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Genesis Therapeutics raises $52M A round for its AI-focused drug discovery mission

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Sifting through the trillions of molecules out there that might have powerful medicinal effects is a daunting task, but the solution biotech has found is to work smarter, not harder. Genesis Therapeutics has a new simulation approach and cross-disciplinary team that has clearly made an impression: the company just raised a $52 million A round.

Genesis competed in the Startup Battlefield at Disrupt last year, impressing judges with its potential, and obviously others saw it as well — in particular Rock Springs Capital, which led the round.

Over the last few years many companies have been formed in the drug discovery space, powered by increased computing and simulation power that lets them determine the potential of molecules in treating certain diseases. At least that’s the theory. The reality is a bit messier, and while these companies can narrow the search, they can’t just say “here, a cure for Parkinson’s.”

Founder Evan Feinberg got into the field when an illness he inherited made traditional lab work, as an intern at a big pharma company, difficult for him. The computational side of the field, however, was more accessible and ended up absorbing him entirely.

He had dabbled in the area before and arrived at what he feels is a breakthrough in how molecules are represented digitally. Machine learning has, of course, accelerated work in many fields, biochemistry among them, but he felt that the potential of the technology had not been tapped.

“I think initially the attempts were to kind of cut and paste deep learning techniques, and represent molecules a lot like images, and classify them — like you’d say, this is a cat picture or this is not a cat picture,” he explained in an interview. “We represent the molecules more naturally: as graphs. A set of nodes or vertices, those are atoms, and things that connect them, those are bonds. But we’re representing them not just as bond or no bond, but with multiple contact types between atoms, spatial distances, more complex features.”

The resulting representation is richer and more complex, a more complete picture of a molecule than you’d get from its chemical formula or a stick diagram showing the different structures and bonds. Because in the world of biochemistry, nothing is as simple as a diagram. Every molecule exists as a complicated, shifting 3D shape or conformation where important aspects like the distance between two carbon formations or bonding sites is subject to many factors. Genesis attempts to model as many of those factors as it can.

“Step one is the representation,” he said, “but the logical next step is, how does one leverage that representation to learn a function that takes an input and outputs a number, like binding affinity or solubility, or a vector that predicts multiple properties at once?”

That’s the work they’ve focused on as a company — not just creating a better model molecule, but being able to put a theoretical molecule into simulation and say, it will do this, it won’t do this, it has this quality but not that one.

Some of this work may be done in partnerships, such as the one Genesis has struck up with Genentech, but the teams could very well find drug candidates independent of those, and for that reason the company is also establishing an internal development process.

The $52M infusion ought to do a lot to push that forward, Feinberg wrote in an email:

“These funds allow us to execute on a number of critical objectives, most importantly further pioneering AI technologies for drug development and advancing our therapeutics pipeline. We will be hiring more top notch AI researchers, software engineers, medicinal chemists and biotech talent, as well as building our own research labs.”

Other companies are doing simulations as well and barking up the same tree, but Feinberg says Genesis has at least two legs up on them, despite the competition raising hundreds of millions and existing for years.

“We’re the only company in the space that’s working at the intersection of modern deep neural network approaches and biophysical simulation — conformational change of ligands and proteins,” he said. “And we’re bringing this super technical platform to experts who have taken FDA-approved drugs to market. We’ve seen tremendous value creation just from that — the chemists inform the AI too.”

The recent breakthrough of AlphaFold, which is performing the complex task of simulation protein folding far faster than any previous system, is as exciting to Feinberg as to everyone else in the field.

“As scientists, we are incredibly excited by recent progress in protein structure prediction. It is an important basic science advance that will ultimately have important downstream benefits to the development of novel therapeutics,” he wrote. “Since our Dynamic PotentialNet technology is unique in how it leverages 3D structural information of proteins, computational protein folding — similar to recent progress in cryo-EM — is a nice complementary tailwind for the Genesis AI Platform. We applaud all efforts to make protein structure more accessible such that therapeutics can be more easily developed for patients of all conditions.”

Also participating in the funding round were T. Rowe Price Associates, Andreessen Horowitz (who led the seed round), Menlo Ventures, and Radical Ventures.

Lyron Foster is a Hawaii based African American Musician, Author, Actor, Blogger, Filmmaker, Philanthropist and Multinational Serial Tech Entrepreneur.

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Ars online IT roundtable today: What’s the future of the data center?

