Keeping up with Climate Tech vol. 14

In the race to decarbonize industry, most climate startups build something new — a material, a fuel, a battery, a reactor.

Vienna-based startup Elio is building something more invisible: decision infrastructure to make pharma more sustainable.

“We’re enabling scientists in pharmaceutical manufacturing, specifically in the early discovery stages, where a lot of the key parameters of the final manufacturing process of a drug do get actually defined inadvertently,” Kami Krista, co-founder and CEO of Elio, told the Harvard Technology Review. “We enable those individuals to consider sustainability—specifically right now, CO₂ emissions—as a decision criteria when they’re developing and making their decisions at that stage.”

Targeting Process Inputs at the Earliest Stage

Sustainability in pharma is often treated as a downstream accounting exercise, something quantified after a process is built and a product is ready. Elio believes sustainability is critical to shaping the process as a product comes into being. Krista and her team are trying to make carbon legible while the manufacturing guardrails are still being set.

“We’re very focused on process input selection, essentially optimizing anything that kind of goes into the manufacturing process in theory,” Krista said. “Process inputs make up up to 50% of the emissions of an average pharma company, and it’s where kind of the biggest data challenges lie.”

The idea is not to redesign entire pharmaceutical processes overnight. It is to influence the decisions that quietly compound into long-term impact.

“It turns out that like 80% of the final environmental impact of most products is estimated to be determined in the first few years of process design,” Krista said. “So you really need to get in very early.”

Rather than forcing radical redesigns, the company is focusing on incremental but scalable substitutions, like “switching out specific compounds you’re using, or even switching suppliers, since there are a fair number in the market.”

The Two-Sided Challenge: Data and Decision Flow

Elio’s work sits at the intersection of two problems.

“We want to understand how you assess the sustainability impact of very complex chemicals at scale,” Krista said. “That has not yet been solved at the level of granularity where it’s meaningful for decision making.”

That is the technical feasibility side: reconstructing emissions impact at a level precise enough for a chemist comparing options.

“The other side of the challenge…is how do you bring that data actually into the hands of decision makers, meaning the scientists, at a point in time, and in an interface and in the context that they are able to consider sustainability at that point in time?” she added.

Sustainability tools today often sit outside core scientific workflows. As she put it, sustainability is “very much separate or distinct from their day-to-day decision flow.” Scientists “have to jump into a different pool in order to do that.”

Elio’s solution is not just to provide emissions data, but to embed it inside the workflow where tradeoffs are already being evaluated.

Building the Missing Planning Layer

“What we’re now doing is building an interface that acts as generally a decision coordination planning layer that currently doesn’t exist within pharma companies,” Krista said. “We’re helping scientists understand their options in drug development.”

Deadlines dominate those decisions. 

“The key element here is that drugs operate on deadline,” Krista said. “That’s the biggest constraint for pharma. They consider the time that they have, the lead times at which compounds are coming in, and the amount of time it basically takes to plan those pieces.”

By shortening planning time and clarifying feasibility, Elio earns the right to add another column to that comparison.

“We’ve identified opportunities to shorten the planning time and to enable more accurate understanding of when they can really run an experiment effectively,” Krista said. “And because of that, we can then begin layering sustainability into that comparison chart as well.”

Sustainability is not presented as a separate objective. It becomes one criterion among many, alongside timeline, feasibility, and cost.

Closing the Implementation Gap

Elio’s origin traces back to a broader question — one that led Krista to leave Harvard.

“The problem that I actually started with, and which is why I dropped out of Harvard as a junior in 2020, is to think about how we can close the implementation gap when it comes to climate solutions.”

There is no shortage of sustainable materials or alternative processes under development. The problem, she argues, is adoption.

“When you look at… the people who are designing the products and the manufacturing processes for the products we use on a day-to-day basis, are they able to consider sustainability?” Krista asked. “The answer is, basically across the board, no.”

Elio’s wager is that climate impact is ultimately a coordination problem. Traditional supply chain tools assume that procurement teams control purchasing decisions. But in pharma, many of the most consequential supply chain choices are made much earlier.

“And yet the decisions are not being made by them, particularly in pharma,” Krista said. “By the time procurement gets involved, so many decisions have been made that they don’t want to redo…because then they lose a lot of time and money to go back and redo a bunch of work.”

The early “guardrails” that chemists set define the long-term option space for a drug’s supply chain. And those scientists have historically had little infrastructure for deliberate optimization.

“Those people…at the moment don’t have anything available to them to make decision making,” Krista said.

That insight shapes Elio’s longer-term ambition. 

“We’re building a foundational decision infrastructure for supply chain optimization,” she said. “It’s geared towards the technical users in the company that are actually defining what a product looks like.”

Sustainability, in that framework, is only one dimension.

“We’re also talking about the adaptation side of sustainability, which is a risk,” she said. “Supply chains are going to get very fragile, and the need to be able to agilely adapt is going to be really critical.”

Using AI with Restraint

Given the computational intensity of lifecycle modeling, the question of AI’s environmental footprint inevitably arises.

“I don’t think anyone really has an answer to that at the moment,” Krista said.

Elio’s approach is pragmatic. “Do we need generative AI for everything? No.” 

Many problems, she argues, can be solved with deterministic models that are less energy-intensive and more precise.

“That’s not what we do,” she said of constantly re-running large models. “We precompute a lot of things, and then we reuse those values…we’re not consistently running high amounts of requests, so we are able to control how much water and power is consumed by these systems.”

Expanding Beyond Pharma

For now, Elio plans to remain focused on pharma. But Krista sees broader potential.

“We’re definitely planning to stay in the pharma space for at least next two years,” she said. Longer term, she imagines moving “upstream…into the specialty chemicals spaces,” or into parallel industries “like the cosmetics industry,” which are chemical-intensive.

But the real expansion, she suggests, is conceptual.

“What matters for us is value expansion,” Krista said. “We want to help more people achieve a sustainable supply chain, which is becoming even more pressing given regulatory pressures and pressures to grapple with the consequences of our past unsustainable actions.”

If climate change is often framed as a materials problem, Elio is treating it as a decision problem.

And in pharmaceutical labs, those decisions are being made every day.