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Why genomic pioneer Lee Hood hopes the covid-19 pandemic will make precision medicine based on personalized patient data a reality

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Jim Heath


Davis believes the key to understanding why covid affects people in such varied ways is to identify the differences between the immune systems of those who successfully fight the disease and those who succumb. Those differences could range from the simple, such as whether someone has been exposed to other coronaviruses in the past, to factors as complex as genetically determined variations in how certain cells display viral protein fragments on their surfaces for inspection by circulating immune cells. These proteins can influence how likely the immune cell is to recognize the presence of a dangerous pathogen, sound the alarm, and mobilize an army of antibodies to go on the attack.

“Now there is a flood of data, and it’s the highest quality that we’ve ever had, and also the most we’ve ever had,” Davis says. 

A boon for the science, to be sure. But will the ISB study change how patients are treated and help prepare us for future pandemics? Hood is optimistic. “This absolutely validates everything I have been arguing for the past 20 years,” he says. 

The needed tools

Hood made a major contribution to immunology early in his career, after attending medical school and getting his PhD from Caltech. He helped solve the mystery of how the body can produce roughly 10 billion varieties of antibodies, Y-shaped proteins that can bind to the outer surface of a distinctly shaped invading pathogen and destroy it with the specificity of a guided missile. 

Despite his early success, Hood recognized from the start that without major advances in technology, he would never answer the most intriguing biological questions that remained about the immune system: those revealing how it coordinates its remarkably complex collection of cell types and proteins. If immunologists were ever to understand how all these parts worked together, Hood realized, they would first need to recognize, characterize, and measure them. 

Jim Heath, president of the Institute for Systems Biology

IAN ALLEN

Hood’s Caltech lab played a key role in developing a wide range of tools, including instruments that would enable biologists to read and write sequences of amino acids, and machines that could string together DNA nucleotides (the letters of the genetic code). Perhaps most famously, in 1986 he helped invent the automated DNA sequencer, a machine able to quickly read the nucleotides in the genome and determine their order; it paved the way for the Human Genome Project, the $3 billion, 13-year effort to produce the first draft of a complete human genome. 

In the years that followed, Hood advocated for a reinvention of modern health care that relied on the new tools of molecular biology to collect data from individual patients: genome sequences, and complete inventories of proteins circulating in the bloodstream. This data could then be analyzed, using early systems of machine learning and pattern recognition to pull out interesting patterns and correlations. Insights could be harnessed to maximize a person’s health and head off diseases far earlier than previously possible. 

It all made perfect scientific sense. But nearly two decades after the Human Genome Project’s completion in 2003, and despite much progress in genomic sciences as well as in data science, Hood’s predicted revolution in health care has still not arrived. 

Hood says one reason is that the tools used to be expensive. Now, however, a genome can be sequenced for $300 or less. And, he says, researchers have gained access to computational tools “that can really integrate the data, and turn data into knowledge.” 

But the biggest roadblock is that the health-care system is inefficient and resistant to change. There’s a “lack of understanding about how important it is to get diverse types of data and integrate them,” Hood says. “Most physicians went to medical school five or 10 or 20 years ago, and they never learned anything about any of this.”

“Everybody is really busy, and changing takes time, so you have to persuade leadership as well as physicians this is in their interest,” he says. “That all turned out to be far more difficult than I ever thought it would be.” 

Pandemic lessons

These days, Hood is still pushing hard, and despite the years of frustration, he is characteristically optimistic. One reason for his renewed hope is that he finally has ready access to patients  and the money to begin his next grand experiment. 

In 2016, ISB merged with Providence Health & Services in Seattle, a massive network with 51 hospitals, billions of dollars in cash, and a hunger to develop a more robust research program. 

Soon after the merger, Hood was talking up an impossibly ambitious-­sounding campaign to start what he calls the Million Person Project. It would apply phenotyping and genetic analysis to, yes, a million people. In January 2020, Hood kicked off a pilot project, having recruited 5,000 patients, and began to sequence their genomes. 

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The hunter-gatherer groups at the heart of a microbiome gold rush

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The hunter-gatherer groups at the heart of a microbiome gold rush


The first step to finding out is to catalogue what microbes we might have lost. To get as close to ancient microbiomes as possible, microbiologists have begun studying multiple Indigenous groups. Two have received the most attention: the Yanomami of the Amazon rainforest and the Hadza, in northern Tanzania. 

Researchers have made some startling discoveries already. A study by Sonnenburg and his colleagues, published in July, found that the gut microbiomes of the Hadza appear to include bugs that aren’t seen elsewhere—around 20% of the microbe genomes identified had not been recorded in a global catalogue of over 200,000 such genomes. The researchers found 8.4 million protein families in the guts of the 167 Hadza people they studied. Over half of them had not previously been identified in the human gut.

Plenty of other studies published in the last decade or so have helped build a picture of how the diets and lifestyles of hunter-gatherer societies influence the microbiome, and scientists have speculated on what this means for those living in more industrialized societies. But these revelations have come at a price.

A changing way of life

The Hadza people hunt wild animals and forage for fruit and honey. “We still live the ancient way of life, with arrows and old knives,” says Mangola, who works with the Olanakwe Community Fund to support education and economic projects for the Hadza. Hunters seek out food in the bush, which might include baboons, vervet monkeys, guinea fowl, kudu, porcupines, or dik-dik. Gatherers collect fruits, vegetables, and honey.

