Regulatory Decision-making Process Research Articles

Utilization of a novel human hepatocyte-endothelial cell coculture model to determine differential toxicities of pyrrolizidine alkaloid food contaminants

Pyrrolizidine alkaloids (PA) are comprised of a family of hundreds of metabolites, produced by plants as a mechanism to protect against herbivory. Upon ingestion and metabolism, dehydropyrrolizidine alkaloids are formed, which are known to generate DNA adducts and subsequently double-strand DNA breaks. Within the liver, the most sensitive cell type to PA exposure is the sinusoidal endothelial cell, as evidenced by the generation of veno-occlusive disease in the human population. PAs are a common crop contaminant and have been regulated by some agencies, using the precautionary principle; each equally potent and genotoxic. Therefore, as a proof of principle we have established a human in vitro coculture model system, utilizing the metabolically active HepaRG hepatocyte and the SK-Hep-1 endothelial cell, to determine differential potencies of different PAs commonly found in crops and food products, notably cell death, targeting of endothelial cells, and genotoxicity comparing the micronucleus assay versus γH2AX assay. Our results demonstrate differential potencies of the PAs used, which encompass three esterification states (monoester, cyclic diester, and open-chain diester). The results suggest that a more nuanced approach to the regulation of PAs may be more appropriate in the regulatory decision-making process.

Translational Insights into Molecular Mechanisms of Chemical Hepatocarcinogenesis for Improved Human Risk Assessment

Background: Hepatocellular carcinoma (HCC) is a prevalent liver cancer with major risk factors being hepatitis viral infections, alcohol, non-alcoholic fatty liver disease, and aflatoxin exposure. Both genotoxic and non-genotoxic agents can induce HCC through mechanisms involving DNA damage, oxidative stress, chronic inflammation, and disrupted signaling pathways like MAPK/ERK, PI3K/AKT, WNT/β-catenin and PPARα. While rodent assays are utilized to detect potential chemical hepatocarcinogens, species differences in pathways like PPARα and CAR/PXR activation impact human risk assessment. Purpose: This analysis provides an updated, critical examination of species concordance in mechanisms of hepatic carcinogenesis to inform human safety assessment of rodent liver tumor findings. Main Body: Rodent assays including 2-year bioassays, transgenic models, and short-term studies detect liver tumors through lifetime exposure or early biomarkers. However, rodent-specific PPARα and CAR/PXR activation, along with human risk factors like hepatitis, highlight key interspecies differences. Determining mode of action relevance requires evaluating mechanistic validity and pivotal key events leading to tumors across species. Non-genotoxic compounds eliciting rodent liver tumors can activate PPARα, CAR/PXR, and other pathways triggering increased cell replication; but downstream signaling may differ in human liver. Understanding applicability of these mechanisms in humans as well as incorporating human risk factors into experimental models is critical for accurate risk assessment. Conclusion: In summary, elucidating conserved versus divergent molecular mechanisms of hepatic carcinogenesis between rodents and humans is essential for appropriately interpreting rodent findings and safeguarding human health through science-based risk assessment frameworks and regulatory decision-making processes around potential chemical hazards.

ANALYSIS AND DEVELOPMENT OF A SMART NOISE INFORMATION COLLECTION SYSTEM BASED ON THE SPECTRUM ANALYZER SVAN 958A

This paper presents the analysis and development of a smart noise information collection system utilizing the Spectrum Analyzer SVAN 958A to enhance real-time noise monitoring and data analysis. The study addresses the limitations of traditional noise measurement tools, which often lack real-time processing and comprehensive integration with modern data management platforms. By leveraging the SVAN 958A’s advanced frequency domain analysis capabilities and integrating it with IoT-based technologies and machine learning algorithms, the proposed system aims to improve noise data accuracy, automation, and scalability. Through the design and implementation of a real-time data processing framework, the system enables precise noise source identification and facilitates immediate response to noise pollution issues. The system’s performance was validated in various urban and industrial noise environments, demonstrating significant improvements in noise data collection accuracy, with enhanced signal differentiation by up to 35% over traditional methods. Additionally, real-time data visualization tools were developed to support regulatory compliance and decision-making processes. The results of this research suggest that the proposed smart noise information collection system can serve as an efficient tool for environmental noise monitoring, offering both practical benefits for public health and potential applications in smart city infrastructure. The system also opens avenues for further research in integrating advanced analytics into acoustic monitoring frameworks, contributing to the ongoing development of smart environmental management technologies.

