Engine Biosciences expands its digital drug discovery pipeline with $43M round

Drug discovery is a large and growing field, encompassing both ambitious startups and billion-dollar Big Pharma incumbents. Engine Biosciences is one of the former, a Singaporean outfit with an expert founding crew and a different approach to the business of finding new therapeutics, and it just raised $43 million to keep growing.

Digital drug discovery in general means large-scale analysis of biological data like genes, gene expression, protein structures, binding sites, things like that. Where it has hit a wall in the past is not on the digital side, where any number of likely molecules or processes can be generated, but on the next step, when those notions need to be tested in vitro. So a new crop of biotech companies have worked to integrate these aspects.

Engine does so with a pair of tools it has dubbed NetMAPPR and CombiGEM. NetMAPPR is a huge sort of search engine for genes and gene interactions, taking special note of “errors” that could provide a foothold for a molecule or treatment. CombiGEM is like a mass genetic testing process that can look into thousands of gene combinations and edits on diseased cells simultaneously, providing quick experimental confirmation of the targets and effects proposed by the digital side. The company is focused on anti-cancer drugs but is looking into other fields as they become viable.

Image Credits: Engine Biosciences

The focus on gene interactions sets their approach apart, said co-founder and CEO Jeffrey Lu.

“Gene interactions are relevant to all diseases, and in cancers, where we focus, a proven approach for effective precision medicines,” he explained. “For example, there are four approved drugs targeting the PARP enzyme in the context of mutation in the BRCA gene that is changing cancer treatment for millions of people. The fundamental principle of this precision medicine is based on understanding the gene interaction between BRCA and PARP.”

The company raised a $10 million seed in 2018 and has been doing its thing ever since — but it needs more money if it’s going to bring some of these things to market.

“We already have chemical compounds directed toward the novel biology we have uncovered,” said Lu. “These are effectively prototype drugs, which are showing anti-cancer effects in diseased cells. We need to refine and optimize these prototypes to a suitable candidate to enter the clinic for testing in humans.”

Right now they’re working with other companies to do the next step up from automated testing, which is to say animal testing, to clear the way for human trials.

The CombiGEM experiments — hundreds of thousands of them — produce a large amount of data as well, and they’re sharing and collaborating on that front with several medical centers throughout Asia. “We have built what we believe to be the largest data compendium related to gene interactions in the context of cancer disease relevance,” said Lu, adding that this is crucial to the success of the machine learning algorithms they employ to predict biological processes.

The $43 million round was led by Polaris Partners, with participation by newcomers Invus and a long list of existing investors. The money will go toward the requisite testing and paperwork involved in bringing a new drug to market based on promising leads.

“We have small molecule compounds for our lead cancer programs with data from in vitro (in cancer cells) experiments. We are refining the chemistry and expanding studies this year,” said Lu. “Next year, we anticipate having our first drug candidate enter the late preclinical phase of development and regulatory work for an IND (investigational new drug) filing with the FDA, and starting the clinical trials in 2023.”

It’s a long road to human trials, let alone widespread use, but that’s the risk any drug discovery startup takes. The carrot dangling in front of them is not just the possibility of a product that could generate billions in income, but perhaps save the lives of countless cancer patients awaiting novel therapies.

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The buzzy biotech Verve is gearing up to test a gene-editing treatment that could cure heart disease. The CEO shares his 3-step vision for the one-and-done heart treatment.

