A London start-up called Apoha has built a prototype device, the Liquid Brain, that uses principles from brain physics to screen antibody drugs for hidden flaws before they reach human trials. Poor developability—problems like unwanted clumping or high viscosity in drug molecules—causes one third of clinical-stage failures for biologic drugs, costing roughly $450 million per drug developed. Current screening methods are too slow and sample-hungry to catch these issues early, so flawed antibodies often only reveal their problems after years of costly development. Apoha’s platform combines neuromorphic sensing and computing to evaluate multiple biophysical properties simultaneously from tiny sample volumes. With this Smart funding, Apoha will build the first site-deployable version of the Liquid Brain for use by BioTech and Pharma researchers. If successful, the platform could let drug developers weed out problematic antibodies at the hit-identification stage, reducing the time, cost, and failure rate of bringing new biologic therapies to market. That could ultimately make advanced treatments—including complex next-generation formats like multispecific antibodies and nanobodies—more accessible and affordable for patients.
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Founded in 2021 by Dr Shamit Shrivastava (experimental physicist and inventor of Apoha's core platform technology; previously postdoctoral researcher at the University of Oxford) and Anshika Srivastava (skilled in operating and scaling businesses; previously Executive Director/Vice President, Goldman Sachs), Apoha is a seed-stage start-up based in London. Our mission is to empower scientists to design materials with new functional properties inspired by the physics of brain matter. We have developed a prototype in-house neuromorphic sensing and computing platform, the Liquid Brain, for high-throughput antibody screening. During drug discovery, thousands of hit candidates are screened at the hit identification stage based on target binding affinity. However, early developability screening (i.e., evaluating key biophysical properties of potential drug candidates such as viscosity, hydrophobicity, and self-aggregation, which amongst other biophysical properties determine drug-like properties, manufacturability, and safety) remains a significant multi-parameter challenge, facing resource and time constraints, including limited sample material availability. Consequently, few hits are screened against a limited number of biophysical parameters, and antibodies with poor developability profiles frequently progress to clinical-stage development before being identified. Indeed, poor developability is responsible for one third of clinical-stage failures of biologics, costing ~USD450m/biologic developed. This already major developability challenge is only being exacerbated by increasingly complex and even synthetic formats of next-generation antibodies including multispecifics, antibody-drug conjugates, and engineered nanobodies. Apoha's Liquid Brain platform addresses this multi-parameter challenge through combining neuromorphic sensing and computing to evaluate the underlying biophysical properties that define antibody developability, unlocking novel biologic design and optimisation. With Smart funding, we will develop the first site-deployable prototype of the Liquid Brain for operation by research scientists and technicians in BioTech/Pharma companies. This will revolutionise early stage antibody screening of developability, reducing novel biologic therapeutic development time, costs, and likelihood of clinical-stage failures, ultimately improving treatment accessibility, affordability, and health outcomes.
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