Radically different
The handsome new book Maintenance: Of Everything, Part One, by the tech industry legend Stewart Brand, promises to be the first in a series offering “a comprehensive overview of the civilizational importance of maintenance.” One of Brand’s several biographers described him as a mainstay of both counterculture and cyberculture, and with Maintenance, Brand wants us to understand that the upkeep and repair of tools and systems has profound impact on daily life. As he puts it, “Taking responsibility for maintaining something—whether a motorcycle, a monument, or our planet—can be a radical act.”
Radical how? This volume doesn’t say. In an outline for the overall work, Brand says his goal is to “end with the nature of maintainers and the honor owed them.”
The idea that maintainers are owed anything, much less honor, might surprise some readers. Actually, maintenance and repair have been hot topics in academia since the mid-2010s. I played some role in that movement as a cofounder of the Maintainers, a global, interdisciplinary network dedicated to the study of maintenance, repair, care, and all the work that goes into keeping the world going.
Brand is right, too, that maintainers haven’t gotten the laurels they deserve. Over the past few decades, scholars have shown that work from oiling tools to replacing worn parts to updating code bases all tends to be lower in status than “innovation.” Maintenance gets neglected in many organizational and social settings. (Just look at some American infrastructure!) And as the right-to-repair movement has shown, companies in pursuit of greater profits have frequently locked us out of being able to do repairs or greatly reduced the maintainable life of their products. It’s hard to think of any other reason to put a computer in the door of a refrigerator.
Some of Brand’s earlier work helped inspire those insights. But his new book makes me think he doesn’t see things that way. For Brand, maintenance seems to be a solitary act, profound but more about personal success and fulfillment than tending to a shared world or making it better.
Born in 1938, Brand is 87 years old. A sense hangs over the book—with its battles against corrosion, rust, and decay, with its attempts to keep things going even as they inevitably falter—of someone looking over life and pondering its end. Maintenance: Of Everything connects to every stage of Brand’s life. It’s worth reviewing where it falls in that arc. Brand has always been interested in tools and fixing things, but rarely has he focused on the systems that need the most care.
More than a half-century ago, Brand was a member of the Merry Pranksters, a countercultural, LSD-centered hippie collective famously led by Ken Kesey, the author of One Flew Over the Cuckoo’s Nest. In 1966, Brand co-produced the Trips Festival, where bands like the Grateful Dead and Big Brother and the Holding Company performed for thousands amid psychedelic light shows.
Brand’s Whole Earth Catalog had a vision that might feel progressive, but its libertarian, rugged-individualist philosophy of remaking civilization alone stood in contrast to more collective social change movements.
In some ways, the Trips Festival set a paradigm for the rest of his life’s work. Brand’s biographers have described him as a network celebrity—someone who got ahead by bringing people together, building coalitions of influential figures who could boost his signal. As Kesey put it in 1980, “Stewart recognizes power. And cleaves to it.”
Brand applied this network logic to the undertaking he will always be best remembered for: the Whole Earth Catalog. First published in 1968 and aimed at hippies and members of the nascent back-to-the-land movement, the publication had the motto “Access to tools.” Its pages were full of Quonset huts, geodesic domes, solar panels, well pumps, water filters, and other technologies for life off the grid. It was a vision that might feel progressive or left-leaning, but the libertarian, rugged-individualist philosophy of eschewing corrupt systems and remaking civilization alone stood in contrast to the more collective movements pushing for deep social change at the time—like civil rights, feminism, and environmentalism.
That vision also led straight to the empowerment that came with new digital tools, and to Silicon Valley. In 1985, Brand published the Whole Earth Software Catalog, the last of the series, and also cofounded the WELL—the Whole Earth ’Lectronic Link, a pioneering online community famous for, among other things, facilitating the trade of Grateful Dead bootlegs. He also wrote a hagiographic book about the MIT Media Lab, known for its corporate-sponsored research into new communications tech. “The Lab would cure the pathologies of technology not with economics or politics but with technology,” Brand wrote. Again, not collective action, not policymaking: tools. And Brand then cofounded the Global Business Network, a group of pricey consulting futurists that further connected him to MIT, Stanford, and the Valley. Brand had literally helped bring about the modern digital revolution.
His attention then turned toward its upkeep. Brand’s 1994 book, How Buildings Learn: What Happens After They’re Built, argued against high-modernist architectural ideas. Nearly all buildings eventually get remade, he argued, but he especially favored cheap, simple structures that inhabitants could easily retool to suit changing needs. In some ways, Brand was recapitulating the liberated—or libertarian—philosophy of the Whole Earth Catalog: People can remake their world, if they have access to tools. In a chapter titled “The Romance of Maintenance,” he asked readers to see the beauty, value, and occasional pleasures of fixer-uppers of all kinds.
