Bsky is, believe it or not, still the place to be. The mood has shifted, sure. Scientific X is gone -- remember its algo sinks posts with links, so effectively you can't share articles there.

Live Webinar: April 24, 9 AM PST | 12 PM EST. Accelerating Protein Structure Prediction and Visualization: Scalable Workflows with Nextflow. Speakers: Darren Ames, Head of Solution Science DNAnexus, and Eric Talevich, VP of Bioinformatics DataXight

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What explains the difference in conclusions between Scale AI / Secure Bio and Active Site? Different lab flows being assessed, or a hint of incentives and selection bias?

I'll give a webinar talk April 24th, covering:
- nf-core/proteinfold (AlphaFold2, ESMFold, etc.)
- Molstar/Mol*
- what comes before and after them

This kicks off a series on molecular modeling using open-source tools on DNAnexus.

I wrote about how I write code for clinical use, as of 2026:
etal.github.io/2026/03/30/v...

Briefly:
- Claude Code in one terminal, zsh in another
- Papers and docs in a browser
- Plugins: feature-dev, serena, python-lsp, explanatory-output-style
- Lots of deterministic tools.

I have been listening to the Hubermann-JB podcast. It is 4 hours, so it will take some time to finish, but here are some thoughts...

Regeneron Acquires 23andMe Assets for $256M to Expand Consumer Genomics and Data-Driven Drug Discovery

Regeneron picks up the 23andMe dataset -- one of the best possible outcomes, I think. REGN has a stellar track record of handling patient data responsibly and effectively, e.g. UK Biobank, Geisinger Health.
www.biopharmatrend.com/post/1252-re...

www.savensf.com/take-action

Gut feeling: AAV is probably out aside from what is already at the clinical stage in pipelines; LNP with various payloads is probably the future, and there might be a lull in between while scientific gaps get figured out.

Tracing the Shared Foundations of Gene Expression and Chromatin Structure The three-dimensional organization of chromatin into topologically associating domains (TADs) may impact gene regulation by bringing distant genes into contact. However, many questions about TADs' fun...

Bio foundation models are great design and engg tools. But can they help decode the fundamental principles of life?

We harnessed a single-cell FM for decoding the long-debated relationship between genome arch. and gene coregulation. 1/

Preprint here: www.biorxiv.org/content/10.1...

To be fair, there was some chicanery and sloppy work happening under LDT's lighter scrutiny, per @annaleighclark.bsky.social

Whereas, the LDT route allows easier commercial ramp-up from research use only (RUO) to CAP/CLIA-certified lab-developed tests (LDT), requiring technical/analytical validation of the new test on banked samples but not patient recruitment. Faster, less overhead, lower reimbursement. Stepstone to IVD.

The rule was seen as unfair by both academic medical centers and biotech startups because it would have essentially required a clinical trial to bring any new test to market. Only the biggest existing players can afford to do that, and it takes a long time to build up to that point.

American Clinical Laboratory Association v. U.S. Food and Drug Administration, 4:24-cv-00479 - CourtListener.com Docket for American Clinical Laboratory Association v. U.S. Food and Drug Administration, 4:24-cv-00479 — Brought to you by Free Law Project, a non-profit dedicated to creating high quality open legal...

A district court has struck down the FDA's Final LDT rule, which would have required clinical test developers to navigate full FDA IVD approval to bring new products to market -- a much tougher bar to clear.

Tl;dr: Diagnostics biz isn't dead.

Source: www.courtlistener.com/docket/68802...

Element Bio says this on-instrument hybrid capture approach can bring total library prep time down from 12-24 hours to as little as 5 hours (before sequencing). That faster TAT should be great for NGS diagnostics.

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Deprioritizing posts with links is probably a deal-breaker for scientists on X. (On top of all the other stuff.)

It's critical to
1. choose the right market, and then
2. bring a working product to that market, in the right way, considering pricing and reimbursement.

For GT in particular, patients sometimes hold out because you usually only get one shot at a cure.

Scientifically, there's some bitter irony there because CRISPR gene therapies / gene editing therapies "ought" to be able to anything a cell therapy can do, but more directly. But they're not ready yet.

AstraZeneca adds ‘in vivo’ cell therapy capabilities with EsoBiotech deal The pharma is paying up to $1 billion to buy the Belgian startup, whose technology it sees as useful in treating cancer and autoimmune conditions.

Cell therapies, on the other hand, might actually be doing OK. For example: www.biopharmadive.com/news/astraze...

Maybe the clinical endpoints are more compelling in cancer and autoimmune diseases. Maybe the tech just works better.

Roche overhauls Spark gene therapy unit, recording $2.4B in full impairment Roche has recently launched a “fundamental reorganization” of Spark Therapeutics, the gene therapy unit the Swiss pharma bought for $4.3 billion in 2019. | Roche has recently launched a “fundamental r...

Roche deems Spark Therapeutics, a flagship gene therapy company, has fizzled with a US$2.4bn write-off. Luxturna didn't sell well, surprisingly.

I hadn't thought gene therapies were in a bubble but it seems like a broader correction is happening. www.fiercepharma.com/pharma/roche...

Evidence Aggregator: AI reasoning applied to rare disease diagnostics Retrieving, reviewing, and synthesizing technical information can be time-consuming and challenging, particularly when requiring specialized expertise, as is the case of variant assessment for rare di...

New preprint! We worked with @msftresearch.bsky.social and @broadinstitute.org to see whether large language models (LLMs) can be useful to variant scientists in deciding whether genetic variants seen in a patient are responsible for their disease. tl;dr yes they can: www.biorxiv.org/content/10.1...

What a great resource! Python developer tooling has matured a lot over the past decade.

E.g. say you have an in-house notebook that supplements the NGS analysis you get from laava. You decide during development that you'd like to copy in one of laava's plots and maybe tweak it. With Quarto that could be a more seamless copy-paste, versus Jupyter <> Rmarkdown.

The reporting mechanism would also benefit from using Quarto. I have various notebooks to create plots using both Python and R from the same LAAVA output data, and while Jupyter and Rmarkdown can be multilingual, for the purpose of generating and remixing visual reports, Quarto handles it better.

Ideally I'd translate the Bash scripts to Python, convert it all into a proper Python package, and refactor. But modern Python packaging handles CLI scripts in a quirky way that I worry might harm the experience for developers who wear other hats most of the time. Still worth doing, but not today.

The motivation for making it modular and easy to modify is that some parameters deserve studies to tune properly, particularly the read mapping parameters. Even the choice of minimap2, bowtie2, or maybe megablast is worth evaluating.

I focused on the developer experience in this release. The codebase now supports multiple entry points fairly smoothly: portable Nextflow, Form Bio GUI, docker image, a Bash script mirroring each process in the workflow, and a Python quasi-package (with room for improvement).

Standardized Nomenclature and Reporting for PacBio HiFi Sequencing and Analysis of rAAV Gene Therapy Vectors Despite recombinant adeno-associated viruses (rAAVs) being the leading platform for gene therapy, there is a lack of standardized computational analysis methods and reporting to assess the contents of...

Here's the preprint manuscript describing how this work came about and what it's for: www.biorxiv.org/content/10.1...

Release v4.0.0 · formbio/laava What's Changed Functional changes: Handle mITR/wtITR directionality for scAAV classification via new input "mitr_label" (#70) Output aggregate summary tables for reporting (#67) Add version number...

LAAVA 4.0 is out! Get the latest on GitHub:
github.com/formbio/laav...

Long-read AAV Analysis (LAAVA) is an open-source bioinformatics pipeline that reports on AAV vector genome integrity using a standardized, published nomenclature and read classification scheme. 🧵