Assistant professor @OhioStateSurg. Designing new strategies to treat pancreatic cancer patients with #immunotherapy. PhD trainee advocate. Tweets are my own.

Columbus, OH
Joined August 2022
Gunderlab retweeted
THE BREWERS WIN THE PENNANT The full call of the final out from @JLevering4, as heard on the Brewers Radio Network
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Gunderlab retweeted
THIS IS A MASTERPIECE
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Gunderlab retweeted
🔊 Listen to the roar of the @Brewers faithful as Jackson Chourio walks it off! 🎥 @GEICO #BallparkCam
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at ucsf
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The FIRST 4-Peat in NL Central History 🏆🏆🏆🏆
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In case you missed it… Last night, American Family Field was led by 102-year-old World War II veteran Sverre Vinje in God Bless America on the 25th anniversary of 9/11. Incredible moment in Milwaukee.
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Excited to share our new review in @CellCellPress. We propose fibrosis is a reversible state encoded in chromatin circuits shaped by immune-stromal crosstalk, and that rewiring this logic may offer durable therapeutic paths. @GladstoneInst authors.elsevier.com/sd/arti…
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NEW content online! The long return on discovery science in cancer therapeutics dlvr.it/TVCjdd
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Gunderlab retweeted
We need to rev it up. Cancer vaccines. nature.com/articles/d41586-0… @Nature
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Gunderlab retweeted
Important changes coming to how @NIH reports scores on reviewed grants - while individual reviewers will still provide an overall impact score, the investigators will only receive information on which of three broader categories their grant falls under: grants.nih.gov/grants/guide/…
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The biotech era debuted in the 1980s, and this is the type of lab the NIH thought a single R01 could support. Using the NIH entry-level postdoctoral stipend as a consistent benchmark, a single R01 with $250,000 in annual direct costs could theoretically pay for about 15.6 postdoc-years in 1987, when the stipend was $15,996 per year. How about today? At the FY2026 stipend of $63,480 per year, that same $250,000 would pay for only about 3.9 postdoc-years. This means that while a single R01 could theoretically support the equivalent of about 3 entry-level postdocs over 5 years in 1987, it could support fewer than one (one for four years) today—a roughly 75% loss in personnel purchasing power. And, of course, this assumes that every dollar goes directly to postdoc stipends. It does not include fringe benefits, PI salary, graduate students, technicians, supplies, equipment, animals, core-facility fees, travel, publication charges, or any of the other costs required to run a modern laboratory. Same nominal R01. Roughly one-quarter of the scientific labor.
The Simpsons debuted in 1987 and this is the type of house the shows creators thought a single-income family could afford. According to an episode in Season 1, Homer made 25k a year(60k in 2026 dollars). In 1987 that house would cost about 100k(which was the national average) with a mortgage of roughly $700/month(assuming 20% down and interest rates consistent with that time) How about today? The same house would cost 450k with a mortgage of roughly $2,500/month. This means that while Homer was spending ~30% of his income on his mortgage in 1987 he would need to spend closer to 50% of his income on his mortgage today. And of course, this doesn't include other areas of inflation such as food, gas or etc.
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Gunderlab retweeted
New preprint from Maitra Lab alumni @FredrikThege @SonjaWoermann (Congratulations!) Targeting AXL Overcomes Adaptive Resistance to KRAS Inhibition in KRAS-Driven #LungCancer and #PancreaticCancer biorxiv.org/content/10.64898… Next - KRASi + AXLi combination trials to sustain responses.
