Unleashing therapeutic biology
Creating antibody activators for key disease targets
Key targets lack drugs
Millions of patients remain untreated because drug discovery has failed to deliver therapeutics for many key disease targets.
Existing drugs lack specificity
Small molecules or peptides often have off-target interactions, resulting in intolerable side effects.
Antibodies are specific but lack activity
Antibodies can recognize their targets with exquisite specificity. However, it has been a very difficult task to find activators.
We create target-activating antibodies that unlock key challenging disease targets
We have developed our Functional Antibody Selection Technology (FAST) platform to rapidly create difficult-to-discover antibody activators for challenging and promising target classes. We focus first on key G-protein coupled receptors (GPCRs), which play a role in regulating nearly every biological area.
What makes us different?
We tackle GPCRs, the hardest target class for antibodies
Unlike other target classes, which can be activated through dimerization or clustering, GPCRs require precise adjustments to their protein structures to activate or modulate them.
We measure function not just binding: 100M antibodies at once, 100X more than others
We biologically measure individual antibodies for activity in a massively parallel fashion with our engineered yeast cells that link cell survival to antibody functional against a target.
We have enabled AI to predict activating antibodies, a first in the field
We don’t only discover rare activators. Our large, proprietary activity datasets pave the path to AI-guided antibody design.
It's not just an idea. We've already done it twice
We’ve built and derisked the platform and are currently creating activating antibodies for our internal pipeline and our partners.
We tackle GPCRs, the hardest target class for antibodies
Unlike other target classes, which can be activated through dimerization or clustering, GPCRs require precise adjustments to their protein structures to activate or modulate them.
We measure function not just binding: 100M antibodies at once, 100X more than others
We biologically measure individual antibodies for activity in a massively parallel fashion with our engineered yeast cells that link cell survival to antibody functional against a target.
We have enabled AI predict active antibodies, a first in the field
We haven’t just discovered rare activators. Using our large proprietary activity datasets , we have compiled large-scale activity data that paves the path to design.
We have created agonists for our internal programs and pharma partners
Our system works: we have discovered activators for 2 GPCRs - only 4 others have even been done before us.
Our leadership team
Discovering the next generation of antibody drugs
Overview
Platform
Pipeline
Partnerships
With experiences spanning health tech, synthetic biology, and drug discovery, Dr. Soi has spearheaded initiatives leveraging data and machine learning to drive impact for patients.
At Atomwise, as Director of Drug Discovery Data Science, he led the development of uncertainty quantification methods for deep learning models of small molecule binding as well as tools for evaluating and improving similarity-based searches for hit-to-lead generation.
At Zymergen, he managed the productionization of statistical and machine learning models that supported the company’s portfolio of high- throughput screening projects. Before that, at Grand Rounds (now Included Health) he engineered a platform enabling the scaling of machine learning for clinical outcomes models across indications for which he received a patent.
Monica has a deep background in early discovery and platform development.
At Achaogen, she led the development of a microfluidic B-cell capture and screening platform, in addition to her efforts in target development and characterization.
At Zymergen, she was project and portfolio leads for multiple teams to develop and scale cellular engineering technologies.
Lauren brings a wealth of antibody and immuno-oncology drug development experience to Abalone Bio.
At Xoma and Distributed Bio, she was behind the development of two of the most well-regarded antibody libraries used for antibody drug discovery, and she managed multiple antibody drug discovery and preclinical drug development teams.
At QLSF, she directed three pre-clinical stage bispecific antibody drug development programs for immuno-oncology.
Toshi brings over 20 years of industrial experience and expertise in antibody expression and engineering, therapeutic discovery and development, and project and departmental leadership to Abalone Bio.
Prior to joining Abalone Bio, Toshi worked at companies ranging from small startups (Bioren, acquired by Pfizer) to large multinational companies (Bayer). As VP of Discovery Research at XOMA Corporation, he was responsible for selection, engineering and characterization of multiple clinically developed antibodies. Most recently, as VP of Discovery Research at Second Genome, he helped develop therapeutics derived from the human microbiome.
Richard has been in and around startups since 2008, on both sides of the lease and term sheet, as founder, incubator manager, and venture capital principal.
His path to co-founding Abalone Bio started at UC Berkeley in Biophysics and Computer science, and wound its way through protein engineering, structural biology, and then systems biology and synthetic biology at the Molecular Sciences Institute, where he met co-founder Gustavo Pesce.
Abalone Bio grew out of an “a-ha!” moment shared with Gustavo defining a technology that uniquely combines their skillsets and experiences to meet a long-standing therapeutic need- safe and effective drugs for promising yet difficult to drug targets.