Abalone Bio is developing antibody drugs that target receptors on the surface of cells to treat diseases. G-protein coupled receptors (GPCRs) are important for cellular health and frequently get disrupted in disease, yet many remain undruggable by small molecules. Antibodies are also limited to only blocking, not activating, GPCRs. Abalone is changing this by finding both activating or inhibiting bioactive antibodies that target GPCRs. To discover these antibodies, Abalone is combining engineered living cells with data-driven computation, which is compatible with different types of antibodies. Abalone’s first therapeutic focus is immune system regulators that cause inflammatory diseases and cancer.

<p>Abalone Bio is developing antibody drugs that target receptors on the surface of cells to treat diseases. G-protein coupled receptors (GPCRs) are important for cellular health and frequently get disrupted in disease, yet many remain undruggable by small molecules. Antibodies are also limited to only blocking, not activating, GPCRs. Abalone is changing this by finding both activating or inhibiting bioactive antibodies that target GPCRs. To discover these antibodies, Abalone is combining engineered living cells with data-driven computation, which is compatible with different types of antibodies. Abalone’s first therapeutic focus is immune system regulators that cause inflammatory diseases and cancer.</p>


Abalone Bio

Last week I came across this great, thought-provoking report by Chris Bradbury (many kudos). It's awesome to see the evolution of AI in drug discovery! As the field matures, we're learning valuable lessons and developing increasingly powerful tools.

It’s also exciting to be at Abalone Bio as we ourselves ride the 4th wave of AI biotech: We are combining the massive, functionally relevant datasets generated by the FAST platform with cutting-edge protein language models (PLLMs), which allows us to turn prior information about structure learned through self-supervision into insights about target-relevant function. We operate in tight feedback loops that allow us to turn hits into leads. Our success in developing CB2 agonist antibodies, overcoming receptor specificity challenges, exemplifies the power of the FAST platform.

Like any good thinkpiece, I found myself nodding along a lot but also finding some differences in perspective. The report postulates that supervised learning is 3rd-wave and self-supervised is 4th-wave–implying a natural evolution from one to the next. I think this is not a function of the superiority of self-supervision but rather the reality that the scale of high-quality, relevant data needed to train PLLMs and other data-hungry models is hard to come by and using self-supervision is more pragmatic. We at Abalone are generating datasets with measurements of functional activity–not just binding–for 100’s of millions of antibodies against GPCRs allowing us to reap the benefits of supervised learning at scale.

I've noticed an uptick in skepticism about the impact of AI in drug discovery (as there should be – this is science after all). At the same time, I see an upsurge in innovation and an increased focus on finding drugs from those pushing the field forward. It's a thrilling time to be in this space, and I'm eager to connect with others who share this passion. If you feel the same way, reach out and let’s chat about the future of AI in biotech!

https://lnkd.in/gJf4GpE3

PartnershipsWe are working with top drug companies to bring them target-activating antibodies for their key targets. Learn more about collaborating with Abalone Bio.

Antibodies are transforming drug development, especially when it comes to tackling challenging targets like GPCRs (G-protein-coupled receptors). GPCRs are among the hardest target classes for antibodies because they require precise adjustments to their protein structures to activate them.

Unlike other targets that can be triggered through straightforward dimerization or clustering, GPCRs demand a unique level of precision - making antibody therapy both complex and groundbreaking.

Here at Abalone Bio we have developed our Functional Antibody Selection Technology (FAST) platform to rapidly create difficult-to-discover antibody activators to specifically and effectively drug challenging and promising target classes 🎯

Stay tuned for more updates!

The Co-Founder & CEO of Abalone Bio, Richard Yu is talking about Abalone Bio’s cutting-edge antibody modulator technologies for challenging specific GCPRs. 

These next-generation therapies aim to tackle unmet medical needs at the intersection of inflammation, fibrosis and pain. Their lead programs, including ABt285, are pioneering solutions for conditions like chemotherapy-induced peripheral neuropathy and liver fibrosis with a strong emphasis on precision and safety. ABt285 avoids psychoactive effects, the risk of metabolic side effects, and issues related to chronic use and tolerance, setting new standards in therapeutic innovation for pain and inflammation management.

