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One of the most important areas to be transformed by our ability to generate larger than life data sets, and our capacity to analyze them, is medicine. 23andMe’s ability to analyze anyone’s DNA quickly and cost effectively, paired with its success in getting 800,000 people (an impressive 90% of its customers) to provide their genetic data as part of an anonymized database, foreshadows a future where personalized medicine becomes possible.
23andMe was founded in 2006 with the mission of (1) providing genetic testing and interpretation to individual consumers, and (2) through these tests, creating a vast genomic database which may be used in advancing medicine.
- How the test works
- How 23andMe differs from other genetic testing services
- Faster and cheaper testing (Ease of data collection)
Rather than sequencing a full genome (which costs $10,000), 23andMe employs single nucleotide polymorphisms (SNP) chip technology, which sequences less than 0.1% of the genome but offers genetic results for 260 factors. This enables 23andMe to provide fast results, at an affordable price – today, kits cost $199.
- Accessing a larger population (Scale of collection)
23andMe fundamentally differs from others in the genetic testing space in terms of its underlying “Direct-to-Consumer” (DTC) approach to collecting data – it is the first and only company to receive FDA authorization to market a direct-to-consumer genetic test. The vast majority of genetic tests come through a doctor, and are requested for testing one, or a very specific set, of genes. Navigenics, for example, a 23andMe competitor, makes its tests available only through healthcare professionals, whereas 23andMe launched its genetic test as a DTC product. According to founder Anne Wojcicki, “We’re DTC not because it’s easy, but because that’s how you create a revolution.” A key to this ‘revolution’ is being able to aggregate genomic data from far more people, thanks to a $199 price tag and DTC marketing.
- Value Creation & Value Capture
23andMe creates value for consumers by (1) generating quick and affordable insights which may help them better plan their healthcare, and (2) ancestral information which may help find relatives, or be of pure entertainment value. It captures value from consumers through its $199 kit fee.
While this consumer facing value creation/value capture mechanism has generated 23andMe’s revenue so far, building its large, unprecedented genomic database has laid the foundation for 23andMe to capture value in much bigger ways – by selling data and related services, and down the line, even developing its own personalized drugs. 23andMe’s Personal Genome Service isn’t primarily intended to be a consumer device, but a “front-end for a massive information-gathering operation”, where its true value creation and capture lie – analogous to the search engine’s role in Google’s ultimate value creation/capture. In February,“23andMe announced the first of ten deals with big biotech: Genentech will pay $60M to access 23andMe’s data to study Parkinson’s.”  The potential to uncover genetic causes of hereditary diseases through pattern matching in its massive data set could pave the way for 23andMe to develop its own billion-dollar blockbuster drugs; and in March, 23andMe announced plans to start inventing medicines itself.
- Avoiding the big pitfalls in the data
SNP is used to sample the genome at thousands of points, rather than fully sequencing it; to then correlate genomic variants commonly found in the ‘average’ population with diseases and traits.
- Using genomic variants means results of these reports are not nearly as predictive as looking at family history or specific genes (such as the BRCA breast cancer gene) – geneticists call their clinical validity into question.
- Companies doing SNP-based testing don’t define ‘average’ population risks or select sets of single nucleotide polymorphisms in the same way, as evidenced by published research (Tables 1) on taking tests across different providers, which produced vastly different results.
- These tests assume genes are always ‘acting’ independently of one another – they only “consider marginal effects of each SNP and fail to accommodate epistatic effects” (genes having different effects in combination than individually)
Bias in sample population
- There may be inherent selection bias in the populations that opt to take DTC tests – (1) young, more tech savvy early adopters keen to get a glimpse of their genetic information for more recreational value, or (2) people who have a family history of a serious disease, to cite a few examples. This means the average test taker will not be representative of the average population.
Incorrect interpretation of results
- Beyond the above-mentioned risks, there is that of consumers incorrectly interpreting their results.
 Source: Illumina
 Murphy, “Inside 23andMe.”
Variations in predicted risks in personal genome testing for common complex diseases, Rachel R.J. Kalf, MSc,1 Raluca Mihaescu, MD,1 Suman Kundu, MSc,1 Peter de Knijff, PhD,2 Robert C. Green, MD, MPH,3 and A. Cecile J.W. Janssens, PhD1,4