Harmonized Data Quality Indicators Maintain Data Quality in Long-Term Safety Studies Using Multiple Sclerosis Registries/Data Sources: Experience from the CLARION Study.

Understanding the long-term safety of disease-modifying therapies for multiple sclerosis (MS) in routine clinical practice can be undertaken through registry-based studies. However, variability of data quality across such sources poses the challenge of data fit for regulatory decision-making. CLARION, a non-interventional cohort safety study of cladribine tablets, combines aggregated data from MS registries/data sources, except in Germany (which utilizes primary data collection). We describe the application of key data quality indicators (DQIs) within CLARION to evaluate data quality over time, as recommended by the European Medicines Agency (EMA) guideline on registry-based studies. DQIs were defined with participating registries/sources; they were used to assess data quality according to the EMA Data Quality Framework, addressing consistency, accuracy, completeness, and study representativeness. DQIs were associated with potential remedial measures if data quality was not met. DQIs were summarized overall and for individual MS registries/data sources to November 1, 2022. A total of 28 DQIs were analyzed using data from 5069 patients arising from eight MSregistries/data sources and 14countries. The Representativeness DQIs showed that 72.0% of patients were female, median age at MS diagnosis was 29.0 to 43.3 years, and 93.5% had relapsing-remitting MS. Consistency DQIs showed a total of 2899 patients had achieved at least two years of follow-up; 6.9% did not have any recorded visits during this timeframe. Discrepant values were assessed as part of Accuracy DQIs, and improvements over time were noted for recorded dates of MS onset and diagnosis. Regarding Completeness DQIs, 191/5069 (3.8%) patients were lost to follow-up. The application of 28 DQIs within the CLARION study has helped with understanding, not only intrinsic and question-specific determinants of data quality, but also tracking the quality of post-authorization safety data obtained from MS registries/data sources, thereby providing a foundation for the regulatory decision-making process.

Patient Engagement and Patient Experience Data in Regulatory Review and Health Technology Assessment: A Global Landscape Review

BackgroundWorking with patients through meaningful patient engagement (PE) and incorporating patient experience data (PXD) is increasingly important in medicines and medical device development. However, PE in the planning, organization, generation, and interpretation of PXD within regulatory and health technology assessment (HTA) decision-making processes remains challenging. We conducted a global review of the PE and PXD landscape to identify evolving resources by geography to support and highlight the potential of integration of PE and PXD in regulatory assessment and HTA.MethodsA review of literature/public information was conducted (August 2021–January 2023), led by a multistakeholder group comprising those with lived or professional experience of PE and PXD, to identify relevant regulatory and HTA initiatives and resources reviewed and categorized by geography and focus area.ResultsOverall, 53 relevant initiatives/resources were identified (global, 14; North America, 11; Europe, 11; Asia, nine; UK, six; Latin America, one; Africa, one). Most focused either on PE (49%) or PXD (28%); few (11%) mentioned both PE and PXD (as largely separate activities) or demonstrated an integration of PE and PXD (11%).ConclusionsOur analysis demonstrates increasing interest in PE, PXD, and guidance on their use individually in decision-making. However, more work is needed to offer guidance on maximizing the value of patient input into decisions by combining both PE and PXD into regulatory and HTA processes; the necessity of integrating PE in the design and interpretation of PXD programs should be highlighted. A co-created framework to achieve this integration is part of a future project.

Perception of Green Facility Management

The paper aims to identify the attitudes and opinions of selected types of actors regarding green facility management and its practice. This objective is fulfilled by developing a questionnaire survey among selected groups of actors. Understanding the views and attitudes of actors can inform strategic green facility management, the development of an appropriate regulatory and methodological framework and decision-making processes at different levels.

Application of implementation science framework to develop and adopt regulatory science in different national regulatory authorities.

