Opportunity Information: Apply for RFA FD 14 011
Apply for RFA FD 14 011
- The Food Drug Administration in the health science and technology and other research and development sector is offering a public funding opportunity titled "Pharmacometric Modeling and Simulation for Generic Drugs Evaluation" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.103 Food and Drug AdministrationResearch.
- This funding opportunity was created on Apr 1, 2014 and posted on Mar 28, 2014.
- Applicants must submit their applications by Jun 2, 2014. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The funding agency has allocated a total of $1,250,000.00 to eligible and selected applicants.
- Each selected applicant is eligible to receive up to $250,000.00 in funding.
- The number of recipients for this funding is limited to 5 candidate(s).
- Eligible applicants include: Independent school districts For profit organizations other than small businesses Native American tribal organizations (other than Federally recognized tribal governments) City or township governments Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education Private institutions of higher education Special district governments Native American tribal governments (Federally recognized) County governments Public housing authorities/Indian housing authorities Public and State controlled institutions of higher education State governments Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education Small businesses Others (see text field entitled Additional Information on Eligibility for clarification).
- Foreign Institutions
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Opportunity Summary:
The Pharmacometric Modeling and Simulation for Generic Drugs Evaluation opportunity (RFA FD 14 011) is a Food and Drug Administration cooperative agreement grant created under the Fiscal Year 2014 GDUFA Regulatory Research program. Its central purpose is to strengthen how the FDA evaluates generic drugs by expanding the use of computational pharmacometrics (modeling and simulation based on pharmacokinetics and pharmacodynamics) in the ANDA review process. The program is built around the idea that modern generic drug assessment should rely not only on traditional bioequivalence studies, but also on quantitative tools that can predict clinical performance, clarify risk, and help tailor regulatory standards to the needs of specific drugs.
The funding announcement targets development of quantitative models and simulation methods in three major areas. First, it seeks population PK/PD models that link dose, exposure, efficacy, and toxicity for narrow therapeutic index (NTI) drugs. The practical regulatory goal is twofold: to support a more defensible approach for determining whether a drug should be considered NTI, and to inform what bioequivalence standards should look like for NTI products where small exposure differences can matter clinically. The intention is to identify drugs whose clinical use profile demands tighter control of product quality and equivalence attributes, and to provide model-based evidence that can guide those decisions.
Second, the opportunity focuses on pharmacometric approaches for evaluating generic substitutability and supporting postmarketing risk assessment. This area is meant to address real-world concerns that can emerge after approval, such as reports of adverse events, perceived loss of effect, or complaints tied to switching between products. The FDA is looking for modeling frameworks that can include clinical trial simulation as well as clinical use or substitution simulation, giving the Office of Generic Drugs tools to interpret postmarket signals in a more quantitative and mechanistic way. The announcement notes example drug classes where substitutability questions are common, including antiepileptic drugs, ADHD medications, and antidepressants, while leaving the door open to other appropriate candidates.
Third, the grant calls for modeling and simulation work to evaluate partial AUC measures as bioequivalence criteria. Traditional BE metrics focus on overall exposure (AUC) and peak concentration (Cmax), but for certain drugs the shape of the concentration-time curve, or exposure within a specific time window, may be more closely tied to therapeutic effect or safety. The FDA is asking applicants to develop tools that help determine when partial AUCs are warranted and, when they are, which partial AUC intervals are most appropriate for demonstrating bioequivalence. The broader regulatory objective is to identify products that require a higher degree of pharmacokinetic profile similarity to ensure therapeutic equivalence.
Structurally, the announcement is divided into three corresponding subtopics, and applicants interested in more than one area are instructed to submit separate proposals for each subtopic. Awards are issued as cooperative agreements, which generally implies substantial FDA involvement during the project (for example, coordination on aims, data interpretation, or alignment with regulatory questions). The FDA expected to make about five awards, with total estimated program funding of $1.25 million. Individual awards were anticipated to fall between $150,000 and $250,000.
Key administrative details include the posting timeline (posted March 28, 2014; closing date June 2, 2014; archived July 2, 2014) and the CFDA listing under 93.103 (FDA research). Cost sharing was not required. Eligibility was broad, covering many domestic entities such as universities, nonprofits, small businesses, certain for-profit organizations, and various government bodies, and the announcement also referenced foreign institutions in the eligibility information. Overall, the grant is best understood as an FDA effort to make generic drug evaluation more predictive and clinically relevant by embedding pharmacometric modeling into decisions about NTI classification, switching and postmarket safety interpretation, and more nuanced bioequivalence metrics like partial AUC.
FAQs: Pharmacometric Modeling and Simulation for Generic Drugs Evaluation (RFA FD 14 011)
What is the Pharmacometric Modeling and Simulation for Generic Drugs Evaluation opportunity (RFA FD 14 011)?
It is an FDA cooperative agreement grant created under the Fiscal Year 2014 GDUFA Regulatory Research program. The opportunity focuses on expanding the use of computational pharmacometrics (modeling and simulation based on pharmacokinetics and pharmacodynamics) to strengthen how the FDA evaluates generic drugs during the ANDA review process.
