Daniel Bryan Goodman

Why test #celltherapies one-by-one when you can use multiplexed #SynBio, #proteinengineering & #ML to design, measure & track them at scale? The Goodman Lab @PennMedicine opens July 2025. We’re hiring Specialists & Postdocs! Apply @ bit.ly/42BnJNJ RTs appreciated!🙏

Yeah, well, it turns out grandma figured out all of the analysis methods for single-cell RNA-seq. 1/

I am so excited to share our new paper in @Nature: the first programmable, site-specific integration of a large DNA payload into T cells in vivo. A single IV injection results in therapeutic levels of TRAC-targeted CAR T cells in multiple models. #Ack1" target="_blank" rel="nofollow noopener">nature.com/articles/s4158… a 🧵

Excited to share this milestone from @FaunaBio - the first Target Designation in our obesity collaboration with Lilly. Efforts spanning AI platform design, target selection, and in vivo validation uncovered genuinely novel biology from animals to treat human disease 🚀 businesswire.com/news/home/2026…

How specific are therapeutic monoclonal antibodies, really? In our new paper, @Yile_Dai led a collaboration with Adimab to profile 174 FDA-approved and clinical-stage mAbs against 6,172 human extracellular proteins. What we found surprised us.🧵 sciencedirect.com/science/articl…

@hhlee I've always wanted to give my kids the Young Lady's Illustrated Primer from the Diamond Age. Maybe we're almost there!

It’s time to homeschool

Ok this is ridiculous. Everything here could have been done without ChatGPT 1. The dog is on conventional immunotherapy with the mRNA vax 2. It appears the mRNA vaccine started WITH ICI, so we can’t know if the vax had ANY additional effect 3. The team can’t say what ~~AI~~ identified the neoantigens (no, not AF3). It sounds like they used existing sequence homology workflows. 4. No evidence of antigen-specific effect from mRNA vax - the authors need to prove this before anyone can believe the neoantigen selection had any effect 5. The in-kind contributions here are ~$20-50k. Custom cancer vax isn’t cheap Custom mRNA cancer vaccines have been in development for years! None have been clear, resounding successes (yet). Once we have Phase 3 PFS/OS, not N=1 anecdotes, we can start having arguments about people being denied access to effective treatments by unnecessary regulation Right now, the only thing people are denied are the opportunity to fork over $50k for hope and dreams. Should we really make it easier for people exploiting desperation to sell unproven remedies? If you don’t want to think before you tweet, ask the fucking AGI if any of these claims are remotely plausible and what evidence you’d need to believe them

2x Claude usage for the next 2 weeks. Did the timezone math for you.

@hhlee @Penn @ChildrensPhila 8 months in and I’m still floored by the brilliant, humble, mission-focused scientists at Penn and CHOP. It’s the most collaborative and collegial environment I’ve seen. Everyone is pulling together for patients and the future of medicine. Excited to be part of what comes next.

Does anyone know why @Penn @ChildrensPhila seem to be such a powerhouse for new genetic therapies? Why are we not talking about this more? Re-read this and wow, more of this please: chop.edu/news/worlds-fi… cc @dbgoodman

The empty drops you threw out in your single-cell RNA sequencing analysis might be hiding mysterious things 👀 check out our bioRxiv preprint! The empty drops do not contain cells. Yet we can still use them to learn interesting things about biology and technology. 1/

OK this thing is totally insane. Before going to bed I... * used try to make a new qmdresearcher directory * told my pi to read this github repo and make a version of that for the qmd query-expansion model with the goal of highest quality score and speed. Get training data from tobi/qmd github. * woke up to +19% score on a 0.8b model (higher than previous 1.6b) after 8 hours and 37 experiments. I'm not a ML researcher of course. I'm sure way more sophisticated stuff is being done by real researchers. But its mesmerizing to just read it reasoning its way through the experiments. I learned more from that than months of following ml researchers. I just asked it to also make a new reranker and its already got higher base than the previous one. Incredible.

I'm very excited to announce my official appointment as Chair of the Department of Systems Biology at @Columbia @ColumbiaMed @ColumbiaSysBio. Looking forward to more SysBio growth in NY! systemsbiology.columbia.edu

@srikosuri We are all Brutus on the eve of Philippi, reading currents we cannot fully see.

“There is a tide in the affairs of men Which, taken at the flood, leads on to fortune; Omitted, all the voyage of their life Is bound in shallows and in miseries. On such a full sea are we now afloat; And we must take the current when it serves, Or lose our ventures.”

Finding new medicines is getting more and more expensive, and AI won't help much unless we can generate physiological data at scale. In our new preprint, @GordianBio extends the progress of the functional genomics community to run pooled in vivo screens at scale, in a way that answers questions about physiology and therapeutic potential. We show screens in mice and horses, fibrotic and degenerative disease, with a framework for physiological predictions validated in human ex vivo tissues. Very proud of @v_sontake, @vkartha88, Neety and the rest of the team. Tweetorial follows:

Excited to share yet another case study on using BAGEL 🥯👨🏻‍🍳 for protein design – this time, we are miniaturizing enzymes! 🧬✂️ Paper 📄 doi.org/10.64898/2026.… Data 💾 zenodo.org/records/188541… Code 👨‍💻 github.com/softnanolab/ba…

Aldehyde and seek: Toxic aldehydes drive exhaustion in tumor-infiltrating T cells | Science Immunology science.org/doi/10.1126/sc…

Sometimes, when you think you are ten years "ahead" in biotechnology, you are actually ten years behind. DARPA recently announced a ~$40M program to synthesize DNA directly in living cells, using pulses of light. This is a great idea! DNA synthesis is way too expensive ($0.07 per base, or thereabouts) and is the limiting ingredient for most experiments. If we could coax cells to make arbitrary sequences in situ, then we could skip the ~5 days it currently takes to order DNA from a company and clone it into cells. We could run biology experiments much faster. But the more you look into this idea, the more you'll discover that biohackers have been talking about it for, like, several decades. And not just light-based approaches, either, but also really nice ideas centered around electrical pulses or other ways to make proteins without using DNA or RNA whatsoever. We should be funding more "out of the box" ideas. Biotechnology has followed quite a linear, status quo funding cycle for the last 10+ years at least. I'm sure many of these ideas won't work out, but this whole website is a goldmine. I'm feeling inspired!: diyhpl.us/wiki/polymeras…

It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow. Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes. As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now. It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.

New paper alert 🚀 Our organism-wide single-cell ATAC-seq atlas of mammalian aging is now out in @ScienceMagazine, led by our fantastic graduate student @ziyu__lu from @RockefellerUniv! science.org/doi/10.1126/sc…

I'm really thrilled to share what I've been working on the past year! We hope this method represents a step towards democratizing single-cell screens, and helps to make it possible to run genome-wide scale experiments routinely. Check out our tweetorial and the preprint here 👇