The purpose of developing and adopting regulatory science (RS) for drug regulatory authorities (DRAs) is to enhance regulatory capacity by advancing the scientific approach for the evaluation of health-related products. While many DRAs around the world advocate the concept of RS, the implementation approaches of RS vary according to local needs and have not been systemically examined. This study aimed to systematically identify the evidence about how RS was developed, adopted, and advanced by the selected DRAs, and analyzed and compared the implementation experiences of RS development under the guidance of an implementation science framework. Documentary analysis of government documents and a scoping literature review were conducted, and data analysis was performed under the guidance of the PRECEDE-PROCEED Model (PPM). DRAs in the United States, the European Union, Japan, and China had officially launched RS initiatives and were therefore selected as the target countries in this study. There is no common consensus on the definition of RS among the DRAs. However, these DRAs shared the same goal of developing and adopting RS, which was used to develop new tools, standards, and guidelines that could improve the effectiveness and efficiency of the risk and benefit assessment of the regulated products. Each DRA had decided its own priority areas for RS development and thus set specific objectives that might be technology-based (e.g., toxicology and clinical evaluation), process-based (e.g., partnership with healthcare systems and high-quality review/consultation services), or product-based (e.g., drug-device combination products and innovative emerging technologies). To advance RS, considerable resources had been allocated for staff training, advancing information technology and laboratory infrastructure, and funding research projects. DRAs also took multifaceted approaches to expand scientific collaborations through public-private partnerships, research funding mechanisms, and innovation networks. Cross-DRA communications were also reinforced through horizon scanning systems and consortiums to better inform and assist the regulatory decision-making process. The output measurements might be scientific publications, funded projects, DRAs interactions, and evaluation methods and guidelines. Improved regulatory efficiency and transparency leading to benefits to public health, patient outcomes, and translation of drug research and development as the key primary outcomes of RS development were anticipated but not yet clearly defined. The application of the implementation science framework is useful for conceptualizing and planning the development and adoption of RS for evidence-based regulatory decision-making. Continuous commitment to the RS development and regular review of the RS goals by the decision-makers are important for DRAs to meet the ever-changing scientific challenges in their regulatory decision-making process.

Patient-Centered Clinical Trial Design for Heart Failure Devices via Bayesian Decision Analysis.

The statistical significance of clinical trial outcomes is generally interpreted quantitatively according to the same threshold of 2.5% (in one-sided tests) to control the false-positive rate or type I error, regardless of the burden of disease or patient preferences. The clinical significance of trial outcomes-including patient preferences-are also considered, but through qualitative means that may be challenging to reconcile with the statistical evidence. We aimed to apply Bayesian decision analysis to heart failure device studies to choose an optimal significance threshold that maximizes the expected utility to patients across both the null and alternative hypotheses, thereby allowing clinical significance to be incorporated into statistical decisions either in the trial design stage or in the post-trial interpretation stage. In this context, utility is a measure of how much well-being the approval decision for the treatment provides to the patient. We use the results from a discrete-choice experiment study focusing on heart failure patients' preferences, questioning respondents about their willingness to accept therapeutic risks in exchange for quantifiable benefits with alternative hypothetical medical device performance characteristics. These benefit-risk trade-off data allow us to estimate the loss in utility-from the patient perspective-of a false-positive or false-negative pivotal trial result. We compute the Bayesian decision analysis-optimal statistical significance threshold that maximizes the expected utility to heart failure patients for a hypothetical two-arm, fixed-sample, randomized controlled trial. An interactive Excel-based tool is provided that illustrates how the optimal statistical significance threshold changes as a function of patients' preferences for varying rates of false positives and false negatives, and as a function of assumed key parameters. In our baseline analysis, the Bayesian decision analysis-optimal significance threshold for a hypothetical two-arm randomized controlled trial with a fixed sample size of 600 patients per arm was 3.2%, with a statistical power of 83.2%. This result reflects the willingness of heart failure patients to bear additional risks of the investigational device in exchange for its probable benefits. However, for increased device-associated risks and for risk-averse subclasses of heart failure patients, Bayesian decision analysis-optimal significance thresholds may be smaller than 2.5%. A Bayesian decision analysis is a systematic, transparent, and repeatable process for combining clinical and statistical significance, explicitly incorporating burden of disease and patient preferences into the regulatory decision-making process.

