Sergey Menis is seen outside on a sunny day with a colorful landscape of mountains behind him, Sergey is standing to the left with his arms crossed, looking into the camera
Sergey Menis developed the nanoparticle platform that underpins a promising HIV vaccine candidate. The nanoparticle Menis designed snaps together with a protein, eOD-GT8, which is optimized to stimulate production of the rare antibodies that can eventually become bnAbs.
Courtesy of Sergey Menis

Amazon scientist Sergey Menis contributes to development of vaccine approach against HIV

"I hope we have accelerated HIV vaccine development by providing findings that we and others can build on."

About 16 years ago, Sergey Menis was volunteering at a protein design lab during the day and parking cars at night. He'd come to the Baker Lab in Seattle on a whim. While earning his master's degree in bioinformatics at Chalmers University of Technology in Sweden, he read a 2003 paper describing the lab's work designing a novel protein that didn't exist in nature.

"I was just in awe of that power," Menis recalled. He wanted to learn more about biochemist David Baker's work and emailed asking to join the lab, which is based at the University of Washington. Once there, he opted to work with Bill Schief, a postdoctoral researcher with Baker who was just starting his own lab. But Schief noticed Menis wasn't fully present in his work — he often seemed sleepy. What was going on?

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Menis explained about the night job at the car park. He wanted to do more at the lab, but after all, he had to pay rent. Schief asked how much Menis needed to cover his expenses. Then he hired him.

That job was a turning point.

Schief and his team, along with Menis, developed a breakthrough approach to a vaccine for HIV. In February 2021, the nonprofit scientific research organizations IAVI and Scripps Research announced exciting results in a phase 1 clinical trial — called IAVI G001 — of the Schief lab's vaccine candidate. A phase I trial represents the first time a vaccine is tested in humans, one step in what is typically a four-phase process that determines its safety, efficacy, and proper dosage. In this case, the promising vaccine produced the desired immune response in 97% of participants.

HIV vaccine approach succeeds in first clinical trial

Earlier this year, building on those results, IAVI and Moderna announced that first doses had been administered in a new clinical trial of the experimental HIV vaccine. IAVI officials noted this portion of the phase 1 trial, called IAVI G002, will test the ability to prime and further mature the desired immune response using Moderna’s messenger RNA (mRNA) delivery platform used for their coronavirus vaccines. The mRNA platform enables rapid vaccine production that may dramatically accelerate the development timeline.

Guided by curiosity

Menis, who joined Amazon as a scientist in November 2020 and is now a solution architect with Amazon Web Services (AWS), hadn't set out to be a biomedical researcher, or even a scientist. "I never had a career in mind, in general," he said. "I would just follow whatever looked interesting."

As an undergrad at the University of Florida, that meant computer science. It wasn't until he had obtained his master's degree in software engineering and begun working at the defense and aerospace company Lockheed Martin that he started to rethink his career path.

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Writing software for government contract projects was fine, but it didn't feel hands-on enough. "I wanted to see more feedback and results, faster," Menis said.

He recalled a bioinformatics elective class that he'd taken while in grad school at the University of Central Florida. On another fateful impulse, he decided to look at bioinformatics grad programs; this time in Europe, as he was in search of a change of scenery. He got accepted to Chalmers University of Technology and, without knowing much about the university, headed to Sweden.

"Even though it's a well-known school in certain circles, I wasn't even sure it was a real school until I arrived there," he said, laughing. "But it turned out to be a fantastic school and a really intense program."

And when he read about David Baker's work in inventing a protein molecule from scratch, the next chapter of his career — computational protein design — began to unfold.

HIV: a formidable foe

Human immunodeficiency virus has infected more than 75 million people and killed more than 32 million since the epidemic began in early 1980s. With the isolation of the virus in the mid-1980s, it seemed that a vaccine was in the offing. But conventional approaches, which involve taking some inactivated part of the virus to stimulate an immune response, have not worked for HIV.

The virus has multiple wily strategies it employs to hide within the body. It cloaks itself with sugars that make it nearly invisible to the human immune system. And its surface is always changing, a series of disguises that fool most enemy antibodies. But researchers have identified a ray of hope buried within the immune system: the potential to make bnAbs, which can recognize and defeat 99% of HIV strains.

Sergey Menis is seen in a lab setting, wearing gloves while holding a device
Sergey Menis said when he read about David Baker's work in inventing a protein molecule from scratch, the next chapter of his career — computational protein design — began to unfold.
Courtesy of Sergey Menis

The problem is, people don't develop bnAbs until they're years into an infection. “That's too little, too late," Menis said. "By the time you've actually started developing the responses you need, you're already productively infected."

The strategy researchers are pursuing is to initiate the process of making these potent antibodies before infection occurs, giving the body a head start. To do so, they must identify the right "baby antibodies," as Menis calls them, and train them to be bnAbs.

Given that the human body has the ability to make an estimated 1 quintillion unique antibodies, finding and training the right ones is a needle-in-the-haystack endeavor. And only certain antibodies have the ability to become bnAbs—those baby antibodies are literally one in a million.

Only a small fraction of people with HIV develop the most potent bnAb response — the kind an effective vaccine would elicit — on their own. Researchers have been able to zero in on these antibodies by analyzing blood from HIV-positive donors. But there's good news, and the recent clinical trial confirmed it.