This chapter was a touchstone for many of us in the academic subfield of maintenance studies. Researchers in disciplines like history, sociology, and anthropology, as well as artists and practitioners in fields like libraries, IT, and engineering, all started trying to understand the realities and, yes, romance of maintenance and repair. Brand joined and contributed to Listservs, attended conferences, chatted with intellectual leaders. So it’s a bit uncharitable when he writes that his new book is “the first to look at maintenance in general.” He knows better. The real question, though, is what his work has to teach us that others have not said before. In this first volume, the answer is unclear.
Maintenance: Of Everything, Part One is an odd book. If so much of Brand’s thinking has been about access to tools, he now asks, in a more extended way: How are our tools maintained? But where Brand began his career with a catalogue, in this volume we get … what? A digest? An almanac? An encyclopedia? Its form and riotous variety fit no genre easily.
The book has two chapters. The first, “The Maintenance Race,” recounts the story of three men who took part in the Golden Globe, a round-the-world race for solo sailors held in 1968. Each of the sailors, Brand explains, had a different philosophy of maintenance. One neglected it and hoped for the best. He died. Another thought of and prepared for everything in advance, and while he didn’t win the race, he completed it and once held the record for the “world’s longest recorded nonstop solo sailing voyage.” The final sailor won and did so through heroic acts of perseverance; his style was “Whatever comes, deal with it,” Brand explains. Structured like a fairy tale and unremittingly romantic, the story—like most of the anecdotes in the book—focuses on the derring-do of vigorous white guys. The strategy is no secret. Brand’s outline explains: “Start with a dramatic contest of maintenance styles under life-critical conditions—a true story told as a fable.” This myth is meant to inspire.
The second chapter, “Vehicles (and Weapons),” is over 150 pages long. It has five sections, multiple subsections, five subsections designated “digressions,” one called a “subdigression,” two “postscripts,” and several “footnotes” that are not footnotes in a formal sense but, rather, further addenda. At times, it all feels like notes for a future work. Brand makes no apology for the book’s woolliness. “All I can offer here,” he writes, “is to muse across a representative of maintenance domains and see what emerges.” Perhaps the most charitable reading of the potpourri is that it represents the return of a Merry Prankster, offering us a riotous varied light show. It’s a good book to leave on a table and occasionally open to a random page for entertainment. But it often seems as if it does not know what it wants to say or be.
“Vehicles (and Weapons)” begins by paraphrasing two famous works of maintenance philosophy, Robert M. Pirsig’s Zen and the Art of Motorcycle Maintenance and Matthew B. Crawford’s Shop Class as Soulcraft. Maintenance involves both “problem finding” and “problem solving.” While much repair work is marked by anxiety, impatience, and boredom, it also offers positive values and outcomes. “Motorcycle maintainers take heart from what they repair for—the glory of the ride,” Brand writes.
The beauty and triumph of cheapness is a running theme throughout the work, harking back to How Buildings Learn. Henry Ford’s Model T won out over early electric vehicles and hugely expensive luxury vehicles like Rolls-Royce’s Silver Ghost because it was cheap and easier to maintain. The three most popular cars in human history—the Ford Model T, the Volkswagen Bug, and the Lada “Classic” from Russia—all privileged cheapness, “retained their basic design for decades, and … invited repair by the owner.” Or, to be fair, maybe demanded it? For every hobbyist who delighted in being able to self-reliantly keep a VW running, there must have been thousands who appreciated how cheap it was and hated that it broke a lot. Brand never points to social research, like surveys, that might help us know people’s feelings on such matters.
Other sections recount how Americans created interchangeable parts (enabling not only cheap mass production but also easy maintenance), examine how maintenance works with assault rifles and in war, and track the history of technical manuals from the early modern period to the age of YouTube. These stories are solid, but they’re also well known to students of technology, and nearly all are recycled from the work of others, featuring many large block quotes. The volume breaks little new ground.
Brand treats maintenance as an unalloyed good. But the field of maintenance studies has moved on, burrowing into the domain’s ironies, complexities, and difficulties. A simple example: In most cases, it is environmentally far better to retire and recycle an internal-combustion vehicle and buy an electric one than to keep the polluting beast going forever. Maintaining a gas-guzzler or a coal-burning power plant isn’t a radical act but a regressive one. Also, maintenance can become a life-breaking burden on the poor, and it falls inequitably on the shoulders of women and people of color. Keeping existing systems going can be a way of avoiding tough, necessary change—like making technological systems more accessible for people with disabilities. In this volume, Brand is uninterested in such difficult trade-offs. He avoids any question of how politics shapes these issues, or how they shape politics.
