FINLAND – A groundbreaking study, published in the scientific journal Advanced Materials, led by researchers at VTT Technical Research Centre of Finland, introduces a transformative approach that integrates synthetic biology with advanced machine learning and computational techniques.
This integration significantly accelerates the development of new biomaterials, reducing the timeline from years to mere minutes and promising rapid advancements in medical and industrial applications.
“By leveraging the power of AI and synthetic biology, we’ve fine-tuned and dramatically sped up the design process of new protein-based materials, achieving in months what used to take years, with the potential to reduce this time to minutes further,” says Pezhman Mohammadi, VTT’s Senior Research Scientist and the head of the study.
Utilizing machine learning algorithms, VTT’s research team efficiently sifted through thousands of protein structures to pinpoint the most promising candidates for laboratory synthesis.
The new high-performance, protein-based biomaterials developed through this method are expected to replace fossil-based materials and bring game-changing properties to high-demand applications, such as medicinal injectables and smart materials.
This research showcases the effective use of hybrid biomimetic and de novo design strategies, combining insights from nature’s own design capabilities to create innovative materials from scratch.
“Synthetic biology enables the production of complicated structures present in nature. Through this approach, we are not only replicating the extraordinary properties of natural materials but also enhancing them to meet specific functional needs, going one step beyond evolution,” adds Pezhman.
The publication in Advanced Materials marks a significant milestone in the multidisciplinary field of material biotechnology and highlights the potential of integrated sciences in solving complex global challenges.
The research team, including collaborators from VTT, the Polish Academy of Sciences, Temple University, Nanyang Technological University, and Aalto University, brings diverse expertise in biology, chemistry, physics, data science, machine learning, AI, and computational science.
Together, they continue to refine these innovative techniques and expand their applications in the near future.
“As we move forward, we envision that the fusion of biotechnology, biorefinery processes, automation, synthetic biology, as well as the pivotal roles of machine learning and AI – all underpinned by biointelligence – will dramatically transform manufacturing,” says Pezhman.
“This comprehensive approach enables the rapid, precise design and production of biomaterials, leveraging automation to streamline and scale operations efficiently.
“The convergence of all these technologies not only accelerates innovation but also enables a radical shift towards more customized, sustainable production methods across various sectors, offering tailored solutions with minimal environmental impact and revolutionizing industry practices.”
The study, titled “Accelerated Engineering of ELP-based Materials through Hybrid Biomimetic-De Novo Predictive Molecular Design,” demonstrates how the collaboration of experts from diverse fields, including synthetic biology, artificial intelligence, molecular dynamics simulation, and more, has led to the creation of new biomaterials that are both sustainable and highly functional.
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