Home Healthcare Verge Genomics AI Neuroscience Startup Secures $32M

Verge Genomics AI Neuroscience Startup Secures $32M

Developing new drugs is not an easy task. In fact, the Tufts Center for the Study of Drug Development revealed that pharmaceutical companies spent an average of $2.7 billion to put medicine to store shelves.

The organization also said that a maximum of 90 percent of treatments in late-stage tests never reached the market as they are considered unsafe or ineffective.

Amidst this challenge affecting drug development, Verge Genomics, a Y Combinator graduate, is convinced that by leveraging the power of artificial intelligence, the drug development process can be expedited dramatically.

Recently, the Silicon Valley-based company announced that it had secured $32 million in a financing round that was led by DFJ. Other companies that took part in the round include OS Fund, Agent Capital, ALS Investment Fund, WuXi AppTec’s Corporate Venture Fund.

In a phone interview with VentureBeat, Alice Zhang, the founder of Verge Genomics, said that Verge Genomics is looking forward to eliminating guesswork from drug discovery.

As such, she added that the recent funding would help the company in advancing its most budding drug candidates towards the clinic as it continued to grow not only its therapeutic portfolio but also its proprietary datasets.

A significant portion of Verge Genomics’ research revolves around various conditions including amyotrophic lateral sclerosis(ALS), Parkinson’s, Alzheimer’s among other neurodegenerative diseases that have historically proven to be challenging for researchers in the pharmaceutical industry to target.

Currently, an estimated 400 clinical trials have conducted experimental treatment tests.

However, the only drugs approved for Parkinson’s disease only deal with its symptoms without stopping its progression.

Currently, Verge Genomics utilizes machine learning models that are trained on both lab and patient data, which spots genes within disease networks, forecasting compounds that may be an obstacle to their activity.

Researchers from the company test the compounds in both animal nerves and models that are grown out of stem cells. They use the results gathered from such tests to further improve their models.

According to Zhang, developing a drug that projects results in the laboratory takes nearly one year and a half. He added that much of the training data that is produced by Verge Genomics’ in-house animal facilities and drug discovery labs is proprietary.

The company has one of the most complete and largest databases of Parkinson’s disease and ALS’ genomic data thanks to its collaboration with twelve government and academic organizations.

Back in May, Verge Genomics partnered with VIB, a Berlin-based research institute, and the University of California San Diego to sequence genes that are expressed in the brains of those who have Parkinson’s disease.

Last year, the company unveiled an alliance with the Motor Neuron Center at Columbia University, the University of Michigan Medical School, Massachusetts General Institute for Neurodegenerative Disease and the Kerk School of Medicine at the University of Southern California to study ALS.

Alice Zhang said that drug companies are focusing on a single gene at a time. She added that even though that process works for various diseases, hundreds of genes can cause more complex conditions. Also, drug companies do not normally use human data until they enter clinical trials.

Source VentureBeat

Subscribe to our newsletter

Signup today for free and be the first to get notified on the latest news and insights on artificial intelligence

KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
- Advertisment -

MOST POPULAR

AI Model Development isn’t the End; it’s the Beginning

AI model development isn’t the end; it’s the beginning. Like children, successful models need continuous nurturing and monitoring throughout their lifecycle. Parenting is exhilarating and, if...