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Pharmaceuticals

EQRx launches to develop me-too drugs at a steep discount

The biotech firm has $200m in funding to support its drug development experiment

by Lisa M. Jarvis
January 13, 2020

 

Venture capitalist and serial entrepreneur Alexis Borisy has founded EQRx to develop equal or better versions of innovative medicines—often called me-too drugs—and sell them at a substantial discount to competing therapies. With an initial investment of $200 million from a syndicate of investors, the biotech firm plans to put 10 new, more affordable drugs on the market in the next decade.

Pharma companies have long pursued me-too therapies, but the launch of these competing medicines has not always driven down pricing for a class of drugs—particularly in therapeutic areas like oncology.

Technology is ripe to make the discovery and development of me-toos faster and cheaper, Borisy says. “In the past, people would have said ‘Computation, it’s not good for anything,’ ” he says. “The world has fundamentally changed.”

As an example, Borisy points to the million-compound libraries that big pharma companies have historically screened for hits against a protein of interest. “Today, you can do a virtual screen of a billion compounds, do on-demand synthesis of all of those, and you can do it overnight in the cloud.”

Once a molecule is made, Borisy points to the potential to analyze reams of clinical data to design efficient studies that can prove a drug’s value to government groups and payers.

Combined, these technological efficiencies could bring down the cost of getting a drug onto the market—often cited as between $2 billion and $3 billion—by an order of magnitude, Borisy says. If EQRx spends, on average, $300 million to $400 million per drug, he believes the biotech firm can still be “very profitable,” even as it offers its medicines at a significant discount.

Some experts in the computation field are cautious about how easy it will be to realize the company’s ambitions. To date, biotech firms have used computation and machine learning to make some—but far from all—parts of the drug development process more efficient.

One of the real world successes came last year from Chematica, which showed that machine learning could be used to plot out actionable synthetic routes that evade infringing on drug patents. That milestone was 15 years in the making, says Bartosz A. Grzybowski of the Polish Academy of Sciences and Ulsan National Institute of Science and Technology. He and his colleagues developed the Chematica software, which was acquired by MilliporeSigma in 2017.

Grzybowski is more circumspect about the near-term prospects of using computational methods or machine learning to design around patents. “Even in synthesis, in some sense it’s a very difficult problem, but it’s not as difficult as developing from scratch a new drug,” Grzybowski says.

Still, EQRx has already generated significant buzz for its ambitious aim, marquee investors—Andreessen Horowitz, Arch Venture Partners, and GV are among its backers—and notable names attached to the project. EQRx is cofounded by Sandra Horning, who recently retired from Genentech, where she was chief medical officer, and Peter Bach, the director of the Center for Health Policy Outcomes at Memorial Sloan Kettering Cancer Center, and a critic of spiraling drug prices.

Health care experts are intrigued by the experiment. “Today we rely on generic entry to lower spending on drugs, but that typically takes a long time and, in many cases, clinical practice has moved on to newer drugs by the time generics are approved,” says Stacie B. Dusetzina, a health policy professor at Vanderbilt University Medical School. The situation means new drug prices are priced at “what the market will bear,” she says, a situation that has driven health care costs to unsustainable levels.

If EQRx succeeds in offering real cost savings, “even the threat of this could lead branded drugmakers to be more cautious in their pricing to avoid being targeted for competition,” Dusetzina adds.

But some wonder whether EQRx investors will maintain their support for the founders’ cost-cutting intentions in the long haul. While Amitabh Chandra, director of health policy research at the Harvard Kennedy School of Government, is encouraged that people are trying to show efficient drug development is possible, he is also circumspect. “We have seen no evidence that shareholders are interested in passing up on profits when profits are possible.”

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Comments
Robin Clark (January 16, 2020 3:19 PM)
I wish him luck and maybe I misunderstand the approach but this does not appear to be a novel concept as most, if not all, major pharma have employed the "me too, fast follower, second generation" approach for selected programs. Numerous valuable drugs have resulted from this path but the development time and expense is not necessarily significantly shortened compared to a novel research program. The "me too" drug has to go through the same patent, IND and NDA enabling activities as any other new chemical entity. This remains a dauntingly expensive and high risk process.
Virtual screening of million molecule libraries and synthesis carried out in the cloud? I fail to see the connection to the "fast follower approach" which is usually a patent busting activity based on known structures. Virtual screening may result in hits which then must be converted to a real leads and so forth, which is the approach (albeit with actual screening hits) that most discovery organizations now employ.

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