The Perils and Promise of Partnerships Between Biopharma and Data Companies

Two people standing over data and charts and pointing to it

Recently, 23andMe partnered with GlaxoSmithKline, causing the Forbes Technology Council to cite eight ways these types of partnerships will affect disease treatments. These types of partnerships aren’t exactly new.

In 2015, Calico Life Sciences, a Google/Alphabet company, partnered with Provo, Utah-based AncestryDNA to analyze and investigate genetics and longevity using Ancestry’s proprietary databases, tools and algorithms. And in 2014, Calico signed a deal with AbbVie, and Google in 2015 partnered with the Broad Institute of Massachusetts Institute of Technology and Harvard University to launch a version of Broad’s Genome Analysis Toolkit (GATK) on Google’s Cloud Platform.

Biopharma companies are partnering with tech companies, and the emphasis is on big data analytics and tearing down silos and creating access across multiple databases of health, personal and genomic data.

The Forbes Technology Council, aware of this, presented eight ways they believe these partnerships will affect how diseases are treated. Here’s a look.

#1. Identify key opportunities for treatment. As mentioned earlier, the goal is to find something in the data that can lead to new drugs or possible treatments. “Rather than focus on the DNA of one person, this project will seek to use millions of tests and survey responses to identify key opportunities in the treatment of life-limiting disease,” stated Jeff Bell, chief executive officer of LegalShield.

That’s consistent with what Hal Barron, chief scientific officer and president of R&D for GSK said of the 23andMe partnership: “We know that drug targets with genetic validation have a significantly higher chance of ultimately demonstrating benefit for patients and becoming medicines. Partnering with 23andMe, an organization whose vision and capabilities are transforming the understanding of how genes influence health, will help to shift our research and development organization to be ‘driven by genetics,’ and increase the impact GSK can have on patients.”

#2. Personalized care. So-called personalized medicine is the idea of using genomic testing (or pharmacogenetic testing) to identify which drugs are best suited for an individual. This is already happening to some extent. One area where this is quite noticeable is in oncology drug development. Increasingly, a cancer drug is chosen (and approved) for a very specific subset of cancers. For example, in April, the U.S. Food and Drug Administration (FDA) approved AstraZenecas Tagrisso (osimertinib) for the first-line treatment of patients with metastatic non-small cell lung cancer (NSCLC) in tumors with epidermal growth factor receptor (EGFR) mutations. Those mutations, exon 19 deletions or exon 21 L858R mutations, will be detected by an FDA-approved test.

#3. Faster, cheaper drug development. Gary Bloom, president and chief executive officer of MarkLogic, noted, “in pharma, it means the ability to safely develop effective treatments faster, and at lower costs, which can drive better health outcomes for patients.”

In September 2017, Roivant Sciences launched a new company, Datavant, which plans to use artificial intelligence (AI) to improve clinical trials. It’s led by Travis May, co-founder and chief executive officer of LiveRamp. In a statement, May said, “As a technologist looking at the biopharma industry, it’s surprising and disconcerting how little data is shared as compared to other industries. Biopharmaceutical data is siloed across big pharma companies, universities, healthcare consortia, CROs, research groups, hospital systems, regulatory bodies, patient registries, genomics companies, and EMRs. There is tremendous potential to apply analytics to this data more effectively, improve drug development, and ultimately save lives.”

#4. Efficiency. Not dramatically different than the third point, Karin Lachmi, founder and chief scientific officer of Bioz, a search engine for life science experimentation, stated, “In the next few years, significant strides will be made toward scientific data being fully accessible to researchers so that they will be able to perform their hard work more efficiently and more effectively, as at the end of the day it will benefit us all.”

#5. Insights. And the point of it all, whether it’s the new partnership between 23andMe and GSK or one of the others, is that they find something useful, some new understanding that can lead to a new drug or a new treatment that wouldn’t otherwise be found. “Having so much data will help understand diseases better,” said Chalmers Brown, co-founder and chief technical officer of Due, a company that makes it easier to accept payments and create professional-looking invoices.

#6. Disease prevention. For the most part, modern healthcare focuses on treating diseases. But Thomas Griffin, co-founder and president of OptinMonster, observes, “What if our DNA could tell us the optimal diet for each individual? We could use the data for prevention in addition to treatment.”

But would we? Mmmmm, French fries.

#7. Legislation. The way in which biopharma companies (and tech companies) are mining personal and health information, emphasizes concerns over privacy. Jason Gill, chief technology officer of TheHoth, a search engine optimization company, cites the 2008 Genetic Information Nondiscrimination Act (GINA) as a start. “Legislation needs to catch up—imagine if GSK announced it would be swabbing the doorknobs of clinics to get DNA samples of possible patients to sell them ‘designer’ cures.”

#8. Privacy. And correlating with #7, biopharma and data companies need to be sensitive (we’re looking at you, Facebook!) about how it uses the data. Seth Wasserman, vice president of information technology for Menin Hospitality, stated, “If people think their personal data is being shared, then they may not want to use the service regardless of whether it’s traceable or not.”

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