Mangola, who has met with multiple scientists over the years and participated in many research projects, has witnessed firsthand the impact of such research on his community. Much of it has been positive. But not all researchers act thoughtfully and ethically, he says, and some have exploited or harmed the community.

One enduring problem, says Mangola, is that scientists have tended to come and study the Hadza without properly explaining their research or their results. They arrive from Europe or the US, accompanied by guides, and collect feces, blood, hair, and other biological samples. Often, the people giving up these samples don’t know what they will be used for, says Mangola. Scientists get their results and publish them without returning to share them. “You tell the world [what you’ve discovered]—why can’t you come back to Tanzania to tell the Hadza?” asks Mangola. “It would bring meaning and excitement to the community,” he says.

Some scientists have talked about the Hadza as if they were living fossils, says Alyssa Crittenden, a nutritional anthropologist and biologist at the University of Nevada in Las Vegas, who has been studying and working with the Hadza for the last two decades.

The Hadza have been described as being “locked in time,” she adds, but characterizations like that don’t reflect reality. She has made many trips to Tanzania and seen for herself how life has changed. Tourists flock to the region. Roads have been built. Charities have helped the Hadza secure land rights. Mangola went abroad for his education: he has a law degree and a master’s from the Indigenous Peoples Law and Policy program at the University of Arizona.

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The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan

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The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan


Over the last couple of decades, scientists have come to realize just how important the microbes that crawl all over us are to our health. But some believe our microbiomes are in crisis—casualties of an increasingly sanitized way of life. Disturbances in the collections of microbes we host have been associated with a whole host of diseases, ranging from arthritis to Alzheimer’s.

Some might not be completely gone, though. Scientists believe many might still be hiding inside the intestines of people who don’t live in the polluted, processed environment that most of the rest of us share. They’ve been studying the feces of people like the Yanomami, an Indigenous group in the Amazon, who appear to still have some of the microbes that other people have lost. 

But there is a major catch: we don’t know whether those in hunter-gatherer societies really do have “healthier” microbiomes—and if they do, whether the benefits could be shared with others. At the same time, members of the communities being studied are concerned about the risk of what’s called biopiracy—taking natural resources from poorer countries for the benefit of wealthier ones. Read the full story.

—Jessica Hamzelou

Eric Schmidt has a 6-point plan for fighting election misinformation

—by Eric Schmidt, formerly the CEO of Google, and current cofounder of philanthropic initiative Schmidt Futures

The coming year will be one of seismic political shifts. Over 4 billion people will head to the polls in countries including the United States, Taiwan, India, and Indonesia, making 2024 the biggest election year in history.

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Navigating a shifting customer-engagement landscape with generative AI

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Navigating a shifting customer-engagement landscape with generative AI


A strategic imperative

Generative AI’s ability to harness customer data in a highly sophisticated manner means enterprises are accelerating plans to invest in and leverage the technology’s capabilities. In a study titled “The Future of Enterprise Data & AI,” Corinium Intelligence and WNS Triange surveyed 100 global C-suite leaders and decision-makers specializing in AI, analytics, and data. Seventy-six percent of the respondents said that their organizations are already using or planning to use generative AI.

According to McKinsey, while generative AI will affect most business functions, “four of them will likely account for 75% of the total annual value it can deliver.” Among these are marketing and sales and customer operations. Yet, despite the technology’s benefits, many leaders are unsure about the right approach to take and mindful of the risks associated with large investments.

Mapping out a generative AI pathway

One of the first challenges organizations need to overcome is senior leadership alignment. “You need the necessary strategy; you need the ability to have the necessary buy-in of people,” says Ayer. “You need to make sure that you’ve got the right use case and business case for each one of them.” In other words, a clearly defined roadmap and precise business objectives are as crucial as understanding whether a process is amenable to the use of generative AI.

The implementation of a generative AI strategy can take time. According to Ayer, business leaders should maintain a realistic perspective on the duration required for formulating a strategy, conduct necessary training across various teams and functions, and identify the areas of value addition. And for any generative AI deployment to work seamlessly, the right data ecosystems must be in place.

Ayer cites WNS Triange’s collaboration with an insurer to create a claims process by leveraging generative AI. Thanks to the new technology, the insurer can immediately assess the severity of a vehicle’s damage from an accident and make a claims recommendation based on the unstructured data provided by the client. “Because this can be immediately assessed by a surveyor and they can reach a recommendation quickly, this instantly improves the insurer’s ability to satisfy their policyholders and reduce the claims processing time,” Ayer explains.

All that, however, would not be possible without data on past claims history, repair costs, transaction data, and other necessary data sets to extract clear value from generative AI analysis. “Be very clear about data sufficiency. Don’t jump into a program where eventually you realize you don’t have the necessary data,” Ayer says.

The benefits of third-party experience

Enterprises are increasingly aware that they must embrace generative AI, but knowing where to begin is another thing. “You start off wanting to make sure you don’t repeat mistakes other people have made,” says Ayer. An external provider can help organizations avoid those mistakes and leverage best practices and frameworks for testing and defining explainability and benchmarks for return on investment (ROI).

Using pre-built solutions by external partners can expedite time to market and increase a generative AI program’s value. These solutions can harness pre-built industry-specific generative AI platforms to accelerate deployment. “Generative AI programs can be extremely complicated,” Ayer points out. “There are a lot of infrastructure requirements, touch points with customers, and internal regulations. Organizations will also have to consider using pre-built solutions to accelerate speed to value. Third-party service providers bring the expertise of having an integrated approach to all these elements.”

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