Office of Generic Drugs FY 2015 Regulatory Science Research Report
- Nanotechnology: Physiochemical Characterization of Nano-Sized Drug Products
- Ophthalmic Products
- Complex Mixtures and Peptides
- Long-Acting Injectable Formulations
- Postmarket: Evaluation of Generic Drug Product Substitution
- Locally-Acting Orally-Inhaled and Nasal Drug Products
- Transdermal Drug Products
- Topical Dermatological Drug Products
- Locally-Acting Gastrointestinal Drugs
- Modified Release Drug Products: Therapeutic Equivalence between Brand-Name Drugs and Generics
- Narrow Therapeutic Index Drugs
- Physiologically-Based Absorption and Pharmacokinetic Models
- Pharmacokinetic/Pharmacodynamic Models and Pharmacometrics
- Advances in Predictive Dissolution and Physiological Models of Drug Absorption
- Database and Knowledge Management
- Postmarket: Data Analysis for Generic Drugs
- Postmarket: Patient Substitution Studies
- Nano Drug Products: Clinical Pharmacology and In Vivo Correlation
As part of the implementation of GDUFA, the U.S. Food and Drug Administration (FDA) committed to employ regulatory science initiatives for generic drugs. In 2014, the Office of Generic Drugs (OGD) established a new sub-office, the Office of Research and Standards (ORS) to lead the implementation of the regulatory science commitments and to translate these research results into standards for safe, effective, and equivalent generic drugs. Each year under GDUFA, OGD organizes a public input process to help establish the GDUFA research priorities. This report describes the divisions within ORS and updates 2014 activities and progress in each of the priority areas.
OGD’s GDUFA research supports access to generic drugs in all product categories. We conduct research to develop new or more efficient bioequivalence methods for product categories that have little or no generic drug availability. Focused research programs for inhalation, nasal, topical dermatological, ophthalmic, liposomal, and sustained release parental products lead to new individual product guidances and inform pre-ANDA meetings and controlled correspondence responses.
GDUFA research builds confidence in generic substitution for the 86% of U.S. prescriptions that are filled by generic drugs. Pre-approval research leads to risk-based standards for generics evaluation, and post-approval studies in patients provide solid evidence for successful generic substitution. Monitoring of approved products through analysis of adverse event reports and medical records databases helps detect unexpected events sooner and provides a quantitative context for interpreting individual adverse events. The scientific foundations of our standards and monitoring are a basis for public confidence in generic drugs.
GDUFA research also supports new tools for generic drug development and review. These range from simulation tools to predict drug absorption and advanced analytical methods for product characterization to in vitro methods that predict in vivo performance. These tools give the generic industry additional means to accelerate product development and allow FDA to better evaluate proposed products.
Having the opportunity to lead the transformation of the scientific foundations of the generic drug program is exciting. We look forward to the scientific challenges of 2015 and to working with our many external collaborators to enhance access to safe and affordable generic drugs.
The Division of Therapeutic Performance (DTP) in ORS facilitates development of generic drug products through pre-ANDA communications with potential applicants about therapeutic equivalence of their proposed generic products. Research in DTP focuses on equivalence for complex and locally-acting drug products.
In the past decade, generic drug use has risen exponentially, but the switch from brand-name to generic drugs, however, has moved more slowly for locally-acting and complex drug products, because the assessment of bioequivalence (BE) is less amenable to traditional plasma pharmacokinetic (PK) methods. Unlike orally-absorbed dosage forms, where the rate and extent of drugs delivered systemically can be compared by blood sampling, the rate and extent of drugs delivered locally or of products with unique formulation features is considerably more challenging to measure and compare.
Consequently, traditional approaches for demonstrating BE do not assess therapeutic equivalence for certain classes of drugs, including locally-acting drug products applied to the skin, mucosal surfaces of the pulmonary tree, gastrointestinal (GI), and genitourinary tracts, ophthalmic and otic products, as well as drugs that have been engineered based on more recent technological advances such as nano-products, liposomal products, and long-acting injectable products with unique formulation characteristics. Research facilitates the development of regulatory recommendations for developing generic versions of these complex drug products.
The Division of Quantitative Methods and Modeling (DQMM) in ORS provides expertise in advanced quantitative methods for the generic drug program and conducts quantitative-based GDUFA regulatory science activities.
DQMM research activity advances several key tool sets:
- Physiological based pharmacokinetic (PBPK) models
- Pharmacometrics for generic drugs
- Analysis of Big Data for generic drugs
PBPK models mechanistically describe drug release and absorption for oral and non-oral drug products. These models allow DQMM scientists to drive key decisions about regulatory standards and product specifications. Models of the non-oral routes of delivery are critical in evaluating new bioequivalence approaches for complex products.
Pharmacometrics for generic drugs use tools that characterize the variability and pharmacodynamics (PD) effects of drugs to aid decisions about the best way to establish bioequivalence. Quantitative analysis is critical to decisions about optimal BE study design; sensitivity of pharmacodynamics (PD) endpoints; selection of PK metrics, such as partial AUC (pAUC), for BE assessment; and definition of Narrow Therapeutic Index (NTI) drugs.
Methods based on the emergence of Big Data, such as analytics for equivalence of complex mixtures, risk-based models, systems pharmacology, business process models, and post marketing surveillance, inform decisions across the generic drug program.