FDA Drug Review


This post is part of 'Domain | General' series

If a drug developer has evidence from its early tests and preclinical and clinical research that a drug is safe and effective for its intended use, the company can file an application to market the drug. The FDA review team thoroughly examines all submitted data on the drug and makes a decision to approve or not to approve it.

New Drug Application

A New Drug Application (NDA) tells the full story of a drug. Its purpose is to demonstrate that a drug is safe and effective for its intended use in the population studied.

A drug developer must include everything about a drug—from preclinical data to Phase 3 trial data—in an NDA. Developers must include reports on all studies, data, and analyses. Along with clinical results, developers must include:

  • Proposed labeling

  • Safety updates

  • Drug abuse information

  • Patent information

  • Any data from studies that may have been conducted outside the United States

  • Institutional review board compliance information

  • Directions for use

FDA Review

Once FDA receives an NDA, the review team decides if it is complete. If it is not complete, the review team can refuse to file the NDA. If it is complete, the review team has 6 to 10 months to make a decision on whether to approve the drug. The process includes the following:

  • Each member of the review team conducts a full review of his or her section of the application. For example, the medical officer and the statistician review clinical data, while a pharmacologist reviews the data from animal studies. Within each technical discipline represented on the team, there is also a supervisory review.

  • FDA inspectors travel to clinical study sites to conduct a routine inspection. The Agency looks for evidence of fabrication, manipulation, or withholding of data.

  • The project manager assembles all individual reviews and other documents, such as the inspection report, into an “action package.” This document becomes the record for FDA review. The review team issues a recommendation, and a senior FDA official makes a decision.

FDA Approval

In cases where FDA determines that a drug has been shown to be safe and effective for its intended use, it is then necessary to work with the applicant to develop and refine prescribing information. This is referred to as “labeling.” Labeling accurately and objectively describes the basis for approval and how best to use the drug.

Often, though, remaining issues need to be resolved before the drug can be approved for marketing. Sometimes FDA requires the developer to address questions based on existing data. In other cases, FDA requires additional studies. At this point, the developer can decide whether or not to continue further development. If a developer disagrees with an FDA decision, there are mechanisms for formal appeal.

 

source: fda.gov





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General
What are CDISC standards?
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What is a clinical trial registry?
What is the importance of baseline characteristics in a clinical trial?
Drug discovery
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The Investigational New Drug Process
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Key steps in developing new drugs and biologicals

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What is a crossover clinical trial?

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What is a cohort?

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Introduction to SAS interface
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Count the number of times a particular value occurred in a variable of a dataset

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Check the list of variables in a SAS dataset

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Delete all sas datasets from a library
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WARNING: No matching members in directory.

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How to derive baseline flag in SDTM
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How to convert original results to standard results using conversion factors

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What information does SDTM.DM (Demographics) contain?

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What is causality assessment?
What information does SDTM.AE (Adverse Events) contain?

Disposition
What information does SDTM.DS (Disposition) contain?

Concomitant Medications
What information does SDTM.CM (Concomitant/Prior Medications) contain?

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What information does SDTM.PR (Procedures) contain?

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How to select/subset required rows in SAS and R tidyverse

Appending data
Append two datasets in SAS and R tidyverse

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Merge/full join two datasets in SAS and R tidyverse
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Sort (order) observations
Sort/order observations based on the values in a single variable in SAS and R tidyverse

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Restructure/transpose long data to wide data
Restructure/transpose wide data to long data

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Obtain frequencies/counts based on one variable - one-way frequencies in SAS and R tidyverse
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Descriptive statistics
Descriptive statistics for a numeric variable using SAS and R tidyverse