Daniel Bryan Goodman

Immuno/Synth Bio/ML. PI @PennMedicine/@parkerici. Using DNA synth, multiplex assays & generative models to understand & engineer immune cells. @geochurch alum.

[Daniel Bryan Goodman @dbgoodman]

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 @ https://t.co/DE7aPLp9vr
RTs appreciated!🙏

[Lior Pachter @lpachter]

Sean Eddy developed profile HMMs in the 1990s, ultimately leading to his HMMER project, which includes JackHMMER that AlphaFold relies on. Apparently his work has been determined to be "of absolutely no value to the US taxpayer". Obviously that's not true.
https://t.co/LZgihGGnUk

[lada @ladanuzhna]

Every non-biotech person I describe Verve to is floored. They can't believe this is a future we get to live in - permanent solution for high cholesterol and strokes - even after I tell them it means editing their genes.

At the same time more than 90% of the biotech VCs I've talked to are bearish on exactly this direction.
"Why cure a disease if you can do monthly injections"
"Insurance would never cover cures"

I am excited for those people to not make any money when they are proven wrong. Its striking that no one sees that cures have been out of vogue for very silly reasons - we equated one-and-done to viral vectors, rare disease TAMs, and rare disease prices. None of those are relevant assumptions, and Lilly has multiple bets in this space to prove everyone wrong.

[Martin Borch Jensen @MartinBJensen]

@deepfates Excited to announce my new company:

[Gleb Kuznetsov @glebkuz]

Great essay that captures the nuances of what's happening on the ground in data rich biological endeavors.

We're seeing this evolve organically at @ManifoldBio. As one of the greatest data generators in the world, we've historically been bottlenecked by analysis as most of our data is some variation on next-gen DNA sequencing data. Now all scientists (not just computational) are armed with agentic systems wired up to our databases and empowered to do (read: prompt) quite advanced analyses on their own data on the scale of hours.

[Max Kozlov @maxdkozlov]

NEW: A serious staffing shortage — of the Trump admin's own making — is delaying the agency's ability to send billions to universities around the US, leaving labs reeling.

“I thought we were at rock bottom”, a senior NIH official said. “We are below rock bottom now.”

[Harris Wang @harriswangnyc]

1/ Excited to share our new paper in Science: “Toward life with a 19-amino acid alphabet through generative artificial intelligence design.” @ColumbiaSysBio @ColumbiaBME @Columbia
https://t.co/ZT3Ygw9tiG 🦠🧬🛠️🖥️💥

[Hani Goodarzi @genophoria]

Our paper with Vijay Ramani is out today in @Nature.

We show that chromatin has a richer grammar than simple "open" or "closed" DNA. Using IDLI, we read 14 nucleosome structural states across single chromatin fibers and find that this grammar is actively written by transcription factors.

[Delgoffe Lab @DelgoffeLab]

Dearest gentle reader, we are delighted to announce a new story from our lab published in @Nature describing how a meal's systemic metabolic changes are interpreted by your immune system to enhance adaptive immunity. A thread 1/ https://t.co/zACqCLxDMU

[Nadav Brandes @BrandesNadav]

Really cool work! Initial thoughts:

1. The performance leap compared to Evo2, GPN-MSA etc. is quite remarkable, but we need to remember it's a supervised approach. The gene-level split sounds reasonable, but information leakage is notoriously difficult to eliminate in supervised variant effect prediction. It remains to be seen how well it generalizes (I hope to see more comprehensive evals in the peer-reviewed version).

2. I'm a bit skeptical about the LLM-generated reports reflecting either the true disease mechanism of the variants or the true reasoning behind the Evo2 probe predictions.

3. At the same time, I will not be surprised if geneticists end up liking and using these reports, even if they are not entirely faithful. At least they attempt to provide an explanation (unlike virtually all other variant effect prediction tools), so it's an important step in a neglected direction.

4. Moreover, I'd argue that a lot of biological and clinical reasoning is already in the realm of nice-sounding storytelling and half truths, so we also need to be honest about what human-level biological interpretation is when we judge whether AI is making things better or worse.

[Gleb Kuznetsov @glebkuz]

Multiplexing can be thought of as "GPU-ification" of a complex biological system

Serial measurement becomes massively parallel

To turn biology digital, you need data at *scale* and *relevance*

The power of multiplexing is you get both.

[Prajit Rajkumar @prajitrr]

@srikosuri @OctantBio Any chance this role’s available for the fall as well👀?

[Lior Pachter @lpachter]

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

[Justin Eyquem @j_eyquem]

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.

https://t.co/t3pyjHyGWS

a 🧵

[Linda Goodman @LindaBGoodman]

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 🚀
https://t.co/dJAWs8ZsAh

[george church @geochurch]

https://t.co/EWCsKA7mVY

[Aaron Ring @aaronmring]

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.🧵

https://t.co/ONTSF60B2g

[Daniel Bryan Goodman @dbgoodman]

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

[Egan Peltan @EganPeltan]

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

[Paweł Huryn @PawelHuryn]

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