New FDA guidance on statistical approaches to establishing bioequivalence

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In December 2022, US Food and Drug Administration (FDA) updated its draft guidance on statistical approaches to establishing bioequivalence [1]. Following this, the public were given 60 days to comment of the draft.

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When finalized, the guidance will replace the 2001 version of the guidance which includes ‘principles for assessing in vivo and in vitro bioequivalence studies for investigational new drugs (INDs), new drug applications (NDAs), abbreviated new drug applications (ANDAs) and supplements to these applications’. The updated version has recommendations on additional topics, including: missing data and intercurrent events, adaptive design, and specific situations, such as narrow therapeutic index drugs and highly variable drugs. 

The draft guidance notes that, when it comes to clinical trials, missing data and intercurrent events can introduce issues such as bias, misleading inference, loss of precision and loss of power, which make it hard to interpret the trial outcome. It outlines aspects of the International Council for Harmonization’s (ICH) guideline introducing the concept of estimands for handling missing data [2] and guides drug product applicants towards this and advises the inclusion of methods to minimise missing data. It is also noted that applicants can contact the Agency via the controlled correspondence, pre-ANDA meeting, pre-IND meeting, or pre-NDA meeting pathway to discuss the handling of missing data.

In the guidance, FDA notes that it encourages generic and new drug applicants to propose and discuss novel methodologies such as model-based bioequivalence and novel adaptive designs for comparative clinical endpoint bioequivalence studies, through appropriate regulatory meetings. Adaptive design is described as ‘a clinical trial design that allows for prospectively planned modifications to one or more aspects of the design based on accumulating data from subjects in the trial’ [2]. The guidance states that adaptive design can provide ethical advantages and statistical efficiency and can ‘reduce resources used, decrease time to study completion, and increase the chance of study success’. 

Regarding narrow therapeutic index drugs, FDA notes ‘a fully replicated cross-over design should be used’. Additionally, a partial or fully replicated cross-over design should be used when considering a high variable drug.

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1. U.S. Food and Drug Administration. Guidance for Industry. Statistical approaches to establishing bioequivalence. December 2022 [homepage on the Internet]. [cited 2023 Jan 20]. Available from:
2. U.S. Food and Drug Administration. Guidance for Industry. E9(R1) statistical principles for clinical trials: addendum: estimands and sensitivity analysis in clinical trials, revision 1. May 2021 [homepage on the Internet]. [cited 2023 Jan 20]. Available from:
3. U.S. Food and Drug Administration. Adaptive designs for clinical trials of drugs and biologics. December 2019 [homepage on the Internet]. [cited 2023 Jan 20]. Available from:

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