This avoidance comes out most clearly in a section of “Vehicles (and Weapons)” that talks about Elon Musk—a character of “unique mastery,” Brand informs us. He tells us that Bill Gates once shorted Tesla’s stock, only to lose $1.5 billion. The lesson is clear: Elon won.
In what political and social vision is money the best way to keep the score? Brand rightly points out that electric vehicles have fewer moving parts and, in that sense, are more maintainable than internal-combustion vehicles. He celebrates Musk most of all because his products “have all proven to be game changers in part because they combine ingenious design with surprisingly low cost.” Again, it’s Brand’s “cheap, available tools” hypothesis. But there’s a real superficiality and lack of follow-through in thinking here: Teslas remain luxury vehicles whose sales have slumped since federal tax subsidies disappeared. The company has faced several right-to-repair lawsuits; there’s even a law review article on the topic. Musk is in no sense a maintenance hero. Yet Brand writes that with his companies, “Musk may have done more practical world saving than any other business leader of his time.” By the time Brand was writing this book, the controversies surrounding Musk for at least flirting with antisemitism, racism, sexism, authoritarianism, and more were quite clear. About this, the book says not a word.
For sure, Brand needn’t agree with Musk’s critics, but failing to even broach the subject is tone deaf and out of touch. Others have argued that Silicon Valley’s “Move fast and break things” mentality undermines healthy maintenance. Brand doesn’t raise the idea—even to dismiss it.
It could be that with Maintenance: Of Everything, Part One Brand is just getting going; that in subsequent volumes he’ll have something more coherent to say; that he’ll raise really hard questions and try to answer them. But given his track record, we might reasonably doubt it. Kesey said Brand cleaves to power; he certainly doesn’t question it.
Lee Vinsel is an associate professor of science, technology, and society at Virginia Tech and host of Peoples & Things, a podcast about human life with technology.
Thousands of genes are expressed differently in the brains of men and women, researchers have discovered.
The findings could help explain differences in neurodevelopmental, psychiatric, and neurodegenerative disorders between the sexes.
While men are more likely to experience schizophrenia, attention deficit hyperactivity disorder, and Parkinson’s disease, women are more prone to mood disorders and Alzheimer’s disease.
The U.S. study, in Science, is the first systemic single-cell survey of sex differences in gene expression across multiple regions of the human brain.
“Together, these findings provide a comprehensive map of molecular sex differences in the human brain and offer initial insight into their underlying mechanisms and potential functional consequences,” Alex DeCasien, PhD, from the National Institute of Mental Health in Bethesda, Maryland, told Inside Precision Medicine.
DeCasien and co-workers conducted a high-resolution analysis of gene expression in tissue samples from the brains of 15 men and 15 women using single-nucleus RNA sequencing.
They then used data from earlier large neuroimaging studies to select six cortical regions to sample, four of which showed sex-related differences in grey matter volume and two in which no such differences were found.
The team found subtle but widespread differences in gene activity between men and women. Biological sex explained very little of the variance in gene expression across the brain, at less than 1%, but differences were widespread—with more than 3000 genes showing different expression according to sex in at least one cortical region.
The greatest sex-related differences in gene expression were on the sex chromosomes. However, most of the genes showing sex-related variations in expression were autosomal—carried on one of the 22 numbered non-sex chromosomes.
The predominant driver for sex-biased expression of genes on these autosomal chromosomes were sex steroid hormones such as estrogen and testosterone.
Surprisingly, more than half the X chromosome genes in women were expressed in both alleles for at least one cell type. This indicated that many had escaped X chromosome inactivation—a female phenomenon in which one of the two X chromosomes is switched off early in development to stop women producing double the number of X-linked gene products to men.
“That finding has implications for understanding sex-biased disease susceptibility because several genes implicated in neurodevelopmental disorders reside on the X chromosome,” commented Jessica Tollkuhn, PhD, from Cold Spring Harbor Laboratory, and S Marc Breedlove, from Michigan State University, in an accompanying Perspective article.
They noted that autosomal genes showing sex-biased expression were substantially enriched for extracellular matrix components, hormone signaling pathways, and metabolic processes. “Genes with greater expression in women were enriched for mitochondrial and synaptic functions, whereas male-biased genes were associated with metabolic and structural pathways,” the editorialists added.
“By pinpointing these sexually differentiated processes, the data provide a treasure trove for the discovery of biomarkers of and/or therapeutic targets for differential disease risk in men and women.”
DeCasien and team added: “These findings raise the possibility that sex differences in gene expression modulate the magnitude of genetic effects at risk loci, contributing to differences in disease vulnerability and to reduced portability of polygenic risk prediction across sexes.”
The post Brain Gene Variations Help Explain Neurological and Psychiatric Sex Differences appeared first on Inside Precision Medicine.