Summary List PlacementA Cambridge, Massachusetts biotech chasing the goal of curing heart disease just announced the first treatment it plans to test in people.
Verve Therapeutics’ lead experimental therapy, dubbed VERVE-101, aims to slash bad cholesterol levels and effectively cure patients with a serious genetic heart disease by editing a tiny piece of their DNA. Verve CEO and cofounder Dr. Sekar Kathiresan told Business Insider that’s the first part of his three-step strategy in transforming how heart disease is treated.
“Ultimately, this medicine, if effective and safe, will be a one-and-done for heart attack,” Kathiresan said.
Verve is set to be one of the leading — if not the first — biotechs to begin testing cutting-edge gene-editing technologies in humans to treat heart disease. Other biotechs have started testing CRISPR-based treatments for the genetic blood disorders sickle cell disease and beta-thalassemia.
Kathiresan, a prominent cardiologist, founded Verve while working as a researcher at the Broad Institute and Massachusetts General Hospital. After a lifetime of studying the heart and its related genetics, Kathiresan resigned from his positions to lead Verve, which was incubated by GV, formerly known as Google Ventures, from 2016 to 2018. 
Over the last two years, Verve has raised more than $120 million in seed and Series A rounds led by GV. The company now has 53 employees, with plans to grow to about 80 workers in the next two years, Kathiresan said. Most of the hiring will be for clinical research and manufacturing roles, he added. 
New data shows sustained cholesterol drop in monkeys, further building enthusiasm for gene-editing research
The biotech’s first experimental treatment was built using tools from the biotech Beam Therapeutics called base editing technology. It’s a more precise way to edit genes, allowing scientists to change a single letter of genetic code.
In this case, VERVE-101 aims to change an A to a G in the code of a gene involved in regulating cholesterol levels, called PCSK9. That single infusion should permanently lower someone’s bad cholesterol levels. 
Verve’s first study will enroll patients with heterozygous familial hypercholesterolemia, a genetic heart disease that affects about 1.6 million people in the US and Europe, Kathiresan estimated.
These patients have abnormally high levels of LDL, or bad cholesterol from birth, which often result in overworked arteries. The ultimate result is young patients, often in their 30s or 40s, having heart attacks, strokes, and sometimes even dying. 
The technology isn’t ready to be tested in people. Verve will focus in 2021 on completing the necessary toxicology studies and lab work to set the stage for human testing to begin in 2022, Kathiresan said.
Even as the technology remains a ways away from potentially reaching large numbers of patients, excitement is clearly building in the space.
Verve’s partner Beam, for instance, went public in February 2020 at a valuation of more than $1 billion. Less than a year later, Beam’s stock has increased more than 350%, with the biotech now worth well over $5 billion, despite having no treatments ready for testing in people.
Verve’s latest monkey data, released Tuesday morning, should further bolster enthusiasm. Initial data, presented in June 2020, showed the technology could effectively block genes to dramatically lower cholesterol levels in monkeys.
“This could be the cure for heart disease,” Dr. Michael Davidson, a cardiovascular surgeon not involved in the research, told The New York Times.
In Tuesday’s update, Verve showed that cholesterol drop of 61% was sustained six months out and counting, based on results from four monkeys. These are the first monkey studies to show a prolonged benefit from the base-editing technology, Kathiresan said.
The long-term goal is to develop a one-and-done treatment that can prevent heart attacks
The company’s long-term vision is to tackle cardiovascular disease, the leading cause of death in the US. The initial work in patients with this genetic heart condition is the first of three steps, Kathiresan said.
“Step two and step three are even more exciting,” he added. 
The second phase will expand research to anybody with atherosclerotic heart disease, a group that Kathiresan estimated at about 24 million people in the US and Europe. That’s a condition in which plaque builds up in arteries, narrowing them and potentially blocking blood flow or causing them to break.
The third step is the most ambitious: testing a gene-editing program as a preventive therapy for anyone at risk of heart attack. This would require a sizable amount of safety data in humans, Kathiresan acknowledged — data that doesn’t yet exist at any level for base-editing treatments. 
In chasing that ambitious vision, Verve will soon need to raise more capital. Kathiresan declined to say if Verve plans take advantage of a red-hot IPO market and go public this year.
“We’re in the process of thinking through what those additional raises are going to be like,” he said. “That’s probably all I want to say right now on that topic.”Join the conversation about this story » NOW WATCH: We took a 1964 Louisiana literacy test and failed spectacularly

Big pharma is using AI and machine learning in drug discovery and development to save lives

Summary List PlacementThe pharmaceutical industry has been slow-moving when it comes to adopting digital health technology, and pharma companies overall have taken a long time to implement AI and machine learning strategies — making broad-scale digital transformation difficult.

There is ample opportunity for drug discovery and development, but it relies on the ability of companies to implement advanced health tech into everyday strategies. 
While the healthcare industry is rapidly adopting digital tech, the pharma industry is lagging on digital maturity, and any measures even early movers are taking to catch up are patchworked due to a lack of strategy and digital-focused leadership.
AI & Machine Learning in the Drug Development Process
An incredible amount of time and money goes into drug development — bringing a drug to market costs about $2.8 billion dollars over 12+ years, according to Taconic Biosciences’ tally.  
Utilizing AI and machine learning can help at every stage of the drug discovery process. Healthcare AI startups were able to raise over  $2 billion in Q3 2020, and those using AI to streamline the drug making process were the recipients of some of the heftiest sums compared with startups deploying the tech in other healthcare segments.
AI in Drug Discovery (Phase I)
The drug discovery process ranges from reading and analyzing already existing literature, to testing the ways potential drugs interact with targets. According to Insider Intelligence’ AI in Drug Discovery and Development report, AI could curb drug discovery costs for companies by as much as 70%.
AI in Preclinical Development (Phase 2)
The preclinical development phase of drug discovery involves testing potential drug targets on animal models. Utilizing AI during this phase could help trials run smoothly and enable researchers to more quickly and successfully predict how a drug might interact with the animal model.
AI in Clinical Trials (Phase 3)
After making it through the preclinical development phase, and receiving approval from the FDA, researchers begin testing the drug with human participants. Overall, this is a four-phase process and usually considered the longest and most expensive stage in the drug making journey. 
AI can facilitate participant monitoring during clinical trials—generating a larger set of data more quickly—and aid in participant retention by personalizing the trial experience. 
Pharma Investments in AI
Big tech investments in pharma are at an all time high. Specifically, big tech firms with a broad range of AI and cloud solutions make valuable partners to drugmakers, which have varied needs when it comes to AI.

For example, Moderna leverages Amazon’s AWS cloud platform to speed up its drug development process. And while Moderna has recently made headlines as a top contestant in the race to develop a coronavirus vaccine, the company should also be recognized for its success in developing a cancer vaccine in just 40 days while leaning on AWS. 
Moderna is just one example of the many pharma companies taking advantage of Big Tech’s growing interest in the digital health industry. And Insider Intelligence expects Big Tech to continue using their AI brawn to forge pharma tie-ups.
Here are the companies analyzed in the report:

AbbVie
Amazon
Apple
AstraZeneca
Atomwise
Biofourmis
Eli Lilly
Exscientia
Google
Insilico
Litmus Health
Microsoft
Moderna
Novartis
Otsuka
Pfizer
Recursion Pharmaceuticals
Repurpose.AI
Roche
Sanofi
TriNetX
Verily
Verisim
XtalPi

Interested in getting the full report? Here’s how you can gain access:

Join other Insider Intelligence clients who receive this report, along with thousands of other Digital Health forecasts, briefings, charts, and research reports to their inboxes. > > Become a Client
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