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In India, a person receiving a blood transfusion is 3,000 times at a greater risk for HIV than a person in the US.
The reason? Most blood transfusions in our country use blood units that have been tested with the less accurate ELISA (enzyme-linked immunosorbent assay) test instead of the highly sensitive NAT (Nucleic Acid Testing), which costs Rs 1,050 per unit of Whole Blood. Despite molecular tests being available, their cost hinders their use.
Bengaluru-based is on a mission to make this gold standard molecular testing more widely available.
Launched last year, the deep-tech startup is building algorithms for molecular programming. Its technology works like a compression algorithm for molecular testing and has applications in healthcare, pharmaceuticals, agriculture, animal husbandry, food safety, synthetic biology, and molecular biology research.
For close to 18 years, Algorithmic Biologics’ founder Dr Manoj Gopalkrishnan has worked as a researcher in the field of molecular computing and has been a faculty at IIT Bombay.
Molecular computing brings insights from computer science to engineer molecular systems. “Molecular testing of DNA, RNA, protein, and other molecules helps us diagnose diseases, ensure safety of food and environment, discover, prove the efficacy, and ensure the quality of new drugs and new seed varieties,” explains Manoj.
The startup’s product ‘Tapestry’ is already enabling affordable screening in college campuses for Covid19.
While Algorithmic Biologics began to help scale the screening process for COVID-19, its seeds were laid in 2009 when Manoj, who was then a faculty member at TIFR (Tata Institute of Fundamental Research), heard about the swine flu epidemic.
He realised that diagnostic testing had become a bottleneck that was preventing an effective response to the epidemic.
“That was when I conceived of the basic idea of Tapestry. I tried to find collaborators then to help me implement this idea, but found interest was thin. When COVID-19 news started to reach us in early 2020, I tried again and this time found a much more favourable environment to taking this idea forward,” explains Manoj.
In times of COVID-19, the startup promised this: even a small lab with a capacity to conduct about 100 tests a day could use its technology test up to 1,000 individuals.
Algorithmic Biologics’ USP, according to its founder, lies in its AI-enabled SaaS solution that is independent of the underlying molecular test.
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“This space is greenfield and ripe for a huge growth spurt like we have seen in AI-based medical imaging in the last five years. We have some key patents in the area that we believe will be a big advantage in the future. We take the responsibility of training and supporting the lab to use our software around their standard workflow and charge them a fraction of savings demonstrated on a per sample basis,” says Manoj.
Design: Daisy
Imagine you have to look for a needle in a haystack, except there are several haystacks and some of them have no needles. What if there was a search tool to help you determine which haystacks might have the needle?
Tapestry, according to the startup, is a search engine that can help make the task of finding these needles—target molecules—easier.
“Our technology Tapestry is a first-of-its-kind software molecular search technology which comes in when there are many samples to be searched and few of them have the target molecules. Tapestry overlays existing gold-standard molecular tests to find the small number of samples with the molecules of interest with only a fraction of searches (tests) performed on various combinations of samples,” says Manoj.
The technology gives triplicate testing of every sample with highly accurate and quantitative individual results, at a cost that is a fraction of the cost of an individual test.
Apart from making blood transfusions safer, affordable molecular testing can also help lower newborn mortality.
“Hardly 2% of newborns are getting a newborn screening test leading to 25,000 avoidable mortalities every year. The food we consume has trace amounts of pesticides and even heavy metals causing much harm to health,” Manoj explains.
It is a software product running on the cloud as a web app. The lab gets training on SOP for the required preprocessing and solution support to achieve this preprocessing efficiently. The preprocessing achieves a compression of order 3X to 10X based on volumes.
After that, the labs run their test as per their existing practices. The results from these tests are uploaded to the web app. The solver runs on the cloud and gives the lab individual and quantitative results. The solutions are compatible with multiplexing—simultaneous detection of multiple targets.
Within a year of inception, the startup has received regulatory approvals, tested 25,000 samples, and signed up five enterprise customers.
“We obtained CE approval for in vitro diagnostics in the European Union for our product within one year. We are in the early revenue stage and working with leading names across various industries using molecular testing in their workflows,” says Manoj.
Algorithmic Biologics, the founder says, has been able to prove the technology capability is agnostic to underlying molecular test by showing that it works not just for qPCR (real-time PCR) but also for NAT tests, mass spectrometry, sequencing, etc. on a variety of samples from nasal swabs to plant tissue to blood.
Algorithmic Biologics’ key customers are research, diagnostic and industrial labs that benefit from increasing either throughput or volumes without incurring any additional capital investment.
The startup provides them with “scale multiplication” on their installed capacity through its software-only solution.
Traditionally such scale multiplication is offered through automation hardware, novel chemistry and biologics, or algorithm-based efficiencies supported by the software.
“We are in the third category, which has the advantages of being low capital cost and easy solution delivery through the cloud,” the founder says.
Algorithmic Biologics has 14 team members, out of which five have PhDs.
The initial R&D was funded via grants and institutional support through IIT Bombay. Once it was clear that the work was valuable and urgently needed to be taken to market, the team raised funds from Axilor Labs for making the technology commercially available.
“We take a small fraction of those savings as a cost of our services. We have been able to demonstrate positive unit economics at the operational level in all our engagements,” says Manoj.
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