The American Association for Cancer Research (AACR) Annual Meeting kicks off this weekend in San Diego. A whirlwind of sessions, keynotes, fireside chats, posters, and exhibitors, the meeting is THE annual event for the cancer community.
Before the conference, GEN spoke with AACR program chairs Paul S. Mischel, MD, Professor and Vice Chair for Research for the Department of Pathology at Stanford Medicine of Stanford University and Alice T. Shaw, MD, PhD, Chair of the Department of Medical Oncology and the Chief of Strategic Partnerships at Dana-Farber. In this interview, they share their perspectives on the event, what attendees should be looking out for, and what they, personally, are most looking forward to.
This interview has been edited for length and clarity.
GEN: What did you feel were some of the most important themes to include in the conference program?
Shaw: First of all, it’s been such an honor for me to work with Paul as well as our president, Lillian Siu, MD. We had an expert program committee and incredible staff at AACR who all helped shape the program.
This year’s annual meeting feels more meaningful than ever, because of everything going on in the world, including funding challenges, challenging geopolitics, and everything else. It has felt even more important that we have this time to bring together our global community of cancer researchers and investigators.
When Paul and I met last summer, we felt strongly that this meeting was not just about designing an incredibly strong scientific program to showcase the science and all of the innovation, but we wanted to make a point to demonstrate to the audience, and the world, the tangible benefits of scientific research to patients with cancer, and to highlight how all the research we do is done with an eye toward improving the lives of patients with cancer.
We intentionally planned a scientific program with patients and patient impact front and center and have tried to incorporate the patient perspective and even patient voices in some sessions—to emphasize that science drives impact for patients.
Mischel: When we started about a year ago, our conviction—that there probably has never been a more important year for an AACR meeting—grew over the year. This organization is a beacon of light at a time in which there’s been extraordinary progress in cancer, and [there is] the potential to really make a difference in patients’ lives at the face of some very major headwinds. What we’re seeing is a level of enthusiasm and engagement in coming together in the community that’s saying: we won’t be stopped in making a difference for patients with cancer. And there were a number of themes that were central to this meeting.
For example, precision—that you can use information about patients to identify what’s gone wrong and how to develop therapies based upon deep molecular knowledge. Partnership—The growing recognition of how we work together to make a difference for patients. It’s not a winner-take-all strategy. It’s not a race to the top for individuals. It’s a race to the top for people with cancer. And we do it effectively by joining hands to make a difference for patients. And global work—another major theme that we’re really talking about this year, because together we can make a real difference for people with cancer.
We work together with people that span an enormous range of disciplines and expertise. A number of themes came front and center during the year. The technologies to interrogate what’s happening in human beings, whether it’s in their tissue, their blood, or their images—it’s nothing short of breathtaking. The ability to either forestall cancer by detecting if it’s going to happen, or catch it early, or monitor our most effective treatments is really changing the game. New modalities for developing treatments. We’ve heard a lot about harnessing the immune system and about the development of small molecules. There’s all kinds of new chemistry, molecular glues and degraders that are leading the way. And they’re tied to deep investigations into the fundamental biology.
AI is changing the game as well. We are very excited that we’ve brought together perhaps the most interesting AI sessions that you can imagine, that talk about all of the ways that AI can be used—not like an oracle but actually in partnership with helping make a difference for patients, whether it be in the diagnostics or the development of therapeutics. AI is only beginning to be tapped to help us think about how to integrate knowledge across all of these domains. And it goes beyond that because it’s not only about the molecular composition of a person’s tumor, it’s about a human being, what they eat, where they live, what they do, and various other social determinants of health that might increase risks of cancer. A lot of attention is paid in the meeting to that aspect of it as well. So, I think we’re in for an incredibly interesting meeting.
Shaw: One of the themes that came right out from everyone on the program committee was how important it was to highlight AI; I think everyone believes that AI is going to be transformative and it’s going to impact all aspects of cancer research and clinical care in the coming years. We had a number of AI experts on our program committee. They really helped embed AI topics throughout the scientific and also the educational program.
In fact, when Paul and I were planning the opening plenary session, we really wanted one of the opening plenary speakers to be able to speak on AI. So, we have Regina Barzilay, PhD, from MIT, who’s going to speak on her work in the AI space, both in terms of drug discovery and all the way out to clinical applications. We also have an AI-focused plenary session all unto itself as well, to drive home the importance of AI tools and technologies. It is incredible how AI is already being used in terms of foundational discovery and in terms of real-world, clinical data mining and implementation. And Paul already mentioned genomics, precision medicine, biomarker discovery, histopathology, radiology, all of which are already being impacted by AI.