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Ars online IT roundtable today: What’s the future of the data center?

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If you’re in IT, you probably remember the first time you walked into a real data center—not just a server closet, but an actual raised-floor data center, where the door wooshes open in a blast of cold air and noise and you’re confronted with rows and rows of racks, monolithic and gray, stuffed full of servers with cooling fans screaming and blinkenlights blinking like mad. The data center is where the cool stuff is—the pizza boxes, the blade servers, the NASes and the SANs. Some of its residents are more exotic—the Big Iron in all its massive forms, from Z-series to Superdome and all points in between.

For decades, data centers have been the beating hearts of many businesses—the fortified secret rooms where huge amounts of capital sit, busily transforming electricity into revenue. And they’re sometimes a place for IT to hide, too—it’s kind of a standing joke that whenever a user you don’t want to see is stalking around the IT floor, your best bet to avoid contact is just to badge into the data center and wait for them to go away. (But, uh, I never did that ever. I promise.)

But the last few years have seen a massive shift in the relationship between companies and their data—and the places where that data lives. Sure, it’s always convenient to own your own servers and storage, but why tie up all that capital when you don’t have to? Why not just go to the cloud buffet and pay for what you want to eat and nothing more?

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Transforming the energy industry with AI

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For oil and gas companies, digital transformation is a priority—not only as a way to modernize the enterprise, but also to secure the entire energy ecosystem. With that lens, the urgency of applying artificial intelligence (AI) and machine learning capabilities for optimization and cybersecurity becomes clear, especially as threat actors increasingly target connected devices and operating systems, putting the oil and gas industry in collective danger. The year-over-year explosion in industry-specific attacks underscores the need for meaningful advancements and maturity in cybersecurity programs.

However, most companies don’t have the resources to implement sophisticated AI programs to stay secure and advance digital capabilities on their own. Irrespective of size, available budget, and in-house personnel, all energy companies must manage operations and security fundamentals to ensure they have visibility and monitoring across powerful digital tools to remain resilient and competitive. The achievement of that goal is much more likely in partnership with the right experts.

MIT Technology Review Insights, in association with Siemens Energy, spoke to more than a dozen information technology (IT) and cybersecurity executives at oil and gas companies worldwide to gain insight about how AI is affecting their digital transformation and cybersecurity strategies in oil and gas operating environments. Here are the key findings:

  • Oil and gas companies are under pressure to adapt to dramatic changes in the global business environment. The coronavirus pandemic dealt a stunning blow to the global economy in 2020, contributing to an extended trend of lower prices and heightening the value of increased efficiency to compensate for market pressures. Companies are now forced to operate in a business climate that necessitates remote working, with the added pressure to manage the environmental impact of operations growing ever stronger. These combined factors are pushing oil and gas companies to pivot to new, streamlined ways of working, making digital technology adoption critical.
  • As oil and gas companies digitalize, the risk of cyberattacks increases, as do opportunities for AI. Companies are adding digital technology for improved productivity, operational efficiency, and security. They’re collecting and analyzing data, connecting equipment to the internet of things, and tapping cutting-edge technologies to improve planning and increase profits, as well as to detect and mitigate threats. At the same time, the industry’s collective digital transformation is widening the surface for cybercriminals to attack. IT is under threat, as is operational technology (OT)—the computing and communications systems that manage and control equipment and industrial operations.
  • Cybersecurity must be at the core of every aspect of companies’ digital transformation strategies. The implementation of new technologies affects interdependent business and operational functions and underlying IT infrastructure. That reality calls for oil and gas companies to shift to a risk management mindset. This includes designing projects and systems within a cybersecurity risk framework that enforces companywide policies and controls. Most important, they now need to access and deploy state-of-the-art cybersecurity tools powered by AI and machine learning to stay ahead of attackers.
  • AI is optimizing and securing energy assets and IT networks for increased monitoring and visibility. Advancements in digital applications in industrial operating environments are helping improve efficiency and security, detecting machine-speed attacks amidst the complexity of the rapidly digitalizing operating environments.
  • Oil and gas companies look to external partners to guard against growing cyberthreats. Many companies have insufficient cybersecurity resources to meet their challenges head-on. “We are in a race against the speed of the attackers,” Repsol Chief Information Officer Javier García Quintela explains in the report. “We can’t provide all the cybersecurity capabilities we need from inside.” To move quickly and address their vulnerabilities, companies can find partners that can provide expertise and support as the threat environment expands.

