AI gets busy helping researchers create the first synthetic blood plasma
Today hospitals rely on blood donations to save patients, but what if you could create any blood or plasma you need on demand instead?
Key takeaways
- The AI made blood plasma, for example, could dissolve and keep real protein biomarkers at room temperatures without the need for refrigeration.
- In another experiment, a solution containing a mixture of fake polymers to mimic cytosol, the liquid found inside cells, was produced inside test tubes.
- In proteins, the building blocks are 20 different amino acids.
Cite or link to this article
Griffin, M. (2023) 'AI gets busy helping researchers create the first synthetic blood plasma', 311 Institute, 31 December. Available at: https://www.311institute.com/ai-gets-busy-helping-researchers-create-the-first-synthetic-blood-plasma/ (Accessed: 1 October 2026).
Scientists are using Artificial Intelligence (AI) algorithms to design new materials, including synthetic proteins to make synthetic blood plasma and biological liquids found inside of cells in a move that could eventually revolutionise healthcare treatments.
These artificial substances were able to support natural proteins and boost their properties, say researchers. The AI made blood plasma, for example, could dissolve and keep real protein biomarkers at room temperatures without the need for refrigeration.
In another experiment, a solution containing a mixture of fake polymers to mimic cytosol, the liquid found inside cells, was produced inside test tubes. When ribosomes, molecules containing RNA, were added, they continued to function normally producing proteins as if they were operating inside a real cell.
The Future of AI in Healthcare, by Futurist Matthew Griffin
Ting Xu, professor of chemistry as well as materials science and engineering at the University of Berkeley, led the research and believes AI can design new polymers to augment biological proteins. Proteins are a type of polymer, molecules made up of a sequence of smaller, repeating units. In proteins, the building blocks are 20 different amino acids.
"Basically, all the data shows that we can use this design framework, this philosophy, to generate polymers to a point that the biological system would not be able to recognize if it is a polymer or if it is a protein," Xu said in a statement. "We basically fool the biology.”
The deep learning model, a modified Variational Autoencoder (VAE), learned to encode features mapping protein structures to their function, and was used to design new materials with specific properties.
"We look at the sequence space that nature has already designed, we analyse it, we make the polymer match to what nature already evolved, and they work," Xu said.
"It was trained using natural proteins by dissecting proteins into short segments. By pooling the chemical characteristics of these segments that have been selected evolutionarily, we develop a blueprint for the polymer to mimic," she explained.
The system, described in a paper published in Nature, allows researchers to design hybrid biological systems or imbue existing materials with new properties. Scientists could make new plastic polymers that naturally degrade over time to combat waste, for example, or develop synthetic proteins to deliver drugs or enhance biological processes like artificial photosynthesis.
Xu believes scientists need to start designing synthetic proteins in new ways, and place less emphasis on trying to mimic natural structures. Unlike real proteins, the AI-made polymers were made up of just five or six different amino acids, making them less complex and easier to synthesize.
"The Food and Drug Administration hasn't approved any new material for polymer bio-materials for decades, and I think the reason is that a lot of synthetic polymers are not really working — we are pursuing the wrong direction," she said. "We are not letting the biology tell us how the material should be designed. We are looking at individual pathways, individual factors, and not looking at it holistically."
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Today hospitals rely on blood donations to save patients, but what if you could create any blood or plasma you need on demand instead?

About the author
Matthew Griffin Founder, 311 Institute
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."
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Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 15-time best selling author of the "Codex of the Future" series, Matthew is the Founder and Futurist in Chief of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.
An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.
As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.
Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.
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Sources and further reading
- Can synthetic polymers replace the bodys natural proteins news.berkeley.edu
- S41586 022 05675 0 nature.com
Source: first published by the 311 Institute on 31 December 2023. Cite as: Griffin, M. (2023). AI gets busy helping researchers create the first synthetic blood plasma. 311 Institute. https://www.311institute.com/ai-gets-busy-helping-researchers-create-the-first-synthetic-blood-plasma/
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