Use of Bayesian decision analysis to maximize value in patient-centered randomized clinical trials in Parkinson’s disease

ABSTRACT A fixed one-sided significance level of 5% is commonly used to interpret the statistical significance of randomized clinical trial (RCT) outcomes. While it is necessary to reduce the false positive rate, the threshold used could be chosen quantitatively and transparently to specifically reflect patient preferences regarding benefit–risk tradeoffs as well as other considerations. How can patient preferences be explicitly incorporated into RCTs in Parkinson’s disease (PD), and what is the impact on statistical thresholds for device approval? In this analysis, we apply Bayesian decision analysis (BDA) to PD patient preference scores elicited from survey data. BDA allows us to choose a sample size () and significance level () that maximizes the overall expected value to patients of a balanced two-arm fixed-sample RCT, where the expected value is computed under both null and alternative hypotheses. For PD patients who had previously received deep brain stimulation (DBS) treatment, the BDA-optimal significance levels fell between 4.0% and 10.0%, similar to or greater than the traditional value of 5%. Conversely, for patients who had never received DBS, the optimal significance level ranged from 0.2% to 4.4%. In both of these populations, the optimal significance level increased with the severity of the patients’ cognitive and motor function symptoms. By explicitly incorporating patient preferences into clinical trial designs and the regulatory decision-making process, BDA provides a quantitative and transparent approach to combine clinical and statistical significance. For PD patients who have never received DBS treatment, a 5% significance threshold may not be conservative enough to reflect their risk-aversion level. However, this study shows that patients who previously received DBS treatment present a higher tolerance to accept therapeutic risks in exchange for improved efficacy which is reflected in a higher statistical threshold.

Benchmarking the performance of water companies for regulatory purposes to improve its sustainability

The regulation of water companies (WCs) is essential to protect the interests of citizens, as companies are natural monopolies. Consequently, several methodological approaches are applied by water regulators to benchmark the performance of WCs, with data envelopment analysis (DEA) being one of the most widely applied. However, traditional DEA models allocate different weights to variables considered in efficiency assessments of each WC. By contrast, this study proposes and applies a common set weights (CSW) DEA model to a sample of Chilean WCs. The results showed that the DEA-CSW approach had greater discriminatory capacity compared to traditional DEA techniques. Moreover, weights allocated to input and output variables involved in efficiency assessment diverged among WCs when the traditional DEA model was employed. By contrast, the DEA-CSW approach generated reliable ranking of WCs based on their efficiency scores, thus facilitating the regulatory decision-making process.

Lost in the woods: Finding our way back to the scientific method in systematic review.

Systematic review has become the preferred approach to addressing causality and informing regulatory and other decision-making processes, including chemical risk assessments. While advocates of systematic reviews acknowledge that they hold great potential for increasing objectivity and transparency in assessments of chemicals and human health risks, standardizing and harmonizing systematic review methods have been challenging. This review provides a brief summary of the development of systematic review methods and some of the frameworks currently in use in the US and Europe. We also provide an in-depth evaluation and comparison of two "competing" US EPA systematic review frameworks, informed by the constructively critical recommendations from the US National Academies of Science, Engineering and Medicine. We conclude with suggestions for moving forward to harmonize systematic review methods, as we believe that further criticism of individual available frameworks likely will be unproductive. Specifically, we issue a call to action for an international collaboration to work toward a blueprint that embraces the most scientifically critical elements common to most systematic review frameworks, while necessarily accommodating adaptations for specific purposes. Despite the array of available systematic review methods, it is clear that there is a shared goal and desire to promote objective assessment and synthesis of scientific evidence informing globally important issues regarding disease causality and human health risk evaluation.

