- Flickr/Tambako The Jaguar
- Fauna Bio, a new biopharmaceutical startup backed by venture capitalist Laura Deming, is researching hibernating animals to unveil clues about how the human body can protect itself in emergency medical conditions like trauma, heart attack, and stroke.
- Hibernating animals have the ability to manipulate their metabolic rates, control blood flow levels, protect tissues against damage, and put on and lose a large amount of weight safely.
- The company is working to re-create a hibernation-like state in patients by using a combination of repurposed drugs that are used now for other indications, and natural compounds like melatonin.
Hibernation allows bears to sleep through entire winters – now a new startup wants to replicate this state in humans to help protect the body against severe injuries.
Ashley Zehnder, Katie Grabek, and Linda Goodman started Fauna Bio in June after they met studying different, but very complementary projects at a post-doctoral lab in Stanford.
Their company is backed by 24-year-old venture capitalist Laura Deming, who runs The Longevity Fund, which principally invests in aging-related research and discoveries.
Hibernating animals are excellent at healing themselves after suffering the equivalent of a heart attack or a stroke. The reason is because these animals are adept at manipulating their metabolism.
Hibernation as a trait can be a spectrum. True hibernators, like bears, drop their body temperature by 2-6°C for 6-9 months.
Smaller animals, like pet hamsters, go into something called torpor, which is a light form of hibernation that can occur daily. Their small size forces them to lower their body temperature more drastically in order to achieve the same metabolic processes. By proxy, they have to re-warm their bodies more periodically.
This dynamic physiology allows them to control blood flow to their heart, function in low oxygen settings (hypoxia), and protect tissues against damage and deterioration.
The Fauna team is mapping and analyzing hibernators’ RNA and DNA, and linking important genes into a network that can be activated pharmacologically. These genes span across networks in charge of energy metabolism, circadian rhythm, and insulin management.
These also overlap with the mTOR, one of the pivotal pathways implicated in aging, and AMP Kinase, a cellular metabolic pathway that’s activated by diabetes drug Metformin.
How hibernation can improve medical outcomes in emergency rooms
Emergency rooms use therapeutic hypothermia to lower patient metabolic rates and improve their survival rates in cases of traumatic brain injury, strokes, and heart attacks. This cools the body artificially from outside inwards.
“We’re forcing the body to cool when it doesn’t really want to, and that causes problems. It causes deficiencies in immune function so people get really bad pneumonia, they have issues with blood clotting,” Zehnder told Business Insider. “Part of what we’re doing is trying to figure out what are the exact initiating factors to be able to allow you to lower metabolic rate, without having to be cooled from the outside. That’s something a lot of the model hibernators do.”
Mimicking short term hibernation or creating a synthetic torpor – accounting for caveats like maintaining immune function, preventing blood clots, and stopping muscle deterioration – can help patients safely cool, heal, and re-warm. Heart attack patients can recover without suffering heart damage, and stroke therapy can be enhanced.
It can also be given long-term to patients with diabetes or silent ischemic heart attacks to resist damage from severe cardiac or metabolic events.
Further research can aid obese patients in losing weight safely, since hibernators have mastered the craft.
“We have a couple of avenues for advancing the work that we’re doing for human trials,” Zehnder said. “Each of those have different development paths and different levels of capital efficiency.” These include repurposing drugs that are already on the market, using natural compounds, and inventing new drugs.
In a recent experiment, combining the natural compounds beta-hydroxybutyrate and melatonin improved survival in animals suffering from a 60% blood loss. This combination will enter human trials sometime this year as a form of trauma therapy.
Currently, the company’s 12-18 month timeline involves a mix of experiments that they’re kicking off in the following weeks. One or two of the products will advance to pre-approval stages by late 2019.
“It’s a great time to be doing this type of work,” Zehnder said. “We’re really sitting on the precipice of being able to take advantage of new genetic drug discovery tools.”
- Alice Zhang, co-founder and CEO of drug discovery company Verge Genomics
- Verge Genomics
- Alice Zhang started Verge Genomics in 2015 with Jason Chen to combine innovation in neuroscience, machine learning and genomics and apply it to the drug discovery process.
