Estima CEO: Generative AI reshapes pharmaceutical value proof

According to Estima co-founder Tim Reason, generative AI is reshaping how pharmaceutical companies prove their drugs are worth paying for.

Reason argued that the disruption underway in health economics and outcomes research (HEOR) is part of a broader pattern moving from consumer-facing industries into what he called "knowledge industries" - fields where value has traditionally been sold based on human time, expertise and experience, including traditional consultancy models.

He doesn't believe the shift eliminates demand for expertise, but expects the time-and-materials consultancy model to look fundamentally different within a decade.

"The most a human can do now has become table stakes," he said. "That's the bare minimum you have to come with. What value can you now offer your client now over and above that, using AI, which is going to be a mixture of your expertise, knowing how to leverage AI, and inserting your specific kind of domain knowledge into that process."

Reason co-founded Estima in 2019 with a desire to accelerate access to patient medicines. The firm works within HEOR, the discipline pharmaceutical companies rely on to show regulators that a new drug is both more effective and more cost-effective than what's already on the market.

"When a pharmaceutical company needs to bring a drug to market, they have to show to the regulator that their drug is better and more cost-effective than anything else that's on the market, and that's a huge part of their commercialisation strategy."

As Reason added, that typically means reviewing existing literature, running statistical analysis, and building an economic model to show whether a country would get value for money by paying for the drug. He noted that the process, when executed manually, done manually, can take three to four years once regulatory back-and-forth is factored in.

While he said the company's mission hasn't changed since the early days before readily available large-scale LLMs, the tools available to pursue it have.

"Our mission as a company hasn't changed. It's always been: speed up these processes, get patients life-changing medicines faster. But the means by which to do it has kind of become available and much more robust with the advent of generative AI."

Standard automation had already sped up the analysis stage at Estima, but it stopped short of the interpretation and write-up work. Generative AI, he said, has changed that. Clients are now able to bring forward launches in countries that might previously have been deprioritised because the HEOR and regulatory analysis was too time and resource‑intensive to justify.

"It's work that used to require dedicated in-country analyst time, which the business case often couldn't support. It doesn't remove the need for expert insight, but AI removes the resourcing barrier that made the analysis too costly to start in the first place," said Reason.

One of the areas he said AI has made the most difference is in responding to individual country regulators, who often require bespoke changes to a submission - asking that a particular comparison treatment be swapped out, for instance. Work that once required substantial manual rework in Excel or older statistical software, he said, can now often be turned around from weeks to minutes.

Estima's own client relationships are concentrated in the UK and U.S., though Reason said the pharmaceutical companies it works with need to support drug launches globally, often through central functions rather than direct relationships with every regional affiliate.

Reason was careful to frame the shift as augmentation rather than replacement. He said AI can produce results that "sound very plausible" but are wrong, and that without an expert checking the output, a company could end up recommending a drug that doesn't work as well as claimed, or worse, could cause harm. 

"I think we're going to need more of the human and more of the expert, in my opinion," he said.