Mischel: One of the things that is perhaps most stunning is this idea that you might be able to prevent cancer. We already see real world examples of that with things like HPV vaccines. The work is advancing so quickly that it might be possible to build vaccines against [something] that might prevent people who are at high risk of developing cancer from getting those cancers. Our colleague and AACR President Lillian Siu, MD, has a presidential symposium focused on that. What I hope that we’re getting across is the real scale and power of the work that’s being presented and the way that it crosses so many disciplines at this meeting.
Shaw: We are going to have a large focus, as we usually do, on molecularly targeted therapies. We have several sessions on the basic research side, but also in the clinical trial sessions around targeting RAS. RAS, of course, is the most commonly mutated oncogene in human cancer and has been undruggable for decades.
In the last five to 10 years, we now finally have small molecule therapies that can target different RAS mutations. In fact, you may have just heard the news about a new RAS inhibitor, daraxonrasib from Revolution Medicines, and pivotal Phase III trial data in previously treated pancreatic cancer. This was an incredibly positive study, doubling overall survival. Not even knowing those results, though, we already had planned quite a lot around RAS.
In that context of precision therapies, I also want to mention that I’m excited about one of our discovery science plenaries on Saturday that is going to focus on minimal residual disease (MRD) in solid tumors. Here the question is, if we have such incredibly effective targeted therapies for oncogene-driven cancers like RAS, EGFR, and ALK, why aren’t we curing more patients who have these types of cancers? We believe that a lot of the reason is because we can’t eliminate every cancer cell. And if we could just understand what allows those residual cells to survive, perhaps we could eradicate those and then be on the road to curing patients who have advanced disease. So, this whole plenary will focus on the science around MRD and how that then leads to clinical applications as well.
Mischel: Fundamental science is deeply central to this process. We frame a lot of things in terms of what it means for patients’ lives. I think an important part of this meeting is also integrating how those discoveries really flow from the work in fundamental science. For example, in the opening plenary, we’re going to be hearing about how tumors change their stripes effectively to become resistant to treatments, the lineage plasticity, this idea that they adopt new states to become resistant. And then what can you do about it?
When people used to be diagnosed with terminal cancer, it meant that they were going to die soon, and now people can be diagnosed with terminal cancer and live for years. That’s stunning. And that is happening because of cancer research and the integration of cancer research all the way from the most mechanistic to the most applied. One of the deepest themes of this meeting comes into this concept of partnership, that we highlight the critical nature of each component and the integration of those components, all the way from fundamental discovery to translation to patients.
GEN: What are some of the biggest scientific challenges you’re seeing right now in cancer biology that you think people will be discussing at the meeting?
Mischel: Cancer is hard because it is evolution on steroids. The mechanism that I study—extrachromosomal DNA, the ability of cancer cells and tumors to change quickly to resist treatment—is all about that. And it comes from us; it’s our cells that have gone bad. We have to find ways to show how they’re different and target those differences. We’re getting better at it through our understanding of science.
Shaw: I am someone who sits between basic research and the clinic, so I do a lot of translational research. What the AACR meeting does well is gets at this key challenge around how we translate basic discoveries into the clinic. We all just want better cancer therapies for our patients. There are many aspects that really make the translation of discoveries difficult, and these will come out in various forms at the meeting. We’ve been talking about how hard it is to understand the biology, and to identify and validate new targets for drug discovery, for cancer treatments in the future.
I have spent some time on the industry side, so I also recognize how challenging it is, even when you have what you think is a perfect target, to drug that target. At the annual meeting, we’re going to talk a lot about different modalities, ways of thinking about going after what we believe are important targets, be it a small molecule or maybe it’s a new degrader or maybe it’s some other very complicated biologic.
I want to emphasize that to use or to identify the optimal modality requires that we understand the biology and the science behind it. The other challenge that I’ve seen in the translational space is around identifying which patients are going to benefit from a new therapy. A good example of where we’ve seen struggles is immunotherapy and identifying novel immunotherapy combinations and which ones have robust activity. But we can’t tell exactly which patients are deriving that benefit. Oftentimes with no biomarker to guide us, we can’t move forward with what could be a promising combination. At the annual meeting, we try to highlight a lot of these correlative or translational biomarker studies from early phase clinical trials.
The last thing I’ll mention is around how we use preclinical models most effectively to predict what’s going to be a promising new therapy. Often, these models are just models; they’re simpler than human cancers. They can’t recapitulate the complexity of human biology, and they can lead us the wrong way. For example, to overestimate how effective a therapy may be. Fine-tuning our models and making them as predictive as possible is a key challenge.
