We know that the entire world is experiencing a phenomenon called AI, which is now everywhere we go and has been seen in medical research as well. Now, there is an AI-based medical research platform named Causaly, founded by Yiannis Kiachopoulos, one of its co-founders. Their company, which is just over six years old, already has clients such as Gilead, Novo Nordisk, Regeneron, the Food and Drug Administration, and the National Institute of Environmental Health Sciences.
“For each drug to make it to the market, there are nine that failed,” said Kiachopoulos, working out to a 90% failure rate. “Each of those drugs typically costs between $1 billion and $2 billion to develop, according to research from the National Institutes of Health in the U.S. This gives us a real chance to accelerate and provide patient and societal benefits.” When asked by TechCrunch if “compute power was an issue for his startup as well, given that this is indeed one of the big themes among AI startups right now, biomedical or otherwise, and his answer was a surprising “no.” He added, “Only a tiny fraction will go into computing resources,” he said. This was partly due to how Causaly was built and partly because of its role in the ecosystem. “Six years ago, when we were starting the company, there were no large language models, so what we built was not computer-power hungry. We built natural language querying before Chat GPT, so we now don’t need large language models.”
He added, “With LLM, it can get easier to query AIs. That is true, and we are working on it. But you don’t need to train an LLM from scratch, so we can take and fine-tune what there is, and fine-tuning is a lot less of a drain on computing resources.” He also mentioned that “Our solution helps biomedical teams, but we are not developing our therapeutics” and that “We are a SaaS-based platform, training our scientists to get the most out of our AI. We have robust partnerships and are not competing, nor do we have plans to.”