compliance and quality

SEND is an abbreviation for Standard for Exchange of Nonclinical Data.

Very briefly, it describes a structured way of compiling data collected in nonclinical (animal) studies for exchange between IT systems. In addition to the structure, SEND also comes with defined terminology for a number of standard endpoints and results.

By using the same way of structuring data as well as defined naming conventions, the electronic data lends itself more easily to analysis. Both IT systems as well as reviewing toxicologists can depend on the same data always being called the same thing and located in the same place.

Not only will science benefit from easier access to increasingly larger amounts of data, but standardizing electronic data is a necessary prerequisite to maintain the data review and ultmately drug safety assessment an effective process.

SEND was developed and is maintained by the Clinical Data Interchange Standards Consortium (CDISC) SEND team. This is a voluntary and collaborative effort by nonclinical and IT experts from more than 40 companies including FDA. Data Standards Decisions has been represented in the CDISC SEND team since 2007.

You can read more about CDISC and SEND here:

CDISC Vision and Mission

SEND Implementation Guide

SEND Implementation Wiki

The Food and Drug Administration Safety and Innovation Act (FDASIA) signed into US law on July 9 2012 provided mandate to FDA to issue binding guidances regarding requirements to electronic submissions.

Binding guidance means that requirements described in these are legally enforceable and can result in actions by the authorities if not followed.

On December 17 2014 FDA issued the final binding guidances on submission of standardized electronic data.

As a consequence, FDA will no longer accept non-standardized and non-electronic submissions from December 17 2016 for NDA's and BLA's and from December 17 2017 for IND's.

For nonclinical studies this means that studies starting after December 17 2016 must be submitted to FDA in SEND format.

The guidance is very clear on exemptions and waivers:

Exemptions applies only to specific devices and noncommercial IND's.

Waivers will not be granted for non-reviewable submissions.

You can read more about FDA regulation here:

FDA Study Data Standards Resources

We are closely monitoring steps taken by the European Medicines Agency (EMA) as well as Japan's Pharmaceuticals and Medical Devices Agency (PMDA). Certainly SEND has also caught the attention of PMDA, but a formal guidance is still awaiting.


On this page you will find high level information about SEND and topics concerning SEND. We have provided references where further information can be obtained. Should you have any questions about the content on this site, you can reach us using the contact information here.

About SEND

There is often a misconception between data quality, compliance and adherence to validation rules. While data validation is an integral part of assessing the quality of a data package, it should never be the only means to that end.

SEND datasets exist in the context of a study package, composed also of a define file and a Study Data Reviewer Guide. All must be coherent with each other.

The quality and compliance of SEND datasets should be assessed not only towards external requirements, such as the SEND Implementation Guide and published data validation rules, but also in relation to the context in which the datasets are provided.

The purpose of having data standards is to facilitate the generation of useful data. Needless to say, the standard itself does not guarantee usefulness of the data, so great care and consideration must be put into how data should be accurately represented within the standard to support its intended purpose.

Data quality is therefore not just about getting as few validation hits as possible, but ensuring that the data is fit for purpose. This can only be achieved by a well-defined business process.

An example of why data validation on its own is not adequate to assess data quality is missing data. Omitted results from the SEND datasets will not be picked up by current published validation rules, but it will severely impact the usefulness of the datasets.  Not only that, if the missing data is not accounted for in the study package, it will appear untrustworthy to a reviewer.