Modern tools to advance generic drug development and review

In news releases issued by the U.S. Food and Drug Administration (FDA), “firsts” always catch the eye. Because the majority of prescriptions in the U.S. are dispensed with generic medications, announcements of new “first generics” are especially noteworthy. These products are the first approval by the FDA that permits a manufacturer to market a generic drug product in the U.S. The FDA considers first generics to be important to public health, and prioritizes the review of these drug applications.

Generic prescription drugs that are approved by the FDA have the same high quality and strength as brand-name drugs. Likewise, the manufacturing and packaging sites for generic prescription drugs must pass the same quality standards as those of brand-name drugs.

At a public meeting held in October of last year—Leveraging Quantitative Methods and Modeling to Modernize Generic Drug Development and Review—FDA Commissioner Scott Gottlieb shared that generic drugs accounted for 89% of all prescriptions in the U.S. in 2016. This translated into an estimated $227 billion saved on healthcare for consumers. Given these realities, Gottlieb stated that he has chosen to make access to quality, affordable generic drugs a priority issue.

Spurring innovation in the generic drug realm will require, as Gottlieb described, the use of “more rigorous science, quality data and the use of sophisticated quantitative methods and computational modeling in drug development, evaluation and review.” He noted that the FDA has already begun to adopt many of these advanced tools, including more widespread use of modelling and simulation, on the new drug side; for example, model-informed drug development (MIDD) has been incorporated into more than 90% of new drugs and biologics. MIDD includes pharmacokinetic/pharmacodynamic (PK/PD) models, physiologically based pharmacokinetic (PBPK) or absorption models, systems pharmacology, quantitative risk modelling and emergent machine learning tools. As with its use in the new drug realm, MIDD can also enable more efficient approvals of generic drugs, Gottlieb said.

During her presentation at the October public meeting, Kathleen Uhl, director of the FDA’s Office of Generic Drugs (OGD), summarized the current key uses of quantitative methods and modelling for new drugs. She noted that the FDA has the most experience with PK/PD and PBPK as related to drug-drug interactions; however, additional applications are:

  • dosing recommendations in labelling;
  • dose extrapolation (pediatrics or other populations);
  • dose determination for patients with organ dysfunction (e.g., renal or hepatic impairment);
  • justification for prioritizing studies (“when” to conduct certain studies); and
  • supporting a particular study design (“how” to conduct certain studies).


There are numerous opportunities for the use of quantitative methods and modelling for generic drugs, Uhl said. Regarding generic drug development, review and regulatory decision-making, Uhl explained that it will be critical to leverage knowledge and experience in the new drug setting and to identify best practices to improve the use and acceptance of quantitative methods and modelling.

Under the FDA’s generic drug program, Uhl noted, approximately 1,000 abbreviated new drug applications (ANDAs) are submitted annually; this is 10-fold higher than the new drug side, she added. Within fiscal year (FY) 2017 (11 months), there were 855 ANDA approvals; these comprised 693 full approvals and 162 tentative approvals. Currently, there are approximately 10,000 approved ANDAs; roughly 25% of these were approved within the past five years, since passage of the Generic Drug User Fee Amendments of 2012 (GDUFA I). This “huge volume” of applications presents abundant opportunities in the generic drug space to use quantitative methods and modelling, Uhl said.


Complex matters 

A specific category of drugs that has at times been difficult to “genericize,” Gottlieb said during the October meeting, is complex generic drugs. These, he explained, represent some very expensive and widely used medicines.

To support the development of high-quality ANDAs for complex generic drugs, the FDA in early October 2017 issued a new draft guidance for industry, Formal Meetings Between FDA and ANDA Applicants of Complex Products Under GDUFA.1 This document describes an enhanced process for discussions between the FDA and a prospective applicant preparing to submit (or an applicant that has submitted) an ANDA for a complex generic drug product to the agency.

As defined in the GDUFA Reauthorization Performance Goals and Program Enhancements for FYs 2018-2022, also known as the GDUFA II “goals letter” or “commitment letter,” complex products are:

  • products with complex active ingredients (e.g., peptides, polymeric compounds, complex mixtures of active pharmaceutical ingredients [APIs], naturally sourced ingredients); complex formulations (e.g., liposomes, colloids); complex routes of delivery (e.g., locally acting drugs such as dermatological products and complex ophthalmological products and otic dosage forms that are formulated as suspensions, emulsions or gels); or complex dosage forms (e.g., transdermals, metered dose inhalers, extended-release injectables);
  • complex drug-device combination products (e.g., auto-injectors, metered dose inhalers); and
  • other products where complexity or uncertainty concerning the approval pathway or possible alternative approach would benefit from early scientific engagement.

Mechanism-informed modelling can help develop complex drug products and facilitate their review and approval, said Uhl at the October public meeting. This work, based on knowledge of drug substance property, formulation characteristics, in vitro release profiles and physiologic variables, is used to create and develop PBPK models and to do hypothesis testing and risk assessment, Uhl said.

In the world of modelling and simulation where one requires “priors” to help define assumptions and create models, there are plenty of priors in the generic space, Uhl explained. Much is known, she said, about formulations and about the reference listed drug (i.e., the brand-name drug) that the generic drug is trying to copy. All this translates into opportunities for more efficient development of drug products with limited generic competition, Uhl noted, including dermal, inhalant, ophthalmic, nasal and transdermal complex generic drug products.

Gottlieb summarized at the October public meeting that the described FDA actions within the generic drug setting, including the issuance of relevant guidance documents, are part of a broader effort by the administration to address the high and rising cost of drugs.





Editor’s Note: This article was originally published in the Journal for Clinical Studies. 

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