The impact of FDA and EMA regulatory decision-making process on the access to CFTR modulators for the treatment of cystic fibrosis

BackgroundOver the past decade, a new class of drugs called CFTR (cystic fibrosis transmembrane conductance regulator) modulators have shown to be able to improve clinical outcomes in patient with Cystic Fibrosis. In this analysis, we have extensively reviewed the regulatory pathways and decisions adopted by FDA and EMA to speed up the development, the review and the approval of these drugs, with the aim of identifying possible clinical and public health implications associated with differences.ResultsCFTR modulators have been developed towards addressing three main genetic domains: (1) F508del homozygous (F508del/F508del), (2) F508del heterozygous, and (3) genotypes not carrying F508del mutation; and expanded from adult to paediatric population. Programs to expedite the reviewing and licensing of CFTR modulators were extensively adopted by FDA and EMA. All CFTR modulators have been licensed in the US as orphan drugs, but in the EU the orphan status for LUM/IVA was not confirmed at the time of marketing authorization as results from the pivotal trial were not considered clinically significant. While FDA and EMA approved CFTR modulators on the basis of results from phase III double-blind RCTs, main differences were found on the extension of indications: FDA accepted non-clinical evidence considering a recovery of the CFTR function ≥ 10% based on chloride transport, a reliable indicator to correlate with improvement in clinical outcomes. By contrast, EMA did not deem preclinical data sufficient to expand the label of CFTR modulators without confirmatory clinical data.ConclusionsRegulators played an important role in fostering the development and approval of CFTR modulators. However, differences were found between FDA and EMA in the way of reviewing and licensing CFTR modulators, which extended beyond semantics affecting patients’ eligibility and access: FDA’s approach was more mechanistic/biology-driven while the EMA’s one was more oriented by clinical evidence. This might refer to the connection between the EMA and the Member States, which tends to base decisions on pricing and reimbursement on clinical data rather than pre-clinical ones. Here we have proposed a two-step personalized-based model to merge the ethical commitment of ensuring larger access to all potential eligible patients (including those harboring very rare mutations) with the one of ensuring access to clinically assessed and effective medicines through Real World Data.

The Road to Achieving the European Commission's Chemicals Strategy for Nanomaterial Sustainability-A PATROLS Perspective on New Approach Methodologies.

The European Green Deal outlines ambitions to build a more sustainable, climate neutral, and circular economy by 2050. To achieve this, the European Commission has published the Chemicals Strategy for Sustainability: Towards a Toxic-Free Environment, which provides targets for innovation to better protect human and environmental health, including challenges posed by hazardous chemicals and animal testing. The European project PATROLS (Physiologically Anchored Tools for Realistic nanOmateriaL hazard aSsessment) has addressed multiple aspects of the Chemicals Strategy for Sustainability by establishing a battery of new approach methodologies, including physiologically anchored human and environmental hazard assessment tools to evaluate the safety of engineered nanomaterials. PATROLS has delivered and improved innovative tools to support regulatory decision-making processes. These tools also support the need for reducing regulated vertebrate animal testing; when used at an early stage of the innovation pipeline, the PATROLS tools facilitate the safe and sustainable development of new nano-enabled products before they reach the market.

The Rise of Three Rs Centres and Platforms in Europe.

Public awareness and discussion about animal experiments and replacement methods has greatly increased in recent years. The term 'the Three Rs', which stands for the Replacement, Reduction and Refinement of animal experiments, is inseparably linked in this context. A common goal within the Three Rs scientific community is to develop predictive non-animal models and to better integrate all available data from in vitro, in silico and omics technologies into regulatory decision-making processes regarding, for example, the toxicity of chemicals, drugs or food ingredients. In addition, it is a general concern to implement (human) non-animal methods in basic research. Toward these efforts, there has been an ever-increasing number of Three Rs centres and platforms established over recent years - not only to develop novel methods, but also to disseminate knowledge and help to implement the Three Rs principles in policies and education. The adoption of Directive 2010/63/EU on the protection of animals used for scientific purposes gave a strong impetus to the creation of Three Rs initiatives, in the form of centres and platforms. As the first of a series of papers, this article gives an overview of the European Three Rs centres and platforms, and their historical development. The subsequent articles, to be published over the course of ATLA's 50th Anniversary year, will summarise the current focus and tasks as well as the future and the plans of the Three Rs centres and platforms. The Three Rs centres and platforms are very important points of contact and play an immense role in their respective countries as 'on the ground' facilitators of Directive 2010/63/EU. They are also invaluable for the widespread dissemination of information and for promoting implementation of the Three Rs in general.