Mischel: Data seems to suggest that very often you might need to combine agents to make differences for patients. And that of course makes enormous sense from a biological standpoint, but it’s much harder to do when you start thinking about how you design the trials to do that. It’s a slow process. And so, there is increasing recognition of the need to figure out how to combine agents and hopefully ways to figure out how practically to begin to test them more effectively and in a more cost-effective fashion.
GEN: What have been some of the biggest advances since the last meeting?
Mischel: I just keep coming back to RAS because it’s such a big deal. An undruggable target that we’re now seeing a huge change in. It’s a huge deal.
Shaw: I would agree with that. And it’s not simply the RAS inhibitor itself. Many of us believe that that is just the start of how we most effectively treat RAS-driven cancers. We need the best RAS inhibitor to serve as an anchor and then we will build these combinations around that which will hopefully be even more effective and allow us to maximally cytoreduce or debulk cancers and then allow us to take in other even higher order combinations.
We have sessions this year all around RAS-mutant cancers. We have a designated session just focused on pancreatic cancer biology, because understanding that biology well is going to be critical to developing these types of combination approaches.
The other thing that’s exciting—and this space is always evolving—is a plenary session on innovative new therapeutic modalities. This session will focus on a couple key modalities that are already transforming the space. Antibody-drug conjugates (ADC), for example. They are basically entering every therapeutic space that we have in cancer [and] understanding of the biology around how you’re targeting certain tumor-selective antigens.
Also, the design of the ADC itself can be very, very sophisticated and can be tweaked to further enhance activity. We’ll have some great talks around the next generation of ADCs that are going to be even more effective and even safer than what we currently have.
And in that same session around innovative modalities, we’ll also have talks around immune cell engagers; also, new data and next generation immune cell engagers that have built upon the early data with the first-generation immune cell engagers. The other very innovative new therapy that we will highlight, even in more detail than last year, is around radioligand therapies—a way to selectively target tumor cells with radiation. Unlike ADCs where the payload is chemotherapy, here the payload is radiation therapy. We’ve already seen really that these radioligand therapies are incredibly important for patients; they are coming out in all different therapeutic spaces. We thought it was important to highlight the latest advances in radioligand therapies, and we also have some education sessions so that physicians and scientists understand the basics around this innovative and exciting modality.
Mischel: The concepts of glues and degraders open the therapeutic landscape in a very different way. In many ways, the landscape has been limited to enzymes that you can inhibit, and not all good cancer targets are going to be enzymes that you can inhibit, and these glues and degraders change what you can do, whether it’s getting rid of them, moving them, giving them new functions. It’s a very powerful technology that is getting ready to make an enormous difference in clinic.
Shaw: In the opening plenary session, George Winter will speak on glues and degraders. I also wanted to highlight the “New Drugs on the Horizon” sessions. We do this every year at the annual meeting. I love these sessions because they are first time disclosures of novel cancer therapies that have just entered the clinic or they’re about to enter the clinic. These talks go deep into the biology of the disease and how the drug was discovered and developed into early clinical plans. Several talks in this session this year are going to feature molecular glue degraders. That will be a nice way to tie together this theme around the degraders and the power of this new modality.
Mischel: One other thing I want to squeeze in is why on Earth are younger people getting cancer, particularly colorectal cancer? That’s really disturbing. We have sessions that are data rich that go right at that, and the answers are interesting.
GEN: Will there be any programming at the meeting that addresses the current state of funding?
Shaw: We’re fortunate that Tony Letai, MD, PhD, the NCI director, is attending and speaking at the meeting in our opening ceremony on Sunday. He’s also participating in a workshop that we’re holding on grant writing and the scientific review process. On Monday, he will give an NCI director’s address and participate in a fireside chat where I’m sure he’s going to get a lot of questions around funding.
There are also sessions within the science and health policy track at the meeting that are going to focus on federal funding of grants. There is even a researcher town hall that’s really going to talk a lot about this.
GEN: Do you have any advice for young cancer researchers that may be attending AACR for the first time?
Mischel: I have two bits of advice. One of them is to know that what you’re doing is incredibly important. You are welcome. You’re one of us, you’re important. Do what you need and go forward because the work that you’re doing is going to matter an enormous amount. The second thing is do not be afraid. Do not think that the senior people at the meeting, the “bigwigs,” are too busy for you. Do not think they do not want to meet you, because they do. You’re the future. Go up, introduce yourself, say hello, tell us who you are.
GEN: What are things you are looking forward to outside of the sessions?
Shaw: I love the AACR annual meeting because it’s such an opportunity not just to learn, but to network and reconnect with friends and collaborators who you may not have seen in a while. I also think it’s a great venue for many of us to have formal sit-down meetings with industry partners and talk through the latest data that were just presented and discuss new collaborations. I personally am looking forward to the 5K race that Paul and I are speaking at. I’m going to try to run the race! One of my sons runs marathons and I thought, well, the least I can do is try and run a 5K.
