Common Filing Deficiencies in Abbreviated New Drug Applications Containing Clinical Endpoint Studies

The objective of this report is to summarize common deficiencies identified in the filing reviews of abbreviated new drug applications (ANDAs) with clinical endpoint bioequivalence studies and skin irritation, sensitization, and adhesion (I/S/A) studies received by the US Food and Drug Administration (FDA) between 2007 and 2017, to help applicants avoid common deficiencies, minimize “refuse-to-receive” (RTR) actions, “information requests,” and ANDA approval delays. Multiple internal FDA databases were searched to evaluate and summarize common deficiencies identified in ANDA submissions containing clinical endpoint studies and skin I/S/A studies that required review by the Division of Clinical Review. A total of 275 ANDA submissions with filing reviews from January 2007 to June 2017 were analyzed in this report. Two hundred eighteen (79.3%) filing reviews contained one or more deficiencies. Seventy-nine (28.7%) ANDAs were issued RTR letters because of major clinical deficiencies, specifically bioequivalence and clinical deficiencies, accounting for 9% of overall identified deficiencies. Twenty-two other categories of deficiencies are summarized into 4 main categories: missing information related to the clinical studies other than data sets (38%), missing data sets (35%), formulation issues (12%), and organization/format issues (6%). The most common deficiency in the “missing information related to the clinical studies other than data sets” category was “missing clarification of information” (22%). We also noted that the Division of Filing Review has identified these same types of deficiencies since assuming responsibility of the filing assessment for ANDAs with clinical endpoint BE studies and skin I/S/A studies. In conclusion, to minimize “refuse-to-receive” actions, “information requests,” and approval of ANDA delays for generic drug products, applicants should submit full clinical study reports, including all data sets for drug products recommending clinical studies