Cybersecurity, AI, and digitalization

Energy sector organizations are presented with a major opportunity to deploy AI and build out a data strategy that optimizes production and uncovers new business models, as well as secure operational technology. Oil and gas companies are faced with unprecedented uncertainty—depressed oil and gas prices due to the coronavirus pandemic, a multiyear glut in the market, and the drive to go green—and many are making a rapid transition to digitalization as a matter of survival. From moving to the cloud to sharing algorithms, the oil and gas industry is showing there is robust opportunity for organizations to evolve with technological changes.

In the oil and gas industry, the digital revolution has enabled companies to connect physical energy assets with hardware control systems and software programs, which improves operational efficiency, reduces costs, and cuts emissions. This trend is due to the convergence of energy assets connected to OT systems, which manage, monitor, and control energy assets and critical infrastructure, and IT networks that companies use to optimize data across their corporate environments.

With billions of OT and IT data points captured from physical assets each day, oil and gas companies are now turning to built-for-purpose AI tools to provide visibility and monitoring across their industrial operating environments—both to make technologies and operations more efficient, and for protection against cyberattacks in an expanded threat landscape. Because energy companies’ business models rely on the convergence of OT and IT data, companies see AI as an important tool to gain visibility into their digital ecosystems and understand the context of their operating environments. Enterprises that build cyber-first digital deployments similarly have to accommodate emerging technologies, such as AI and machine learning, but spend less time on strategic realignment or change management.

Importantly, for oil and gas companies, AI, which may have once been reserved for specialized applications, is now optimizing everyday operations and providing critical cybersecurity defense for OT assets. Leo Simonovich, vice president and global head of industrial cyber and digital security at Siemens Energy, argues, “Oil and gas companies are becoming digital companies, and there shouldn’t be a trade-off between security and digitalization.” Therefore, Simonovich continues, “security needs to be part of the digital strategy, and security needs to scale with digitalization.”

To navigate today’s volatile business landscape, oil and gas companies need to simultaneously identify optimization opportunities and cybersecurity gaps in their digitalization strategies. That means building AI and cybersecurity into digital deployments from the ground up, not bolting them on afterward.

Download the full report.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

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Soci raises $80M for its localized marketing platform

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Soci, a startup focused on what it calls “localized marketing,” is announcing that it has raised $80 million in Series D funding.

National and global companies like Ace Hardware, Anytime Fitness, The Hertz Corporation and Nekter Juice Bar use Soci (pronounced soh-shee) to coordinate individual stores as they promote themselves through search, social media, review platforms and ad campaigns. Soci said that in 2020, it brought on more than 100 new customers, representing nearly 30,000 new locations.

Co-founder and CEO Afif Khoury told me that the pandemic was a crucial moment for the platform, with so many businesses “scrambling to find a real solution to connect with local audiences.”

One of the key advantages to Soci’s approach, Khoury said, is to allow the national marketing team to share content and assets so that each location stays true to the “national corporate personality,” while also allowing each location to express  a “local personality.” During the pandemic, businesses could share basic information about “who’s open, who’s not” while also “commiserating and expressing the humanity that’s often missing element from marketing nationally.”

“The result there was businesses that had to close, when they had their grand reopenings, people wanted to support that business,” he said. “It created a sort of bond that hopefully lasts forever.”

Khoury also emphasized that Soci has built a comprehensive platform that businesses can use to manage all their localized marketing, because “nobody wants to have seven different logins to seven different systems, especially at the local level.”

The new funding, he said, will allow Soci to make the platform even more comprehensive, both through acquisitions and integrations: “We want to connect into the CRM, the point-of-sale, the rewards program and take all that data and marry that to our search, social, reviews data to start to build a profile on a customer.”

Soci has now raised a total of $110 million. The Series D was led by JMI Equity, with participation from Ankona Capital, Seismic CEO Doug Winter and Khoury himself.

“All signs point to an equally difficult first few months of this year for restaurants and other businesses dependent on their communities,” said JMI’s Suken Vakil in a statement. “This means there will be a continued need for localized marketing campaigns that align with national brand values but also provide for community-specific messaging. SOCi’s multi-location functionality positions it as a market leader that currently stands far beyond its competitors as the must-have platform solution for multi-location franchises/brands.”

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