TherML™ integrates CombinAbleAI’s advanced, next generation biologics expertise with insitro’s existing small molecule and oligonucleotide capabilities, unifying therapeutic design across all major drug modalities in a single AI engine
SOUTH SAN FRANCISCO, Calif.–(BUSINESS WIRE)–insitro, the AI therapeutics company built on causal biology, today announced the acquisition of CombinAbleAI and the launch of insitro’s TherML™ (Therapeutic Machine Learning) platform. The acquisition, which is expected to close in late January 2026, will complete insitro’s full stack, modality-agnostic capability spanning small molecules, oligonucleotides, antibodies, and other complex biologics with precision – enabling biology to guide both modality selection and molecular design from target discovery through developability assessment. This integrated approach accelerates the generation of clinic-ready assets while reducing late-stage development risk.
“Drug discovery has traditionally optimized molecules for potency before assessing developability – often discovering that highly potent candidates face manufacturing constraints,” said Philip Tagari, Chief Scientific Officer, insitro. “By integrating CombinAbleAI’s physics-informed, AI-driven design for complex biologic therapeutics with our causal biology platform, we treat potency and manufacturability as interdependent design criteria from the outset. This fundamentally changes the translation from biological insight to viable therapeutic – instead of optimizing sequentially and hoping for serendipitous alignment, we’re designing for both simultaneously.”
“We are delighted to welcome the CombinAbleAI team in Israel as fellow insitrocytes, alongside our colleagues in the U.S., Poland, and Malaysia,” added Daphne Koller, Ph.D., founder and CEO, insitro. “Their addition helps launch our integrated TherML platform, which is a critical part of our end-to-end industrialized AI-enabled system built for repeatable, scalable, predictable drug discovery.”
TherML supports the AI-driven design and optimization of multiple therapeutic modalities within a single platform. For complex biologics, including multi-specific antibodies and T-cell engagers, the platform utilizes CombinAbleAI’s physics-informed, AI-driven optimization engine, which is pre-trained on over 100,000 molecular dynamics surrogates to predict protein structure and flexibility with high fidelity. For small molecules, it leverages insitro’s proprietary Quantitative Adaptive Libraries to densely map chemical space and generate high-resolution local training data. For oligonucleotides, the platform employs AI and large-scale automation to industrialize the design of siRNA candidates, optimizing sequence selection and target knockdown across a diverse range of therapeutic targets. Augmented by advanced machine learning models for predicting ADMET properties – developed through insitro’s internal data as well as that from industry collaborations – TherML optimizes for drug-likeness and safety profiles alongside binding affinity.
By moving optimization for drug-like properties earlier in the workflow, TherML reduces late-stage attrition, balancing efficacy with developability. The platform is directly integrated with insitro’s automated labs, enabling rapid generation of experimental data that continuously improves predictive performance and adapts to the specific constraints of each target and modality.
“Effective therapeutic design requires optimization across affinity, selectivity, stability, and manufacturability,” said Noam Katz, Ph.D., co-founder of CombinAbleAI. “We’re very excited to join insitro and integrate CombinAbleAI’s physics-informed AI modeling into insitro’s end-to-end discovery platform to reliably and rapidly translate high-value targets into molecules that perform as intended in the real world.”
CombinAbleAI was created and incubated within AION Labs, a first-of-its kind Israeli biotech venture studio that builds AI-native drug discovery companies in close collaboration with global pharmaceutical leaders. AION Labs was founded by Merck KGaA, AstraZeneca, Pfizer, Teva, Amazon Web Services, and the Israel Biotech Fund with strategic partner Amiti Ventures, along with support from the Israel Innovation Authority as part of its bioconvergence agenda.
The CombinAbleAI team will continue to operate in Israel as a new insitro R&D center focused on advancing large molecule design.
About insitro
insitro is the AI therapeutics company built on causal biology. By generating an integrated, multimodal corpus of human and cellular data and analyzing it with machine learning, insitro’s platform aims to reveal how disease begins, progresses, and can be resolved. The company applies this approach to identify genetic drivers, prioritize targets, and design medicines intended to treat disease at its root, with programs focused in metabolic disease and neuroscience. insitro is backed by world-class investors and has raised approximately $800M in capital, including approximately $150M from non-dilutive pharma partnerships.
About CombinAbleAI
CombinAbleAI is an AI-driven biotechnology company developing an in silico platform to design and optimize therapeutic antibodies. Founded in 2023 by Dr. Daria Kokh and Dr. Noam Katz in the AION Labs Venture Studio based in Rehovot, Israel, the company applies advanced machine learning and computational molecular simulation to accelerate antibody discovery and engineering. By enabling multi-parameter optimization across key developability and efficacy attributes, CombinAbleAI aims to reduce trial and error, shorten development timelines, and improve the quality of drug candidates advancing toward the clinic.
About AION Labs
AION Labs is a first-of-its kind venture studio built by a coalition of pharma heavyweights (Pfizer, AstraZeneca, Teva and Merck), tech giants (AWS), IBF, Imiti and the Israel Innovation Authority to develop and integrate AI and computational technologies that are redefining drug discovery and development. Its unique model enables the formation of fully-backed biotech startups that are able to fast-track their path to market with funding and real-time guidance from global pharma R&D partners.
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