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Excited to share our new study @ScienceMagazine by the fantastic Raphael Mattiuz and @jboumelha @SinaiImmunol showing how DC build and sustain tertiary lymphoid structures in cancer. A major step toward enhancing anti-tumor immunity (1/2) science.org/doi/10.1126/scie…
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Gunderlab retweeted
How science works according to Nobel Prize winner Thomas Südhof: Very often, politicians think that you can tell scientists what they’re supposed to discover. You can’t! Scientists don’t know what they are going to discover. They have to try things. They have to have curiosity and ideas, but they also have to have the knowledge to try things. Very often, it leads to nothing; it’s a waste. But we didn’t know when we started it’s a waste. But when something does work. When something clicks, it is exciting and rewarding but it’s never just one click. You get a result on it, you’re hopeful, you build on it. Maybe it’s confirmed you’re even more hopeful. So it’s an incremental process. It is never one thing - boom we discovered a major thing, my god this is it. It is more like walking up a flight of stairs where each step counts and the higher up the stairs you go the better you can see what’s on top and become excited about what’s there and how you can use.
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Part-2: Should NIH cap the number of simultaneous RPGs per PI? Grant concentration is real. Question is what we should do about it. Lorenz curve doesn’t take sides, it simply shows the shape of the current system. 𝘍𝘰𝘳 𝘳𝘦𝘧𝘦𝘳𝘦𝘯𝘤𝘦: 𝘎𝘪𝘯𝘪=0 𝘪𝘴 𝘱𝘦𝘳𝘧𝘦𝘤𝘵 𝘦𝘲𝘶𝘢𝘭𝘪𝘵𝘺, 𝘸𝘩𝘦𝘳𝘦𝘢𝘴 1 𝘪𝘴 𝘤𝘰𝘮𝘱𝘭𝘦𝘵𝘦 𝘪𝘯𝘦𝘲𝘶𝘢𝘭𝘪𝘵𝘺. Here’s more data, draw your own conclusions: ▪️NIH RPG funding has a Gini coefficient of 0.47. Compare that to U.S. income inequality of ~0.49. That doesn’t tell us whether concentration is good or bad. But it tells us that it’s real. ▪️Top 10% of PIs receive 35% of all RPG funding. The bottom 50% share 19% ▪️Curve quantifies concentration. It does not tell us whether concentrated funding produces more scientific impact than broader distribution. ▪️ It also does not capture the collaborative nature of modern science. Many highly funded investigators are connected through multi-PI (MPI) grants (& shared research programs) rather than working in isolation. ▪️NIH estimates that capping at 3 grants/PI would free up roughly $2B, enough to support ~3,000 additional investigators. Does today’s distribution best serve the future of biomedical research, or would broader access produce a stronger research ecosystem? NIH is now asking the community exactly that. RFI in first comment 🚨If you have an opinion now is the time to share it. Deadline: Aug 03. - - - - - Plot Source: NIH RePORTER 𝘷𝘪𝘢 @Jori_health - - - - -
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Gunderlab retweeted
Jennifer Doudna won the Nobel Prize for gene editing and went on Bloomberg to say the chatbots everyone is betting on cannot innovate at all. Every promise Silicon Valley is making about AI curing disease just hit the one person qualified to check it. She has spent her whole career inside the actual frontier of curing disease. So when she talks about what AI can and cannot do in biology, she is not guessing. She is reporting from inside the lab. Her words were blunt. She is not seeing chatbots innovate. They summarize data. They write reports. They do not come up with a brand new idea nobody has ever had. Then the interviewer pushed. So you're saying AI can't innovate? Doudna did not flinch. She does not know if it can't. She just does not see it doing it right now. This lands harder when you remember who is making the opposite case. Sam Altman says AI will eliminate disease within five years. Larry Ellison says AI will cure cancer in a 48 hour window. An OpenAI executive even floated that the company should get a cut of sales on any drug discovered through ChatGPT. Doudna answered that in two words. Good luck. Even the cancer specialists Altman is selling to keep warning that cancer is not one disease but hundreds, each needing its own cure, and that compute does not skip the years of lab work. Her reason is simpler. Biology is hard. You cannot simulate your way to an understanding of the human body. The people promising cures are the ones selling the tool. The person who actually won a Nobel building them is telling you it has not happened yet. Source: Bloomberg Originals Watch the full video on their official channel.
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