Download full-text


Available from: Linda S Birnbaum,
15 Reads
  • Source
    • "Also, there is a need to integrate data from multiple evidence streams (human, animal, and " other relevant data " including mechanistic or in vitro studies) in order to reach conclusions regarding potential health effects from exposure to substances in our environment. The National Toxicology Program (NTP) Office of Health Assessment and Translation (OHAT) conducts literaturebased evaluations to assess the evidence that environ mental chemicals, physical substances , or mixtures (collectively referred to as " substances " ) cause adverse health effects and provides opinions on whether these substances may be of concern given levels of current human exposure (Bucher et al. 2011). Building on a history of rigorous and objective scientific review, OHAT has been working to incorporate systematic-review procedures in its evaluations since 2011 through a process that has included adoption of current practice, as well as methods develop ment (Birnbaum et al. 2013; NTP 2012a, 2012b, 2013e). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Systematic review methodologies provide objectivity and transparency to the process of collecting and synthesizing scientific evidence for reaching conclusions on specific research questions. There is increasing interest in applying these procedures to address environmental health questions. To develop a systematic review framework to address environmental health questions by extending approaches developed for clinical medicine to handle the breadth of data relevant to environmental health sciences (e.g., human, animal, and mechanistic studies). The Office of Health Assessment and Translation (OHAT) adapted guidance from systematic-review authorities and sought advice during development of the OHAT Approach through consultation with technical experts in systematic review and human health assessments as well as scientific advisory groups and the public. The method was refined by considering expert and public comments and through application to case studies. Presented here is a 7-step framework for systematic review and evidence integration for reaching hazard identification conclusions: problem formulation and protocol development, search for and select studies for inclusion, extract data from studies, assess the quality or risk of bias of individual studies, rate the confidence in the body of evidence, translate the confidence ratings into levels of evidence, and integrate the information from different evidence streams (human, animal, and "other relevant data" including mechanistic or in vitro studies) to develop hazard identification conclusions. The principles of systematic review can be successfully applied to environmental health questions to provide greater objectivity and transparency to the process of developing conclusions.
    Environmental Health Perspectives 04/2014; 122(7). DOI:10.1289/ehp.1307972 · 7.98 Impact Factor
  • Source
    • "Although this case was resolved under existing FOIA mechanisms, in the wake of this litigation there has been concern that the IQA does not provide outside parties sufficient access to the data for studies that underlie regulatory decisions made by U.S. government agencies. There is increasing interest in improving the methods by which chemical and pesticide hazards and risks are evaluated not only by government but also by independent scien tists (Bucher et al. 2011; Woodruff et al. 2011). This interest has spurred increased demand for transparency and disclosure of the data used by the U.S. EPA to make evalua tions that support regulatory decisions for chemicals and pesticides. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Background: A database for studies used for U.S. Environmental Protection Agency (EPA) pesticide and chemical reviews would be an excellent resource for increasing transparency and improving systematic assessments of pesticides and chemicals. There is increased demand for disclosure of raw data from studies used by the U.S. EPA in these reviews. Objectives: Because the Information Quality Act (IQA) of 2001 provides an avenue for request of raw data, we reviewed all IQA requests to the U.S. EPA in 2002–2012 and the U.S. EPA’s responses. We identified other mechanisms to access such data: public access databases, the Freedom of Information Act (FOIA), and reanalysis by a third party. Discussion: Only two IQA requests to the U.S. EPA were for raw data. Both of these were fulfilled under FOIA, not the IQA. Barriers to the U.S. EPA’s proactive collection of all such data include costs to the U.S. EPA and researchers, significant time burdens for researchers, and major regulatory delays. The U.S. EPA regulatory authority in this area is weak, especially for research conducted in the past, not funded by the U.S. government, and/or conducted abroad. The U.S. EPA is also constrained by industry confidential business information (CBI) claims for regulatory testing data under U.S. chemical and pesticide laws. The National Institutes of Health Clinical Trials database systematically collects statistical data about clinical trials but not raw data; this database may be a model for data from studies of chemicals and pesticides. Conclusions: A database that registers studies and obtains systematic sets of parameters and results would be more feasible than a system that attempts to make all raw data available proactively. Such a proposal would not obviate rights under the IQA to obtain raw data at a later point.
    Environmental Health Perspectives 12/2012; 121(2). DOI:10.1289/ehp.1206101 · 7.98 Impact Factor
  • Source
    • "Several large, new health research efforts are developing approaches that use new technologies to modernize toxicity testing. Examples include Tox21 (Collins et al. 2008; Kavlock et al. 2009; U.S. EPA 2012a, 2012b), the National Institutes of Health's (NIH) National Institute of Environmental Health Sciences (NIEHS 2011), the National Toxicology Program (a multiagency effort headquartered at the NIEHS) (Bucher et al. 2011), the U.S. EPA's Chemical Safety for Sustainability research program (see Appendix 1), ToxCast™ (Dix et al. 2007; Judson et al. 2010a), and the Safety Evaluations Ultimately Replacing Animal Testing (SEURAT) research program (European Commission and European Cosmetics Association 2011). Of particular note is that the Tox21 program alone will gener ate new high throughput data on 10,000 chemicals, using > 100 assays, over the next few years. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Background: Over the past 20 years, knowledge of the genome and its function has increased dramatically, but risk assessment methodologies using such knowledge have not advanced accordingly. Objective: This commentary describes a collaborative effort among several federal and state agencies to advance the next generation of risk assessment. The objective of the NexGen program is to begin to incorporate recent progress in molecular and systems biology into risk assessment practice. The ultimate success of this program will be based on the incorporation of new practices that facilitate faster, cheaper, and/or more accurate assessments of public health risks. Methods: We are developing prototype risk assessments that compare the results of traditional, data-rich risk assessments with insights gained from new types of molecular and systems biology data. In this manner, new approaches can be validated, traditional approaches improved, and the value of different types of new scientific information better understood. Discussion and Conclusions: We anticipate that these new approaches will have a variety of applications, such as assessment of new and existing chemicals in commerce and the design of chemical products and processes that reduce or eliminate the use or generation of hazardous substances. Additionally, results of the effort are likely to spur further research and test methods development. Full implementation of new approaches is likely to take 10–20 years.
    Environmental Health Perspectives 08/2012; 120(11). DOI:10.1289/ehp.1104870 · 7.98 Impact Factor
Show more