Biopharma decarbonization efforts must consider both the drug and manufacturing process, according to new research, which argues that dose optimization, renewable energy use, and AI are the most impactful steps biologics makers can take.
The research, by U.K.-based healthcare sustainability consultancy, YewMaker, compared the “carbon footprints” of various asthma biologics to develop a model that industry can use to make manufacturing processes more sustainable.
Asthma biologics are an ideal test case, according to author Haroon Taylor, YewMaker’s CTO, who told GEN that the team identified significant variation in the carbon footprints of the various products.
“Whilst the manufacturing processes used to make all asthma biologics are similar, the electricity sources used during manufacturing have a big impact on the carbon footprint. At a manufacturing level, biologics that are produced with fewer fossil fuel energy sources will have a smaller carbon footprint.
“We found that the non-fossil fuel electricity percentage of the biologics studied ranged from 22–91%. Overall, the carbon emissions for the first year of treatment of a representative patient ranged from 1.1 kg CO2e to 188.9 kg CO2e,” Taylor says.
Taylor and co-author Nazneen Rahman, MD, PhD, CEO of YewMaker, identified several levers firms could use to reduce emissions, with dosage optimization and switching to renewable energy sources emerging as the most impactful.
“The most effective near-term solution is for manufacturers to use fewer fossil fuel energy sources. By replacing fossil fuel electricity with renewable or nuclear sources, manufacturers can significantly reduce the carbon footprint of asthma biologics.
“Additionally, optimizing dosing practices to reduce the quantity of medicine required for effective treatment will reduce the overall carbon footprint,” Taylor says, adding, “At a clinical level, the amount of medicine required for effective patient treatment will have an impact on the carbon footprint.”
AI analytics
Another critical factor to any industrial decarbonization effort is the ability to measure, model, and, ultimately, predict emission levels associated with candidate manufacturing processes in the development laboratory.
And this is where AI-based data analysis has a vital role to play, according to Taylor, who adds that with such technologies, manufacturers will be able to share more information about sustainability programs for the good of the wider industry and society in general.
“AI and automation can help vastly increase the speed and standardization of carbon footprint quantification. By increasing disclosure, visibility, and comparability of carbon footprint estimates, we can drive forward the decarbonization of asthma biologics,” he says.
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