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"Nearly everyone in the world should have the cells needed to start the process of producing this immune response," Menis said. "To get that process started, we need to find them, stimulate them, and have them multiply."

Building a vaccine platform

After Menis began working at Baker Lab, he decided to pursue a PhD in biochemistry at the University of Washington in the Schief lab. Menis moved to San Diego midway through his PhD studies when Schief moved his lab to Scripps Research and IAVI.

"Sergey is very thoughtful and calm, with meticulous attention to detail. He is curious about how things work," said Schief, who is executive director of vaccine design for IAVI’s Neutralizing Antibody Center (NAC) at Scripps Research and a professor in the Department of Immunology and Microbiology at Scripps.

Schief advised Menis on his PhD thesis, during which Menis developed the nanoparticle platform that underpins the HIV vaccine candidate. The nanoparticle Menis designed snaps together with a protein, eOD-GT8, which is optimized to stimulate production of the rare antibodies that can eventually become bnAbs. The eOD-GT8 protein was developed primarily by another PhD student in the Schief lab, Joe Jardine. The nanoparticle amplifies the body's response by delivering multiple copies of eOD-GT8.

A computer image of the eOD-GT8 immune-stimulating protein.
A computer image of the eOD-GT8 immune-stimulating protein.
Courtesy of Sergey Menis

"It's spherical, like a virus, so the immune system treats it as if it might be a virus of some kind," Menis said. "We want to make it look like a little virus, even though it has no infectious properties whatsoever."

Menis served as the Schief lab's subject matter expert during the multi-year process of developing the vaccine candidate. "He played a big role in planning and carrying out the clinical trial," Schief said.

A team effort

Both Menis and Schief are careful to emphasize that there is much more to do before an approved HIV vaccine becomes reality. While the results from IAVI G001 are encouraging, there are significant milestones remaining.

"By demonstrating that this concept works in humans, and actually can work very well in terms of eliciting strong and consistent responses of the kind we wanted, I hope we have accelerated HIV vaccine development by providing findings that we and others can build on," Schief said.

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Menis is also quick to credit the 48 volunteers who participated in the IAVI G001 clinical trial, noting that without such volunteers, a vaccine wouldn’t be possible. "They are the co-creators of this effort," he said. Schief and Menis also praised the work of many other individuals, particularly colleagues at Fred Hutch, George Washington University, and the NIH Vaccine Research Center.

The upcoming IAVI G002 will recruit 56 volunteers across four sites: GWU School of Medicine and Health, Hope Clinic of Emory Vaccine Center in Atlanta, Fred Hutchinson Cancer Research Center in Seattle, and the University of Texas–Health Science Center at San Antonio. The goal: replicate the priming of “baby antibodies” observed in IAVI G001 and teach them to take a step towards becoming a bnAb capable of neutralizing HIV.

An intriguing offer

Menis was working at IAVI and preparing to go on vacation when Amazon contacted him in 2020, asking whether he'd be interested in a position at the company. The hiring process happened quickly: He did an interview while on the trip, and on his first day back from vacation, he had an offer in his inbox.

"When Amazon reached out, I was really intrigued by the possibilities of what a giant like Amazon could be doing," Menis said. "I was open to discovering what that meant."

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After spending a little over a year as a research scientist, Menis moved into a senior product manager role with Amazon Diagnostics and then transitioned into a role as a solution architect with AWS, building solutions for healthcare and life sciences startups. “For me, the roles represent opportunities to learn and be curious,” Menis said, citing one of Amazon’s leadership principles.

He admitted he didn’t know much about the principles until his first job interview, but now he has come to appreciate them. He enjoys seeing how they relate to him and his past work.

“Working at Amazon has been a learning experience,” he says — yet another on the journey from lab volunteer to medical-breakthrough-creating scientist to whatever the next chapter will be.

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Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the International Emerging Stores organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team Central Machine Learning team works closely with the IES business and engineering teams in building ML solutions that create an impact for Emerging Marketplaces. This is a great opportunity to leverage your machine learning and data mining skills to create a direct impact on millions of consumers and end users.
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Amazon continues to develop its advertising program. Ads run in our Stores (including Consumer Stores, Books, Amazon Business, Whole Foods Market, and Fresh) and Media and Entertainment publishers (including Fire TV, Fire Tablets, Kindle, Alexa, Twitch, Prime Video, Freevee, Amazon Music, MiniTV, Audible, IMDb, and others). In addition to these first-party (1P) publishers, we also deliver ads on third-party (3P) publishers. We have a number of ad products, including Sponsored Products and Sponsored Brands, display and video products for smaller brands, including Sponsored Display and Sponsored TV. We also operate ad tech products, including Amazon Marketing Cloud (a clean-room for advertisers), Amazon Publisher Cloud (a clean-room for publishers), and Amazon DSP (an enterprise-level buying tool that brings together our ad tech for buying video, audio, and display ads). Key job responsibilities This role is focused on developing core models that will be the foundational of the core advertising-facing tools that we are launching. You will conduct literature reviews to stay on the current news in the field. You will regularly engage with product managers and technical program managers, who will partner with you to productize your work.