Mischel: I’m looking forward to having a drink with Alice after the meeting ends and debriefing on putting this meeting together, which has been an absolute pleasure. I wish I were running the 5K race. I’m doing an education session at that time. I’m looking forward to meeting the students. There are these brilliant young people from all around the world and they’re just at the start of their career and they draw inspiration from this meeting, and I really enjoy it when they come up to me and I get to meet them. You see the brilliance and excitement in these people’s faces. And I’m looking forward to that.
The post AACR 2026 Chairs Identify Themes and Highlights from the Conference appeared first on GEN – Genetic Engineering and Biotechnology News.
Earlier this week, Revolution Medicines reported positive results from a global Phase III trial of its RAS‑targeting inhibitor daraxonrasib (RMC-6236) in metastatic pancreatic ductal adenocarcinoma (PDAC). In the RASolute 302 trial, patients receiving daraxonrasib achieved longer progression‑free survival (PFS) and overall survival (OS) than those on standard cytotoxic chemotherapy.
The RASolute 302 trial enrolled patients with pancreatic tumors harboring a wide range of RAS variants, including those with RAS G12 mutations (such as G12D, G12V, and G12R), as well as those without an identified RAS mutation. The primary endpoints of the trial were PFS and OS in patients with tumors harboring RAS G12 mutations. Secondary endpoints assessed PFS and OS in all enrolled patients (the intent-to-treat population), including those with tumors with and without (wild type) an identified RAS mutation.
Daraxonrasib patients achieved a median OS of 13.2 months versus 6.7 months for chemotherapy. The drug was generally well tolerated, with a manageable safety profile and with no new safety signals.
“With these unprecedented results, daraxonrasib has the potential to achieve our goal of bending the mortality curve in pancreatic cancer. Unlike chemotherapy, daraxonrasib is a RAS-targeted medicine that targets RAS in its active ‘ON’ state, shutting down a key signaling pathway that drives aggressive tumor growth. This is especially important in pancreatic cancer, which is among the most RAS-driven cancers, with more than 90% of tumors harboring a RAS mutation that is the driver of the cancer,” asserted Mark A. Goldsmith, MD, PhD, CEO and chairman of Revolution Medicines.
Pancreatic cancer carries one of the highest mortality rates of any solid tumor, a consequence of late-stage diagnosis and resistance to standard chemotherapy. In the United States, recent estimates point to roughly 60,000 new cases and nearly 50,000 deaths each year. With most PDAC tumors driven by RAS alterations, the early success of emerging RAS‑targeted strategies hints at how much more may be possible as this therapeutic space continues to expand.
RAS is the key oncogenic driver of pancreatic cancer. Nearly all RAS mutations occur at KRAS position G12, but RAS mutations in other isoforms and at KRAS positions G13 and Q61 are also observed. Daraxonrasib works by suppressing RAS signaling through inhibition of the interaction between both wild-type and mutant RAS(ON) proteins and their downstream effectors.
Pancreatic cancer is the most RAS-addicted of all major cancers, with more than 90% of patients harboring tumors driven by mutations in RAS proteins. These mutations span a range of RAS variants that fuel aggressive tumor behavior. Daraxonrasib, a multi-selective inhibitor of RAS(ON) proteins, is the first investigational agent in a novel class of RAS inhibitors designed to address a diverse and broad spectrum of oncogenic RAS drivers.
“For patients with metastatic pancreatic cancer, new treatment options are urgently needed to increase survival time and improve quality of life,” said Brian M. Wolpin, MD, MPH, professor of medicine at Harvard Medical School, director of the Hale Family Center for Pancreatic Cancer Research at Dana-Farber Cancer Institute, and principal investigator for the RASolute 302 trial. “The widely anticipated results of this study indicate that daraxonrasib provides a clear and highly meaningful step forward for patients with pancreatic cancer who have experienced progression on prior treatment, typically chemotherapy. I believe that this new approach is a very important advance for the field that I expect will be practice-changing for physicians and improve the care for patients with previously treated metastatic pancreatic cancer.”
Revolution Medicines now intends to submit the drug for approval by regulatory authorities, including the U.S. Food and Drug Administration as part of a future New Drug Application, and for presentation at the 2026 American Society of Clinical Oncology Annual Meeting.
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There’s a fault line running through enterprise AI, and it’s not the one getting the most attention. The public conversation still tracks foundation models and benchmarks—GPT versus Gemini, reasoning scores, and marginal capability gains. But in practice, the more durable advantage is structural: who owns the operating layer where intelligence is applied, governed, and improved. One model treats AI as an on-demand utility; the other embeds it as an operating layer—the combination of operation software, data capture, feedback loops and governance that sits between models and real work—that compounds with use.
