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Federal Register / Vol. 86, No. 3 / Wednesday, January 6, 2021 / Rules and Regulations
should pursue an incremental approach to maximizing transparency in the science that it relies upon by focusing the final rule requirements on doseresponse data and, in particular, only those studies that are integral to characterizing dose-response relationships e.g., identifying candidate PODs. The EPA considered commenters assertions that the scope of the 2018 proposed rule would be so broad as to make implementation infeasible. The 2018 proposed definition of dose-response data and models would apply to dose-response data and models used to characterize the quantitative relationship between the amount of dose or exposure to a pollutant, contaminant, or substance and the magnitude of a predicted health or environmental impact. This relationship of the dose-response data to the magnitude of a predicted health or environmental impact would require the consideration of an array of studies beyond those that characterize doseresponse relationships, including, for example, studies that inform the doseresponse modeling e.g., benchmark response selection; studies that identify data for toxicokinetic adjustments that inform calculation of a humanequivalent point of departure POD;
and studies that inform the selection of uncertainty factors. The number of studies that are used to establish the relationship between dose-response data and models and the magnitude of a predicted health or environmental impact can potentially be very large.
This may make implementing the rule, as proposed, more challenging for at least some significant regulatory actions and influential scientific information.
While transparency in EPA decisionmaking is the purpose of this action, the EPA prefers an incremental approach.
Rather than having this final rule apply to all the studies that support the assessment of the relationship of a dose or exposure of a pollutant, contaminant, or substance to the magnitude of a predicted health or environmental impact, the EPA is balancing transparency and feasibility by focusing on those studies that describe the quantitative relationship between the dose or exposure of a pollutant, contaminant, or substance and an effect.
Specifically, the scope of dose-response data in this final rule is those studies consisting of the data integral to characterizing dose-response relationships. In some instances, this group will consist of a handful of studies. In other instances, where there are multiple toxicity endpoints, there may be more studies that are crucial to
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characterizing dose-response relationships. In some other cases, there may be a large number of studies that are used to characterize a dose-response relationship e.g., where the doseresponse is based on a meta-regression of epidemiology studies. However, not all of these studies would be considered pivotal science see Section III.C.6 of this preamble for the definition of pivotal science.
Based on comments and other considerations, the EPA is concentrating its efforts in the final rule to increase transparency on dose-response data, as the dose-response data are discrete and the dose-response assessment is a welldefined and impactful step in the quantitative assessment of risk. This final rule provides an important step in furthering progress toward maximizing transparency and will provide insight for future statute-specific requirements.
Consistent with this targeted focus, the EPA is replacing the proposed definition of dose-response data and models at 40 CFR 30.2 with a definition of dose-response data see Section III.C of this preamble.
C. Definitions The 2018 proposed rule included proposed definitions for dose-response data and models, pivotal regulatory science, regulatory decisions, regulatory science, and research data. Some commenters stated that several of the proposed definitions were unclear, including some that seemed to overlap e.g., pivotal regulatory science and regulatory science.
Some commenters also stated that certain terms used in the proposed regulatory requirements were not clear and should be defined.
In response to these comments on the 2018 proposed rule, the EPA proposed in the 2020 SNPRM definitions for capable of being substantially reproduced, data, independent evaluation, models, publicly available, and reanalyze. In the 2020
SNPRM, the EPA also proposed a definition of influential scientific information to comport with the proposed expansion of the applicability of the rulemaking to influential scientific information.
Based on a consideration of the public comments on both the 2018 proposed rule and the 2020 SNPRM, the EPA is finalizing the definitions at 40 CFR 30.2
as follows.
1. Capable of being substantially reproduced, independent validation, and reanalyze. In the 2018 proposed rule, the EPA used the term replicate in the proposed regulatory text at 40
CFR 30.5 but did not define it at 40 CFR

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30.2. Proposed 40 CFR 30.5 read, in pertinent part, information is considered publicly available in a manner sufficient for independent validation when it includes the information necessary for the public to understand, assess, and replicate findings . . . . Some commenters contended that the EPA was not clear about what it meant by the term replicate and interpreted the term replicate in several different ways.
For example, some commenters asserted that the EPA used the term replicate but actually meant reanalyze. The EPA finds that these comments have merit and is clarifying that the intent of the term in the proposed regulatory text at 40 CFR 30.5 was reanalyze rather than replicate. In the 2020 SNPRM, the EPA proposed using the term reanalyze instead of replicate and proposed at 40 CFR 30.2 a definition for reanalyze. Given that proposed 40
CFR 30.5 also included the term independent validation and that this term directly relates to replicate, the EPA also proposed a definition at 40
CFR 30.2 for this term. The proposed definition of independent validation included the term capable of being substantially reproduced. The EPA
also defined this term because it was an important component of the definition of independent validation.
While commenters generally supported the inclusion of the proposed definitions for capable of being substantially reproduced, independent validation, and reanalyze, some commenters addressed aspects of the proposed definitions and suggested modifications.
One commenter suggested replacing the term validation with verification because they asserted the term validation has specific meanings in the context of assay development and in the context of model development. The EPA understands that the term validation is used differently in some scientific disciplines than the EPA has defined it. However, for the purposes of this rule, the EPA has defined validation in terms of independent reanalysis.
Another commenter contended that the proposed definition of independent validation was inconsistent with the remainder of the proposal because it restricts the concept of independent validation to subject matter experts who have not contributed to the development of the study, rather than the public as was the stated intent of the rule. Because this rule is about scientific data, the EPA finds it unlikely that without the necessary expertise, one could reasonably reanalyze the doseresponse data underlying pivotal
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