What is the main purpose of this grant?
The central purpose is to improve generic drug evaluation by embedding quantitative modeling and simulation approaches alongside traditional bioequivalence studies. The intent is to support more predictive and clinically relevant regulatory decisions by using tools that can forecast clinical performance, clarify risk, and help tailor regulatory standards to specific drugs.
Which FDA program is this grant associated with?
This opportunity was created under the Fiscal Year 2014 GDUFA Regulatory Research program.
What type of award mechanism is used?
Awards are issued as cooperative agreements. This structure generally implies substantial FDA involvement during the project, such as coordination on project aims, interpretation of results, and alignment of the work with FDA regulatory questions.
How does the grant view the role of traditional bioequivalence studies?
The grant is built around the idea that modern generic drug assessment should rely not only on traditional bioequivalence studies, but also on quantitative pharmacometric tools that can better predict clinical performance and inform risk-based regulatory standards.
What are the major technical areas (subtopics) supported by the funding announcement?
The announcement targets development of quantitative models and simulation methods in three major areas: (1) population PK/PD models for narrow therapeutic index (NTI) drugs, (2) pharmacometric approaches for evaluating generic substitutability and postmarketing risk assessment, and (3) modeling and simulation to evaluate partial AUC measures as bioequivalence criteria.
What is Subtopic 1 focused on?
Subtopic 1 seeks population PK/PD models that link dose, exposure, efficacy, and toxicity for narrow therapeutic index (NTI) drugs.
What regulatory goals does the NTI (narrow therapeutic index) modeling work support?
The practical regulatory goal is twofold: to support a more defensible approach for determining whether a drug should be considered NTI, and to inform what bioequivalence standards should look like for NTI products where small exposure differences can matter clinically.
Why is the FDA interested in identifying NTI drugs through modeling?
The intention is to identify drugs whose clinical use profile demands tighter control of product quality and equivalence attributes, and to provide model-based evidence that can guide decisions about NTI classification and related bioequivalence standards.
What is Subtopic 2 focused on?
Subtopic 2 focuses on pharmacometric approaches for evaluating generic substitutability and supporting postmarketing risk assessment.
What kinds of real-world concerns is Subtopic 2 intended to address?
This area is meant to address concerns that can emerge after approval, including reports of adverse events, perceived loss of effect, or complaints tied to switching between products.
What types of simulations are mentioned for substitutability and postmarketing risk assessment?
The FDA is looking for modeling frameworks that can include clinical trial simulation as well as clinical use or substitution simulation, providing tools to interpret postmarket signals in a more quantitative and mechanistic way.
Are specific drug classes highlighted for substitutability questions?
Yes. The announcement notes example drug classes where substitutability questions are common, including antiepileptic drugs, ADHD medications, and antidepressants, while also leaving the door open to other appropriate candidates.
What is Subtopic 3 focused on?
Subtopic 3 calls for modeling and simulation work to evaluate partial AUC measures as bioequivalence criteria.
How do partial AUC measures relate to traditional bioequivalence metrics?
Traditional bioequivalence metrics commonly focus on overall exposure (AUC) and peak concentration (Cmax). Partial AUC measures evaluate exposure within a specific time window of the concentration-time curve, which may be more closely tied to therapeutic effect or safety for certain drugs.
What is the FDA asking applicants to do regarding partial AUC?
The FDA is asking applicants to develop tools that help determine when partial AUCs are warranted and, when they are, which partial AUC intervals are most appropriate for demonstrating bioequivalence.
What is the broader regulatory objective of the partial AUC work?
The broader objective is to identify products that require a higher degree of pharmacokinetic profile similarity to ensure therapeutic equivalence.
Can an applicant apply to more than one subtopic?
Yes. However, applicants interested in more than one area are instructed to submit separate proposals for each subtopic.
How many awards did the FDA expect to make?
The FDA expected to make about five awards.
What was the estimated total program funding?
Total estimated program funding was $1.25 million.
What was the anticipated award size for individual projects?
Individual awards were anticipated to fall between $150,000 and $250,000.
Is cost sharing required?
No. Cost sharing was not required.
What was the timeline for this funding announcement?
The opportunity was posted on March 28, 2014, had a closing date of June 2, 2014, and was archived on July 2, 2014.
What CFDA number is associated with this opportunity?
The CFDA listing was under 93.103 (FDA research).
Who was eligible to apply?
Eligibility was broad and covered many domestic entities such as universities, nonprofits, small businesses, certain for-profit organizations, and various government bodies. The eligibility information also referenced foreign institutions.
What is the intended impact of the grant on ANDA review?
The goal is to expand the use of pharmacometric modeling and simulation in the ANDA review process so FDA decisions can be more quantitative, predictive, and closely connected to clinical performance and risk.
What are the key decision areas the FDA aimed to strengthen with pharmacometrics through this grant?
The grant is framed as an effort to strengthen FDA decision-making in three areas: NTI classification and NTI bioequivalence standards, interpretation of switching/substitutability and postmarket safety signals, and selection of more nuanced bioequivalence metrics such as partial AUC when appropriate.
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