- The vision for Verge was to become the first pharmaceutical company that automated its drug discovery engine, helping to rapidly develop multiple lifesaving treatments in diseases like Alzheimer’s disease, ALS, and Parkinson’s disease where no cure exists today.
- On Monday, the San Francisco-based company announced it had raised $32 million in series A funding, led by Draper Fischer Jurvetson, bringing its total amount raised to $36.5 million.
The drug development process is laden with problems that make it lengthy and expensive. Right now, it takes 12 years and $2.6 billion to get a single drug to market, with the drug discovery and development process costing $1.4 billion.
Verge Genomics, run by 29-year-old Alice Zhang, is trying to address these problems by making drug discovery faster and cheaper.
On Monday, the San Francisco-based company announced it had raised $32 million in series A funding, led by Draper Fischer Jurvetson, bringing its total amount raised to $36.5 million.
Zhang was three months shy of her MD and PhD graduation from University of California-Los Angeles when she left school to start Verge Genomics in 2015 with Jason Chen, who she met during the program.
“I just became very frustrated with the drug discovery process,” she said. “It’s largely a guessing game where companies are essentially brute force screening millions of drugs just to stumble across a single new drug that works.”
At the time, Zhang also recognized the advancements in neuroscience, machine learning and genomics occurring all around her. Genome sequencing had become more and more affordable, and breakthroughs in understanding how function connects with genes opened a new field of possibilities for exploring disease and health. And there was an opening for an opportunity to guesswork out of drug discovery. The vision for Verge was to become the first pharmaceutical company that automated its drug discovery engine, helping to rapidly develop multiple lifesaving treatments in diseases like Alzheimer’s disease, ALS, and Parkinson’s disease where no cure exists today.
Recently, other big pharmaceutical agencies like Novartis are also starting to follow suit, adapting technology to different steps of the clinical trial process.
Verge, 14 people large, functions at full capacity. Not only do they have computer scientists managing the front-end of machine learning, but they also have researchers working in its own in-house drug discovery and animal lab.The team is stacked with computer scientists, mathematicians, neurobiologists, as well as industry veterans and drug development veterans.
There are three main problems in drug discovery that Verge is using data and software to tackle. The first is that many diseases like Alzheimer’s disease are caused by hundreds of genes. Verge’s algorithms on human genomic data can map these genes out. The second is instead of using animal data only for pre-clinical trials, Verge uses human data from day one, which may enable greater insight into how effective the drug actually is on human cells. Drugs that work in mice often fail in humans, and that’s because they’re usually there to serve as primary mammal model. Instead of tediously screening millions of drugs, the algorithm will computationally predict drugs that work.
Verge uses brain samples from patients that have passed away from Alzheimer’s disease or Parkinson’s disease for its human data, obtained through partnerships with over a dozen different universities, hospitals and brain banks. The company then RNA-sequences them in-house, which allows them to measure the gene expression in its most current state, and it can measure simultaneously how all of the genes in the genome are behaving. This data helps scientists figure out what’s actually causing disease in these patients and see if there are connections between genes and disease.
Verge’s scientists can make predictions about what drugs they think will work. They can take a patient’s own skin cell and turn it directly into their own brain cells in a dish. Then the predictions can be tested on these brain cells to see if they can rescue them from dysfunction or death – a basic test of drug efficacy. That validation data can feed back into the platform and continuously improve predictions over time, even across different diseases.
The Verge algorithm identifies drugable targets for treatments, then design drugs accordingly. This is done by mining through human samples to identify groups of genes that are implicated with the disease, and what crucial hub in these gene networks can turn them on or off.
The latest investment in Verge will serve to advance its ALS and Parkinson’s disease drugs. There are six drugs in development, closer to the clinical end, which are being tested to make sure they’re safe and non-toxic. The funding will also be used to expand the number of diseases Verge has in its portfolio.
Emily Melton, a partner at DFJ, told Business Insider that investment in early stage startups is largely about the team, the uniqueness of the idea and the capability and expertise of the research team. But what drew her in most was Zhang. “She was this brilliant founder, with a very organic desire to create an impact,” said Melton. “She felt like it was her calling.”
Using system learning to recognize patterns that would otherwise go undetected by the human eye can speed up the process while creating a bigger and better feedback loop, said Melton. “We’re rethinking how drug discovery is done, and we’re rethinking how therapeutics are developed.”