In #JPM2023 news, $DNA Ginkgo Bioworks also presented in January 11, 2023. Jason Kelly, one of the co-founders and CEO was the one leading the presentation.
An impressive list of customers and partners, big and small. I didn't know that Moderna was one of them. Also a few "Confidential partners" in the different segments.
Emphasis on the flywheel accelerating, generating millions of data points which inform the AI/ML efforts. If you don't have a large proprietary dataset, then your AI/ML outcome will look no different than the guy next door.
"Ginkgo does not develop their own therapeutics", but enabling the customers, Ginkgo can be in any modality, such as Cell Therapy, Gene Therapy, Small molecule, Biologics, Microbiome, RNA Tx and vaccines.
Examples in Cell Therapy, with mammalian and cell engineering investments, e.g. the new facility in Boston.
Here CAR libraries with 101x101x101 modules generating millions of possibilities. Enrichment with high affinity and low affinity.
Gene Therapy, all work via partners.
Gene Editing, with a huge microbiome genome collection at Ginkgo. CRISPR-like systems in the public data (NCBI), more than 10x bigger in the Ginkgo database. "Small piece of a lot of pies" model here, CRO, Amazon AWS model, etc.
Enzymes services: turn-key service, includes a Merck deal for biocatalysts (enzymes) improvements. Structural and ML models informed by all the EC data that Ginkgo has been accumulating; better economics, better deals for partners.
Circular RNA (circRNA): acquisitions of Circularis, excited about making RNA delivery stable, dialling up expression, etc. Two methods of circularization: Catalytic introns vs hairpin ribozymes, and how they compare to polyA mRNA.
Biosecurity: Synthetic Biology is a national priority for the US. Some parallelisms with biofoundries and silicon foundries: we are already deep in the "chips war" with the Taiwan/China angle, and the US government things in similar strategic terms with biofoundries.
Also Biosecurity applications such as: look at a sequence of DNA and try to determine if it's been engineered or not. Analogy to satellites and weather forecast: same here for infectious diseases and viral surveillance.
And finally a wink at the generative AI world with asking ChatGPT what's more important: atoms or bits, and here Ginkgo is building the world of atoms (biological entities) for the future.
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On library prep at #Nanoporeconf, a description for PCR-free methods showing the difference between ligation (max output) and rapid mode (10minutes, minimal lab equipment needed). Ultralong reads (ULR) also enabled, all Kit14.
Rapid ULR. Current record is about 4 megabases.
PCR expansion kits enable the use of samples with low input amount.
I did a deep dive on the different workflow management (WFM) tools for #Bioinformatics Data Analysis a few years ago, and since then there have been a few extra entrants in this segment, still mostly concentrated in serving the Next-Generation Sequencing field.
A few years ago, there were two communities dominating the open-source WFM ecosystem in NextFlow and SnakeMake, and two platforms dominating the the commercial offerings in DNAnexus and Illumina BaseSpace.
Since then, a company out of the founders of Nextflow has started offering enterprise support for Nextflow workflows in the cloud: Seqera Labs. They offer the extra level of support that some organizations require to run Nextflow on their Data Analysis setups.
More interesting Next-Generation Sequencing knowledge in the ASeq Discord channel (by @new299). Illumina patterned flowcells and the etching process to "print" the wells into the flowcell. Could be down to 350nm diameter for some flowcell configurations now.
If I remember correctly, Illumina started with a 600nm diameter for the patterned flowcell, in the HiSeq X and then later on in the evolution of the platform that used these patterned flowcells.
They then said to have gone down to 500nm, and what you are showing seems to indicate that it's at 350nm now, at least for the NextSeq 2000? I am not sure if they claimed that for NovaSeq X?
There have been some acquisitions in #CancerDiagnostics and #CancerScreening recently, some of which signify a trend towards consolidation that is worth describing:
$A Agilent is moving towards some more vertical integration in Cancer Dx and Cancer screening
by recently acquiring both announcing a partnership with Akoya Bio and announcing the acquisition of Avida Biomed.
Some may ask: isn’t $A Agilent too small to go into this field? Would they be able to compete against $ILMN Illumina/GrailBio or $GH Guardant Health or $EXAS Exact Sciences?
It is likely that as Spatial Biology tools become more robust and user-friendly, they will become increasingly popular and widely adopted in the scientific community.
This may lead to a shift in the balance between single-cell and Spatial Biology approaches, with the latter eventually becoming more prevalent.
Additionally, as more and more datasets are generated using Spatial Biology techniques, the field of Machine Learning and Artificial Intelligence will likely play an increasingly important role in analysing and interpreting this data.