Learn more about Abalone Bio here 👉 https://lnkd.in/eiftJH2Z
Explore the Bioneex platform (bioneex.com) to connect with them.

We are proud to have investors like Seth DeGroot and Adam G. at the Gravity Fund on our journey with us! 

Our FAST platform leverages engineered cells to evaluate hundreds of millions of antibodies simultaneously, assessing their ability to modify the activity of a target rather than merely binding to it.

By producing extensive sequence-activity datasets, FAST not only uncovers rare activators for challenging targets like G-protein-coupled receptors but also enables their AI-powered design.

Preclinical biotherapeutics company Abalone Bio and bioinformatics cloud platform provider PipeBio announce collaborative efforts in antibody drug discovery - PR Web


              What I’ve learned — the hard way — about AI in bio
            

 Abalone Bio’s Post 

What a week at the Antibody Engineering & Therapeutics Conference! 👏 

Here's a quick recap of key takeaways and highlights from our CEO + co-Founder Richard Yu & VP of Antibody Discovery Monica Schwartz:

🔍 Discovery Insights

-Continued focus on structure and developability.
-Broad recognition of the gap in functional activity data.
-Highlights on the importance of agonist antibody discovery.
-A critical reminder: Strong affinity isn’t enough. Improving affinity can sometimes compromise functional activation, as seen in examples from 
Triplebar and Specifica, an IQVIA business.

🧪 The Experimental Frontier:

-Even the best AI models (e.g., David Baker's lab) require testing thousands of proposed molecules to find ones that work.

-GPCRs remain a challenging target for binding-based antibodies.

💡 Sunday Workshop: 
-"Innovate, Invest, Succeed: The Business Landscape of Antibody Therapeutics" was a standout session filled with dynamic discussions and insights.

👏 Kudos to the organizers for assembling such a stellar lineup:
Jennifer Cochran, Stanford University
Jonathan Sockolosky, Curie.Bio

📢 Special thanks to the incredible presenters:
Lazar Bojic, Curie.Bio
Robin Silva, Xencor
Sarah Hymowitz, The Column Group
Alexey "Alex" Lugovskoy, Diagonal Therapeutics
Shelley Force Aldred, Rondo Therapeutics

We look forward to what 2025 has in store as we continue to push the boundaries and shaping the future of antibody therapeutics! 💡🔬

Starting the year full speed ahead at #JPM2025! If you're interested in learning more about what we're working on at Abalone Bio and how we tackle GPCRs, the hardest target class for antibodies, connect with our CEO + Co-Founder Richard Yu to set up a time to meet. See you there! 


Generation of a potent anti-PD-L1-CD47 bispecific antibody with a strong therapeutic and safety profile for cancer immunotherapy - Frontiers

Chemotherapy Induced Peripheral Neuropathy Drugs in Development & and Key Players, 2022 - GlobalData

As we approach 2025, Abalone Bio is moving forward with a new look and website! This refresh marks the next step in our mission to unlock challenging and promising drug targets with our first-in-class, data-driven, and ML-designed activating antibodies.

Check out the new site to stay updated on our latest progress: www.abalonebio.com

More to come! 🚀 

Are you going to Antibody Engineering & Therapeutics 2024? Join us December 18th at 10:30 AM to listen to our VP of Antibody Discovery Monica Schwartz talk about how Abalone Bio’s Functional Antibody Selection Technology (FAST) platform is transforming antibody drug discovery by combining biology and machine learning (ML).

FAST simultaneously tests the entire diversity of antibody libraries directly for the desired function and produces library-scale sequence-function datasets that uniquely power generative protein language models to design novel active antibody sequences. Abalone's FAST-discovered antibodies have been demonstrated to have agonist activity in vitro and in vivo.

If you'd like to set up a separate time to meet, connect with Monica or our CEO + Co-Founder, Richard Yu. See you there!

Our technology directly measures activity of all antibodies, eliminating biases from binding-based methods.

Existing large-scale discovery technologies focus on attributes like binding affinity first, largely because that is historically an easy property to score and optimize.

Activity is tested very late in the discovery process on a few high-affinity antibodies targeting regions that may have nothing to do with altering the activity of the target. It’s like tightly grabbing a pair of scissors by the blades instead of more loosely by the handle - a high affinity but non -functional interaction.

Abalone Bio

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