Digital Health Technologies for Medical Devices – Real World Evidence Collection – Challenges and Solutions Towards Clinical Evidence

The need for sufficient clinical evidence and the collection of real-world evidence (RWE) is at the forefront of medical device and drug regulations, however, the collection of clinical data can be a time consuming and costly process. The advancement of Digital Health Technologies (DHTs) is transforming the way health data can be collected, analysed, and shared, presenting an opportunity for the implementation of DHTs in clinical research to aid with obtaining clinical evidence, particularly RWE. DHTs can provide a more efficient and timely way of collecting numerous types of clinical data (e.g., physiological, and behavioural data) and can be beneficial with regards to participant recruitment, data management and cost reduction. Recent guidelines and regulations on the use of RWE within regulatory decision-making processes opens the door for the wider implementation of DHTs. However, challenges and concerns remain regarding the use of DHT (such as data security and privacy). Nevertheless, the implementation of DHT in clinical research presents a promising opportunity for providing meaningful and patient-centred data to aid with regulatory decisions.

Integrating Real-World Evidence in the Regulatory Decision-Making Process: A Systematic Analysis of Experiences in the US, EU, and China Using a Logic Model.

Real world evidence (RWE) and real-world data (RWD) are drawing ever-increasing attention in the pharmaceutical industry and drug regulatory authorities (DRAs) all over the world due to their paramount role in supporting drug development and regulatory decision making. However, there is little systematic documentary analysis about how RWE was integrated for the use by the DRAs in evaluating new treatment approaches and monitoring post-market safety. This study aimed to analyze and discuss the integration of RWE into regulatory decision-making process from the perspective of DRAs. Different development strategies to develop and adopt RWE by the DRAs in the US, Europe, and China were reviewed and compared, and the challenges encountered were discussed. It was found that different strategies on development of RWE were applied by FDA, EMA, and NMPA. The extent to which RWE was adopted in China was relatively limited compared to that in the US and EU, which was highly related to the national pharmaceutical environment and development stages. A better understanding of the overall goals, inputs, activities, outputs, and outcomes in developing RWE will help inform actions to harness RWD and leverage RWE for better health care decisions.

Contents of US Food and Drug Administration Refuse-to-File Letters for New Drug Applications and Efficacy Supplements and Their Public Disclosure by Applicants

Before reviewing drug applications, the US Food and Drug Administration (FDA) conducts "filing reviews" to assess whether they are complete enough for full review. If the applications are incomplete, the FDA issues refuse-to-file (RTF) letters identifying deficiencies. The FDA does not make these RTF letters public at the time of issuance. Why the FDA issues RTF letters and how often the letters and their contents are made publicly available are unknown. To quantitatively analyze the FDA's reasons for issuing RTF letters and assess the public transparency of RTF letters and their contents. This cross-sectional study analyzes RTF letters issued in response to new drug applications and efficacy supplements (applications for new indications or patient populations for already approved drugs) submitted to the FDA between January 1, 2008, and December 31, 2017. Statistical analysis was conducted in July 2019. Two types of information were extracted and cataloged from RTF letters: (1) the reasons why the FDA refused to file applications and (2) the FDA comments that, while not a basis for RTF letters, conveyed important information to applicants. The extent to which applicants publicly disclosed the FDA's refusal reasons were also assessed. The study included 103 RTF letters containing a total of 644 identified FDA refusal reasons. Among the 2475 applications that the FDA received during the study time frame, 98 (4.0%) received RTF letters. Overall, 84.5% (544 of 644) of the refusal reasons were for scientific deficiencies; most reasons were related to drug efficacy and safety (196 [30.4%]) and drug quality (125 [19.4%]). The remaining 15.5% of refusal reasons (100 of 644) were for application organization deficiencies or legal issues. A total of 26.2% of the RTF letters (27 of 103) identified presubmission advice from the FDA that applicants did not follow; the most frequently ignored advice was related to clinical trial design (33.3% [9 of 27]), followed by product chemistry and manufacturing (25.9% [7 of 27]). Applicants publicly disclosed the existence of 16 of 103 RTF letters (15.5%); however, only 5.4% of applicant-disclosed reasons (35 of 644) matched the refusal reasons that the FDA had provided in the RTF letters. This cross-sectional study found that the FDA refused to file applications for substantive reasons related to quality, safety, and efficacy, and applicants' disclosure of those reasons was incomplete. This work sheds light on the FDA's regulatory decision-making processes and the RTF reasons that could delay availability of therapies to patients.

