The Federal Insecticide, Fungicide and Rodenticide Act (FIFRA) broadly regulates the manufacture, sale and use of pesticides in the United States. FIFRA requires applicants who register, re-register or amend a pesticide registration to submit or cite data in support of the application. These data requirements are designed to ensure that the EPA has sufficient information to determine whether a pesticide is safe and effective for its proposed uses. Applicants can satisfy FIFRA’s data requirements by submitting their own data, citing to publicly available data or citing to data privately developed by other companies. Because citing another company’s data may have huge financial implications, applicants must first carefully consider their data compensation obligations and options under FIFRA before citing such data.
The registration, re-registration or amended registration of a pesticide may require a substantial (and expensive) amount of scientific data. Recognizing this possibility, FIFRA gives data submitters certain rights for the data they submit to the EPA. First, a data submitter is entitled to a 10-year period of “exclusive use” of its data. During the exclusive-use period, the data submitter’s written permission is required before anyone else can cite its data. You can read more about FIFRA’s exclusive-use protection here. Second, a data submitter is also entitled to compensation rights for 15 years for certain data that it submits. This 15-year “data compensation” period starts running from the date the applicant submits data to support or maintain a pesticide registration.
Unlike exclusive-use data, an applicant does not need written permission before citing to data covered only by FIFRA’s data compensation requirements. Instead, an applicant must: (1) offer to compensate the data owner for the use of its data; and (2) certify to the EPA that it has made such an offer (the necessary EPA certification can be found in EPA Form 8570-34). An applicant’s notice to the data owner must include the name of the proposed pesticide product and a list of the product’s active ingredients. An applicant does not need to offer to pay for data found in public literature articles, government-generated studies, and data for which all periods of exclusive use and compensation have expired. However, when a study is developed jointly with government and private resources, the private component may be compensable under certain circumstances.
If an applicant chooses to cite to another company’s compensable data, that applicant has three options:
- Cite-all method – applicant cites to all the data in the EPA’s files that is pertinent to the EPA’s consideration of the requested registration action. See 40 CFR 152.86 & 40 CFR 152.95.
- Selective method – applicant lists the specific data requirements that apply to its product, its active ingredients and its use patterns and then selectively cites to individual studies, including the applicant’s own data. See 40 CFR 152.90(b).
- Selective cite-all method – applicant cites to all data in the EPA’s files to satisfy specific data requirements. See 40 CFR 152.90(b).
Each approach comes with benefits and drawbacks.
Under the cite-all method, applicants must submit EPA Form 8570-34 “Certification with Respect to Citation of Data” and include a completed list of companies that the applicant has sent offers of compensation (using EPA Form 8570-35 “Data Matrix”). The cite-all method can be a very convenient option for both the applicant and the EPA because the applicant does not need to determine each item of data it must cite to, and the EPA does not need to determine whether the applicant omitted any other pieces of data. However, the convenience of the cite-all method can have major financial implications. By citing to all data in the EPA’s possession that supports the applicant’s registration, the applicant may inadvertently be citing (and paying for) unnecessary and redundant data. Accordingly, when using the cite-all method, it is important for an applicant to first quantify the scope and amount of expected data compensation liability. An applicant should also consider the expected profitability of its application. It would be foolhardy to incur hundreds of thousands (or millions) of dollars in data compensation liability when the applicant’s registration is only expected to generate marginal profits.
Under the selective method, applicants list the specific data requirements that apply to their product (i.e., its active ingredients and/or use patterns). The applicant must also demonstrate compliance with the data requirements by submitting the actual studies, citing individual studies or demonstrating that no study has been previously submitted to the EPA (i.e., a “data gap”). The selective method allows applicants to limit their data compensation liability, but it comes at the expense of time and convenience. Applicants will spend more time researching and determining what data must be “selected” for citation, while the EPA’s review is typically lengthened because it must determine whether the applicant has omitted any necessary data.
Finally, an applicant can choose the selective cite-all method, whereby the applicant cites all data in the EPA’s files to satisfy specific data requirements. Although the selective cite-all method is still typically slower than the cite-all method, this approach can be advantageous as it allows an applicant to better ascertain and limit its data compensation liability while also speeding the review process for the specific data requirements that the applicant cites.
The method an applicant chooses can have major financial implications because of how FIFRA addresses data compensation disputes. Because an applicant does not need an original data submitter’s permission before citing to data (unless the data is within the 10-year exclusive use period), an applicant may not know how much the original data submitter will demand for the cited data and how much the applicant will ultimately have to pay to the original data submitter for the cited data. FIFRA leaves the resolution of data compensation disputes to the parties — who can either reach a mutual agreement as to the amount of compensation or have the issue resolved by binding arbitration. Ignoring potential data compensation liability can be an expensive mistake for applicants.