Verge Genomics gathers $32M to trial its AI-built neuroscience drugs

In Silico
Verge CEO Alice Zhang says the company's investors, including WuXi AppTec and tech VC firm DFJ, reflect its commitment to marrying life sciences research with big data analytics. (Pixabay / Geralt)

Neuroscience drug discoverer Verge Genomics has raised $32 million in early venture capital financing, a large boost to its plans to bring its AI-generated compounds to the clinic against amyotrophic lateral sclerosis and Parkinson’s disease within the next three years.

The series A round was led by the tech-focused firm DFJ, which has invested in Tesla, Twitter and Skype, with additional funding from WuXi AppTec’s venture fund. Agent Capital, ALS Investment Fund and OS Fund also participated in the round.

Since being launched in 2015, the San Francisco-based Verge has worked to develop its proprietary genomic datasets—derived from brain tissue samples from patients who have died from neurodegenerative diseases—and created some of the field’s largest, comprehensive sources for ALS and Parkinson’s disease data, according to co-founder and CEO Alice Zhang.

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From those, Verge has identified 22 novel targets for ALS by screening thousands of genes, Zhang told FieldMedTech. After validating several of those targets with in vitro and in vivo testing, they have narrowed down about a dozen compounds that have shown promising initial data.

“What I find really elegant about the approach…is that we actually take drugs flagged by the algorithm and then test them again in real patients’ brain cells,” Zhang said.

“We do that by taking skin cells from patients that have passed away from the disease and directly convert them into their own brain cells in the lab,” she said. The data from those experiments is then fed back into the machine learning platform, to retrain and improve the algorithms over time.

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“Verge has built one of the most comprehensive datasets that we have worked with for disease understanding, machine learning and artificial intelligence,” Edward Hu, WuXi AppTec’s chief financial officer and chief investment officer, said in a statement. “Importantly, Verge’s integrated approach to drug development aligns patient data with animal models to ensure the use of appropriate translational research.”

Zhang hopes that starting from an all-human dataset will give Verge an edge compared to traditional drug discovery that may involve animal proxies or other preclinical models, allowing the company to be more accurate in predicting which compounds will translate into improved outcomes.

“Many companies don't use human data until they get into clinical trials, which is the most expensive and risky part of drug development,” she said. Currently, the company is working on replicating early results and further developing its compounds.

Verge has previously signed discovery deals with two unnamed Big Pharma companies in bipolar disorder and cerebral amyloid angiopathy, and is currently evaluating new opportunities.

“It’s hard to do drug development on your own,” Zhang said. “But I think the nice thing about this most recent round of $32 million is that it allows us to focus on our internal development—and not need to necessarily rely on pharmaceutical companies to generate revenue—and to develop our own most promising candidates.”

“It also gives us space to pursue partnerships when they can help give us multiple shots on goal, or to continue to validate the platform,” she added.

The new money brings Verge’s total funding to $36 million, with the company’s range of participating investors—from the life sciences and technology sectors—mirroring, in Zhang’s view, its upcoming plans to build out its staff in medicinal chemistry and drug discovery, as well as in big data and machine learning.

“Our belief is that the most promising applications of AI will come from owning multiple parts of the value chain, and integrating cross-disciplinary teams that break down the silos between biology and computation,” she said. “Generating your own proprietary data, and focusing on developing your own drug products, is the best way of incentivizing the company to develop the right methods and the right algorithms.”

“I do think there's a scientific and technological renaissance happening in this field, and this is a better moment than any to make real breakthroughs.”