Setting standards in the CRISPR genome editing revolution. Interview: Samantha Maragh (NIST)

- Thank You very much for taking time to talk to us. From your perspective what do you think are the greatest challenges of the CRISPR field?

We are at the beginning of a genome editing revolution. Things are moving so quickly and that is both a challenge and a really great opportunity.

There is a lot of innovation which is very exciting, but it makes it difficult to know where you are in the development of this technology. What you did today may completely change tomorrow because somebody has published a new innovation that makes it already outdated.

Setting standards begin by understanding practise

- When the field is moving so fast how should you implement best practices and standards?

We have to think a little bit differently about standards from standards in a field that's very established.

Right now we have to think about standards in terms of understanding the practices and we are still in that stage of understanding what we are doing.

What we have found particularly for CRISPR applications is that even how much of Cas9 and guide RNA somebody is using in their study, is being done very differently and it is not always clear.

So I think we can begin to standardize by recording metadata about our studies. That is the only way we can even begin to get to what could be a best practice.

Metadata: Opportunity for the community

- You talk about establishing a database for metadata?

Yes, to be able to go back to look at your data and see exactly what you did is really important and being able to share that in a way that is normalized. Something as simple as a fillable form - for these steps I used this reagent at this level, for this amount of time and then I looked at it in this way.

There is no infrastructure for this community to communicate in that way and in fact it is not that common for other communities. But I think there's a really great opportunity here to push the envelope on how we as a field can share information and it could be really powerful for helping understand and replicate science

- To make data from different labs comparable?

To make them comparable and also to know whether it's reasonable to expect they would be comparable.

You may find out by the time we look at the study that 'oh they're using different cell lines' and I would reasonably expect that maybe these different cell lines would give a different result. Or maybe they are using reagents that are formulated slightly differently and it might be reasonable that, how you formulate might make the result different.

But as it is today we can't even begin to tease out those things to know if the studies are comparable.

- How do you plan to launch this database?

Well, it's meant to be a global resource and the first thing is getting the thought process out there.

What we're doing is meeting people and talking at conferences, and then we plan to develop a white paper that would describe the vision of how we might all think about data and about metadata and how we might be able to come together as a field and leverage each other in a more effective way.