By Susi Geiger & Nicole Gross

There’s an old adage that encapsulates our relationship to many of the digital products we consume, from social media to apps to email programs: “If it’s free, you’re not the customer, you’re the product”. But what happens in an industry where this ‘you’ really means – well, you? Your genetic profile and other health information about you? Information that you may never thought you’d share?

Our paper ‘A Tidal Wave’ explores the business models of consumer genomics companies, such as 23andMe or Ancestry, to find out how the consumer becomes the product in this industry, or as we phrase it, how these companies ‘assetize’ their genomic databases. There’s a lot of talk about data privacy in healthcare, which is great; after all, information about our health really is the most sensitive of all data. However, we think that one can only really understand how privacy can be safeguarded when we understand how companies profit from this data.

In our analysis, this happens through a platform model, a business model that is sometimes also called a multisided market model. On one side of this model is the consumer who might buy a  genetic test in a pharmacy out of curiosity, perhaps to find out their ethnic links or how genes affect their wellness, or just as a cool present for Mother’s Day or Christmas. While they normally pay anywhere between €50 to 120 for this service, the costs of sequencing are often higher than the sticker price on the test.

This is where the other side of the multisided market model comes in: by persuading consumers that they really should ‘unlock’ the secrets that lie waiting in their DNA or that it’s a good thing to do so because they help science, consumer genomics companies accumulate vast databases with millions of records of individual DNA data. They then sell these on to (or ‘share’ them with, as they would say) pharmaceutical companies. Often, genetic data are combined with other information that the consumers reveal about themselves when doing the tests, for instance their demographic or lifestyle data. Of course, for pharmaceutical companies this is really valuable information for drug innovation. Not a bad thing in itself, for sure, as many of us will benefit from better medicines at some point, but the problem is that the consumer genomics company potentially makes a lot of money on the basis of ‘assetizing’ consumers’ information. In this case, you’re the product even if you paid for it! And even though the data is anonymized for privacy purposes, with DNA there’s no guarantee that this information can’t be traced back to individuals or even their relatives (Gymrek, McGuire, Golan, Halperin, & Ehrlich, 2013).

So, what alternatives do we see to these fully privatized platform models in the genomics industry? We strongly believe – with many other ethicists and social scientists (for instance Winickoff and Neumann 2005; Prainsack, 2019) – that people’s genomic information should not be privatized or assetized; instead, there should be more emphasis on building genomic data commons. This means that countries should have public genomic databases that they could make accessible to academic and commercial researchers as public good, and not as the most lucrative innovation opportunity. There would be payback for this investment by facilitating public research and development, and it would be governed by a public body, ideally with broad engagement from the public and from patient groups. There are great examples where this is happening; for instance the AllofUs program in the U.S., the 100,000 Genomes Project in the UK or the plan for an African genomic database.

Yes, it might be nice to know about your genetic dispositions to different wines, but do you really want your DNA to become the product, or would you rather know that it’s part of something that can truly benefit everyone?

References:

Geiger, S. & Gross, N. 2021. A tidal wave of inevitable data? Assetization in the consumer genomics testing industry. Business & Society, 6(3): 614-649.   https://doi.org/10.1177/0007650319826307

Gymrek, M., McGuire, A. L., Golan, D., Halperin, E., & Erlich, Y. 2013. Identifying personal genomes by surname inference. Science, 339(6117): 321-324.

Prainsack, B., 2019. Logged out: Ownership, exclusion and public value in the digital data and information commons. Big Data & Society, 6(1), p.1-15.

Winickoff, D.E. & Neumann, L.B., 2005. Towards a social contract for genomics: property and the public in the’Biotrust’Model. Genomics, Society and Policy, 1(3), pp.1-14.