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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.

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.

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.

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.

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).

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