Model providers like OpenAI and Anthropic sell intelligence as a service: you have a problem, you call an API, you get an answer. That intelligence is general-purpose, largely stateless, and only loosely connected to the day-to-day operations where decisions are made. It’s highly capable and increasingly interchangeable. The distinction that matters is whether intelligence resets on every prompt or accumulates over time.
Incumbent organizations, by contrast, can treat AI as an operating layer: instrumentation across operations, feedback loops from human decisions, and governance that turns individual tasks into reusable policy. In that setup, every exception, correction, and approval becomes a chance to learn—and intelligence can improve as the platform absorbs more of the organization’s work. The organizations most likely to shape the enterprise AI era are those that can embed intelligence directly into operational platforms and instrument those platforms so work generates usable signals.
The prevailing narrative says nimble startups will out-innovate incumbents by building AI-native from scratch. If AI is primarily a model problem, that story holds. But in many enterprise domains, AI is a systems problem—integrations, permissions, evaluation, and change management—where advantage accrues to whomever already sits inside high-volume, high-stakes operations and converts that position into learning and automation.
Traditional services organizations are built on a simple architecture: humans use software to do expert work. Operators log into systems, navigate operations, make decisions, and process cases. Technology is the medium. Human judgment is the product.
An AI-native platform inverts this. It ingests a problem, applies accumulated domain knowledge, executes autonomously what it can with high confidence, and routes targeted sub-tasks to human experts when the situation demands judgment that the system can’t yet reliably provide.
But inverting human-AI interaction isn’t just a UI redesign—it requires raw material. It’s only possible when the platform is built on a foundation of domain expertise, behavioral data, and operational knowledge accumulated over years.
AI-native startups begin with a clean architectural slate and can move quickly. What they can’t easily manufacture is the raw material that makes domain AI defensible at scale:
Services companies already have all three. But these ingredients aren’t moats on their own. They become an advantage only when a company can systematically convert messy operations into AI-ready signals and institutional knowledge—then feed the results back into operations so the system keeps improving.
In most services organizations, expertise is tacit and perishable. The best operators know things they cannot easily articulate: heuristics developed over the years, edge-case intuitions, and pattern recognition that operate below the level of conscious reasoning.
At Ensemble, the strategy for addressing this challenge is knowledge distillation. The systematic conversion of expert judgment and operational decisions into machine-readable training signals.
In health-care revenue cycle management, for example, systems can be seeded with explicit domain knowledge and then deepen their coverage through structured daily interaction with operators. In Ensemble’s implementation, the system identifies gaps, formulates targeted questions, and cross-checks answers across multiple experts to capture both consensus and edge-case nuance. It then synthesizes these inputs into a living knowledge base that reflects the situational reasoning behind expert-level performance.
Once a system is constrained enough to be trusted, the next question is how it gets better without waiting for annual model upgrades. Every time a skilled operator makes a decision, they generate more than a completed task. They generate a potential labeled example—context paired with an expert action (and sometimes an outcome). At scale, across thousands of operators and millions of decisions, that stream can power supervised learning, evaluation, and targeted forms of reinforcement—teaching systems to behave more like experts in real conditions.
For example, if an organization processes 50,000 cases a week and captures just three high-quality decision points per case, that’s 150,000 labeled examples every week without creating a separate data-collection program.
A more advanced human-in-the-loop design places experts inside the decision process, so systems learn not just what the right answer was, but how ambiguity gets resolved. Practically, humans intervene at branch points—selecting from AI-generated options, correcting assumptions, and redirecting operations. Each intervention becomes a high-value training signal. When the platform detects an edge case or a deviation from the expected process, it can prompt for a brief, structured rationale, capturing decision factors without requiring lengthy free-form reasoning logs.
The goal is to permanently embed the accumulated expertise of thousands of domain experts—their knowledge, decisions, and reasoning—into an AI platform that amplifies what every operator can accomplish. Done well, this produces a quality of execution that neither humans nor AI achieve independently: higher consistency, improved throughput, and measurable operational gains. Operators can focus on more consequential work, supported by an AI that has already completed the analytical groundwork across thousands of analogous prior cases.
The broader implication for enterprise leaders is straightforward. Advantages in AI won’t be determined by access to general-purpose models alone. It will come from an organization’s ability to capture, refine, and compound what it knows, its data, decisions, and operational judgment, while building the controls required for high-stakes environments. As AI shifts from experimentation to infrastructure, the most durable edge may belong to the companies that understand the work well enough to instrument it and can turn that understanding into systems that improve with use.
This content was produced by Ensemble. It was not written by MIT Technology Review’s editorial staff.