February 2024 edition

Let's untangle life science, one computation at a time.

New VR Lab Allows Scientists to Experience Life as a Molecule: "Computational Research Doesn't Seem So Bad Now”

Molecules don’t have fingers, making genAI particularly useful for the experience

At the intersection of cosplay, mainstream headgear releases, and drug discovery, a new VR lab has emerged, allowing scientists to experience life as a molecule. It turns out novel UIs may or may not lead to improved drug discovery. 

"I've never felt more stable," remarked Dr. Emily Hart, a biochemist who recently 'became' a carbon atom in a diamond lattice structure during her VR session. "Though, I must admit, being part of a rigid crystal structure made it hard to attend the lab happy hour.”

Dr. Leo Mendez, chose to experience life as an enzyme. "I've always wanted to catalyze a reaction," Mendez joked. "But I didn't expect to feel so used, attaching and detaching substrates all day. It’s demanding,” Mendez continued, “computational research doesn’t seem so bad now!” 

Participants can choose their molecular identity, from a humble water molecule to the more complex DNA strands. Once the headset goes on, they're transported into a world where they can bond with other molecules, participate in reactions, or just float around in cellular cytoplasm.

"I'm looking forward to being a lipid molecule in a cell membrane," said Dr. Hart, planning her next VR adventure. "I hear it's quite the fluid experience, though I'm worried about getting too close to the edge. I'm not exactly an adrenaline junkie.”

Doom Played on Gut Bacteria, Proving the Game Can Run on Anything

In a true story not that dissimilar to the satire above, scientists have achieved a feat that blurs the lines between biological science and simulated media. A group of researchers has successfully run the classic video game 'Doom' on a rather unconventional platform: gut bacteria.

With that said, you shouldn’t queue up quite yet, unless you have about 700 years to spare. Yes, that comes out to about 70 minutes per frame.

Want to port your go-to games to a more natural console? Start with E. coli dosed with GFP. Stack the E. coli inside of a cell wall and you’ve got yourself a starter monitor 🤯.

What Does ‘24 Look Like in Life Science Software?

Many (among others, including ourselves in our Life Science Software Landscape 🖼️) have recently weighed in on how they see AI radically altering biotech and drug discovery.

Investors A16Z have made predictions of where AI will provide value in all of the following focus areas - excerpt from their excellent article on “AI Jobs to be Done in Life Sciences” below:

1. Human Pathway Biology: AI is revolutionizing hypothesis generation and prioritization in scientific discovery by automating literature reviews, experimental data analysis, and hypothesis generation. This could lead to vastly improved capabilities in research, with AI Scientists aiding in experimental design, data analysis, and the establishment of a continuous learning loop for faster discovery cycles.
2. Therapeutic Area (TA) Selection and Pipeline Prioritization: AI's ability to synthesize vast amounts of data can significantly aid in selecting therapeutic areas and targets, a critical decision-making process for biotech and pharma companies.
3. Preclinical Development: AI is set to disrupt every aspect of preclinical drug development, from target discovery to final formulation. Innovations in AI are already showing promise in reducing discovery and development timelines, with potential breakthroughs in protein design, structure prediction, and medicinal chemistry.
4. Clinical Development: Integrating AI into clinical development could dramatically reduce the time and cost associated with drug development. AI can improve clinical trial design, patient selection, and data analysis, enhancing the efficiency and success rates of trials.

Learn to 100x Your -Omics Workflows With Our Variant Calling With NVIDIA Parabricks and GATK Webinar

Deep Origin and MILRD have partnered to host a half-day Virtual Training Project (VTP) on variant calling with GATK & NVIDIA Parabricks. Learn to use GPU-accelerated algorithms to speed your genomics workflows by up to 100X!

VTP participants will receive step-by-step training:

• Calling single nucleotide small indel variants with NVIDIA Parabricks and GATK.
• Processing diverse datasets, including human whole exome tumor-normal pairs (SEQC2, Illumina), microbial whole genomes (Mason and Venkateswaran labs, Illumina), and pharmacogenomic diagnostic panels (CariGenetics, ONT PromethION 48).
• Downstream analysis and visualization, including annotation, filtering, and visualization.

Each VTP participant will also receive:

• Example datasets and scripts for variant calling with Parabricks.
• Support from expert mentors.
• Compute credits to use Parabricks to analyze your own data in the Deep Origin platform.

If you’ve already signed up we’ll reach out to confirm and get you fully set up in the coming days.

As an early subscriber, take your pick of swag!

Empire or rebellion? Cat, dog, or hamster? T-shirt or mug? Respond to our email and we’ll ship you swag of your choice to anywhere in the continental US. Present swag choices include a black or white unf*ck life sciences t-shirt or mug. 

Who is Deep Origin?

Deep Origin is a tech-for-bio startup specializing in helping scientists navigate the engineering and operations challenges in life sciences R&D - handling the SciOps so companies, startups, and researchers can focus on the science, and developing unique physicochemical simulations and AI for interrogating biology at the atomistic scale. Committed to pushing the boundaries of science, Deep Origin strives to empower scientists to speed up the process of and improve collaboration in drug discovery.