Environmental epidemiology and risk assessment: Exploring a path to increased confidence in public health decision-making

Throughout history, environmental epidemiology has proven crucial to identify certain threats to human health and to provide a basis for the development of life-saving public health policies. However, epidemiologists are facing challenges when studying tenuous threats such as environmental exposure to chemicals, whose association with adverse health effects may be difficult to characterize. As a result, epidemiological data can seldom be fully leveraged for quantitative risk assessment and decision-making. Despite two decades of efforts to improve a more systematic integration of human data to evaluate human health risks, assessors still heavily rely on animal data to do so, while epidemiology plays more of a secondary role. Although the need for more and better collaboration between risk assessors and epidemiologists is widely recognized, both fields tend to remain siloed. In 2017, the Health and Environmental Sciences Institute initiated a project engaging the epidemiology, exposure science, and regulatory communities with tripartite representation from regulators, industry, and academia in a dialogue on the use of environmental epidemiology for regulatory decision-making. Several focus groups attended by epidemiology, exposure science, and risk assessment experts were organized to explore incentives and barriers to collaboration, to ultimately bridge the gap between the various disciplines, and to realize the full potential of epidemiological data in risk assessment. Various ideas that have emerged from these meetings could help ensure the better integration of epidemiological data in quantitative risk assessment and contribute to building confidence in a robust and science-based regulatory decision-making process.

Intellectual Property, Competition, and Regulatory Policies: A Case of Bt Cotton Seed Industry in India

This paper explores the relationship between intellectual property rights, competition laws and regulatory policies in case of Bt cotton seed industry in India. Using timeline analysis, the paper tracks the events to understand the temporal scope and inter-temporal dependences of the events. This study illustrates that interaction of business model and regulatory policies resulted in anti-competitiveness in the industry. The study shows multiple regulatory enforcements due to the lack of clarity and foresight. Lack of clear legislative framework, specific criteria for assessment, transparency and public involvement in the regulatory decision-making process has led to these multiple enforcements.

Mass balance approach to assess the impact of cadmium decrease in mineral phosphate fertilizers on health risk: The case-study of French agricultural soils

Cadmium is a ubiquitous and highly toxic contaminant that can cause serious adverse effects. The European Food Safety Authority (EFSA) and the French Agency for Food, Environmental and Occupational Health & Safety (ANSES) have shown that the risk related to food contamination by cadmium cannot be ruled out in Europe and France. Fertilizing material is one of the main sources of cadmium contamination in the food chain on which regulators can play to reduce cadmium exposure in the population. The aim of this work was to develop a mass-balance approach integrating the various environmental sources of cadmium to estimate the effects of a decrease in cadmium concentrations in crop fertilizers on dietary exposure and on the health risk. This approach led to a predictive model that can be used as a decision-making tool. Representative and protective fertilization scenarios associated with controlled cadmium levels in mineral phosphate fertilizers were simulated and converted into cadmium fluxes. Cadmium inputs from industrial mineral phosphate fertilizers were then compared with cadmium brought by the application of manure, sewage sludge and farm anaerobic digest, at the levels typical of French agricultural practices. Regardless of the fertilizer and scenario used, a flux lower than 2 g Cd.ha−1.year−1 reduces both the accumulation in soils and the transfer of cadmium in the food chain. It corresponds to a cadmium content of 20 mg.kg P2O5−1 or less in mineral phosphate fertilizers. Modelling the transfer of cadmium from the soil to consumed food made it possible to propose cadmium limits in fertilizers applied in France. In a global context of ecological transition to promote human health, this research will help risk managers and public authorities in the regulatory decision-making process for the reduction of environmental cadmium contamination and human exposure.