- London-based Apoha has raised $36M led by Singular to commercialise a platform that measures how molecules and materials actually behave, a data class that has never existed at scale before.
- Founded by husband-and-wife duo Shamit Shrivastava and Anshika Srivastava, the company is already used by Boehringer Ingelheim to identify high-risk antibody candidates with greater than 90% precision from just 8 micrograms of material.
- The global biophysical assays market stands at $3.8B in 2025 and is projected to reach $7.9B by 2034, growing at a CAGR of 8.5%, according to Dataintelo.
AI has learned to read language, interpret images, and write code. It still cannot feel matter. That gap, the absence of structured, empirical data about how molecules and materials actually behave under real-world conditions, costs the pharmaceutical industry billions every year in late-stage clinical trial failures. Apoha was built to close it. And behind it is one of the more unusual founding stories in London’s deep science scene: a husband and wife, one an Oxford physicist with 15 years of foundational research, the other a Goldman Sachs Executive Director who left one of the world’s most powerful financial institutions to help turn that research into a commercial platform.
Apoha today emerges from stealth with $36M in funding led by Singular, with participation from Tim Draper’s Draper Associates and continued backing from seed investors Redalpine, Seedcamp, Wilbe and Nucleus, alongside grant funding from Innovate UK. The London and San Francisco-based company was founded in 2021 and employs 29 people.
The founders
Shamit Shrivastava (CEO) is a biophysicist and mechanical engineer who completed his PhD at Boston University and postdoctoral research at Oxford. In 2008 he began working on a problem left unresolved by the Nobel Prize-winning Hodgkin-Huxley model of nerve signal transmission — the physics of what happens at the boundary where matter meets liquids. His discovery was named one of Scientific American’s “13 Discoveries That Could Change Everything” in 2018 and has since been cited more than 1,500 times across 19 papers. Apoha now holds more than 60 patents covering hardware, software, data and AI models.
Anshika Srivastava (COO), his wife and co-founder, is a Dartmouth-trained engineer and former Goldman Sachs Executive Director who led engineering teams at one of the world’s largest investment banks before joining Shamit to commercialise the platform. Together they represent a rare founder combination in European deep science — frontier physics meeting institutional finance — and both are of South Asian heritage building one of London’s most technically ambitious stealth companies. As TFN has covered, London continues to produce deep tech companies solving some of the world’s hardest scientific problems — but founder duos of this background remain notably rare at this funding level.
“Liquid State Intelligence took 15 years of science and 5 years of company-building to bring to life,” said Shamit. “Where sequence gave us the language of biology and structure the language of design, Liquid State Intelligence gives us the language of behaviour — what matter, molecules and materials actually do — and we are the company building it.”
Anshika added: “Machines have learned to see what matter looks like and to read what we say about it. They have not learned to taste, smell or feel matter. That is the layer we are building.”
What it does
Apoha’s VIBE® assay takes a sample smaller than the head of a pin, suspends it in liquid, applies a controlled series of stresses, and captures the wave patterns the molecule generates in response — producing more than 1,000 simultaneous behavioural descriptors in minutes. Where conventional tools measure one property at a time under controlled lab conditions, Apoha produces a single readout that tells a drug company whether a candidate will fail before it ever reaches a clinical trial. As TFN has reported, AI drug discovery is now one of the most heavily funded categories in science — but the quality of the underlying physical data has remained a persistent blind spot. Apoha’s argument is that without behavioural data, even the most sophisticated AI models are reasoning about molecules they cannot truly understand.
Joint research with Boehringer Ingelheim shows Apoha identifying high-risk antibody candidates with greater than 90% precision from just 8 micrograms of material — outperforming 12 industry-standard tests simultaneously in a 236-antibody benchmark. Apoha also works with German biotech Ethris on lipid nanoparticles carrying mRNA, with food company THIS for plant-based protein reformulation, and with Somru BioSciences and multiple Fortune 500 companies across pharma, food and materials. Savings from catching failed drug candidates early scale to $100M or more across large multi-site customers.
The investors
Singular — which has previously backed Aikido, Basecamp Research and Vibe — leads as a first-time investor in Apoha. Draper Associates, known for early bets on Tesla, Skype and Coinbase, joins as a new investor alongside Singular. Redalpine and Seedcamp, whose portfolios include 9fin and Revolut respectively, return from the seed round.
Raffi Kamber, Co-Founder and GP at Singular, said: “Apoha represents a new generation of European scientific companies where AI is not a future promise, but a practical tool already transforming how biology is done. For the first time in 25 years, we are back to creating genuinely new science, being commercialised by founders with drive and global ambition.”
Competition and market
Apoha’s closest competitive context comes from contract biophysics providers such as Malvern Panalytical and Charles River Laboratories, both of which perform individual biophysical tests rather than simultaneous multi-descriptor profiling from minimal sample volume. Scientific data platforms such as Dotmatics manage experimental data but do not generate the behavioural layer Apoha produces. The global biophysical assays market stands at $3.8B in 2025, projected to reach $7.9B by 2034 at a CAGR of 8.5%.
As frontier AI moves deeper into physical-world applications from Isomorphic Labs’ $2.1B drug discovery platform to autonomous laboratories and materials science, the quality of underlying physical data will determine what those systems can actually reason about. Apoha’s bet is that molecular behaviour data occupies the same foundational role in physical-world AI that sequence data played in genomics. Whether that holds depends on whether a husband-and-wife team from Oxford and Goldman Sachs can scale one of the most technically complex data layers in science before a better-capitalised rival decides the same gap is worth closing.
