health (BAuA): “Easy-to-Use Workplace Control Scheme for Hazardous Substances (EMKG).”
Federal Institute for Occupational Safety and Health (BAuA): “Einfaches Maßnahmenkonzept Gefahrstoffe—Version 2.1: Eine Handlungshilfe Für Die Anwendung Der Gefahrstoffverordnung in Klein-Und Mittelbetrieben” (2008).
Health and Safety Executive: “COSHH Essentials: Controlling Exposure to Chemicals – A Simple Control Banding Approach” (PDF).
Journal of Exposure Science & Environmental Epidemiology: “Risk Management Measures for Chemicals: The ‘COSHH Essentials’ Approach” (June 2007).
Journal of Occupational and Environmental Hygiene: “History and Evolution of Control Banding: A Review” (2008).
NIOSH: “Technical Report: The NIOSH Occupational Exposure Banding Process for Chemical Risk Management” (July 2019).