AI’s role in material innovation – Part 2: Biofabricated materials

This second article on material innovation follows that on next-generation fibres designed to replace conventional man-made fibres. Here, we explore the role of AI in advancements for the bioengineering or biofabrication of materials.

> Read Part 1 <

While research into biopolymers is advancing across various plastic-based industries—forecast to grow at an annual rate of approximately 13% between 2024 and 2029* (Skoczinski et al., 2025: Bio-based Building Blocks and Polymers – Global Capacities, Production and Trends 2024–2029, nova-Institut GmbH, Hürth, Germany, 2025¹)—the textile sector remains primarily driven by the outdoor and performance markets. Fashion would do well to take inspiration from these developments.

A key industry reference, Understanding ‘Bio’material Innovation: A Primer for the Fashion Industry by Fashion for Good and Biofabricate, defines biofabricated materials as follows:

“Biofabricated materials are produced by living cells (e.g. mammalian) and microorganisms such as bacteria, yeast and mycelium. Examples of biofabricated materials include fermented biosynthetic & biofabricated ingredients and bioassembled materials.”

Advances in bioengineered fibres

Among the early-stage start-ups developing biofabricated fibers, Spiber stands out with its Brewed Protein™, a 100% bioengineered fibre derived from bacteria. Recent collaborations include Burberry, The North Face, Pangaia, Helly Hansen, and Yuima Nakazato. In the field of biofabricated dyeing and pigmentation, companies such as Colorifix and Octarine are producing bacterial pigments and have partnered with key suppliers like RDD, respectively Positive Materials, and are even featured in catwalk collections of designers like Patrick McDowell (whose SS25 show in Milan showcased many innovative start ups).

Microbial nanocellulose is another area of innovation, as seen at Modern Synthesis, one of the first exploring the biofabrication of this fibre. Similarly, Australian textile firm Nanollose has developed Nullarbor™, a fibre made from microbial cellulose through an eco-friendly lyocell process. It is interesting to note that the starting material is made by the natural fermentation of carbohydrates from waste and by-products from the agricultural and food industries. Similarly, Celium™ from Polybion uses fruit waste to develop a biofabricated cellulose-based leather alternative, collaborating with Ganni a.o.. A more recent start-up in this field is Gozen, whose Lunaform biomaterial is produced by microorganisms during fermentation. Balenciaga showcased this innovation in its SS24 collection with a Lunaform bathrobe.

Gozen brand at the PV Paris show

By merging bioengineering, biophysics, and biochemistry, companies are exploring alternatives to silk. Bolt Threads developed Microsilk, a bioengineered fibre inspired by spider silk, created using only yeast, sugar, and water. Similarly, AMSilk introduced Biosteel® fibre in 2013, a high-performance spider silk protein fibre produced by genetically engineered microbes.

An example of a biofabricated biosynthetic material is Mango Materials’ PHA plastic, produced by feeding bacteria with methane. This process transforms a potent greenhouse gas into a sustainable polymer suitable for textiles, packaging, and consumer goods, contributing to waste reduction.

Another area of biofabrication is lab-grown materials, like cultivated leather from animal cells, or lab grown cotton as such of Galy.co, using considerably fewer resources than conventional farming and agriculture.

The role of AI in biofabrication

AI is playing a particularly interesting role in accelerating and enhancing performance in material science.

“AI is not merely a technological trend; it represents a paradigm shift in how materials science may be approached. By leveraging AI, vast datasets can be analysed, material properties can be predicted with high precision, and complex processes that were previously reliant on labour-intensive trial-and-error methods can be automated.”

– Rishi Gurnani³

One of AI’s most compelling contributions lies in high-dimensional learning. This enables the processing of complex datasets beyond human cognitive capacity, similar to how AI systems such as DeepBlue and AlphaGo have surpassed human performance in strategy games. This ability translates in materials science to the discovery of novel materials and optimisation of manufacturing processes, at all stages, from development to recycling challenges, by identifying hidden patterns within intricate data sets.

The Moon Parka / The North Face x Spiber

AI’s integration into materials science has given rise to materials informatics—a specialised field that melds machine learning, data science, and materials research to construct predictive models linking structure to properties. Originally developed to forecast drug behaviour from molecular composition in pharmaceutical research, this approach has been adeptly adapted to polymers and advanced materials, enabling researchers to precisely predict attributes such as mechanical strength, tensile and elastic properties, or other properties from vast datasets; consequently, textile manufacturers could tailor fibre and textile characteristics early in the design process to meet specific performances, aesthetic, and sustainability criteria. For example, Atlanta-based Matmerize Inc., a spin-out from the Georgia Institute of Technology, utilised its AI software to screen over 20,000 biopolymer candidates for Kimberly Clark, successfully identifying more than a dozen promising chemistries with desirable mechanical properties, yet also biodegrabability. The identified polymers currently are undergoing rigorous evaluation to ensure they meet Kimberly Clark’s sustainability and performance standards.3

Additionally, AI-driven personalised search engines allow researchers to refine their queries based on highly specific parameters—such as reaction constraints, chemical inventories, and supplier lists—yielding tailored insights and precise recommendations.

Emerging AI-designed biomaterials

Ginkgo Bioworks is at the forefront of AI-powered biofabrication. The company engineers living cells using synthetic biology to produce biomaterials, chemicals, and proteins. Their collaborations include microbial fermentation for bio-based dyes (e.g. with Huue for indigo) and the development of alternative leathers (e.g. with Bolt Threads for optimising Mylo, a mycelium-based leather). Their AI-driven platform expedites the discovery and scaling of these biological systems. In 2023, Ginkgo partnered with Google Cloud to develop large language models tailored for biological applications. By 2024, they launched Ginkgo Datapoints, a service generating extensive biological datasets to refine AI models.

Several start-ups are leveraging AI to design novel biofabricated materials: Solena Materials is a biotechnology company leveraging Al to design high performance sustainable fibres made by microbes for market-leading apparel. They use computational design to develop a new class of synthetic proteins from scratch. They design fibre proteins to have a spring-shape, providing toughness, that self-assembles into a liquid crystal (a stable state of matter between solid and liquid). Nanoloom specialises in graphene nanomaterials, which are a high-performing, cost-competitive replacement for traditional synthetics in apparel. Their first focus is in providing stretch yarns. They also use Al algorithms to intelligently select which fibres to combine, understand the perfect ratios for each blend, and predict the exact characteristics of the resulting fabric or knit.

Patrick McDowell SS25

Beyond material innovation, AI is revolutionising impact assessment, verification, and predictive modelling for sustainability scenarios. In regenerative agriculture, for instance, AI-driven satellite monitoring tools—such as environmental intelligence company Kayrros—are reshaping how land use, deforestation, carbon sequestration, and biodiversity are tracked. These insights help verify regenerative practices and strengthen trust in Voluntary Carbon Markets.

Conclusion: AI as a catalyst for future craftsmanship

As in pharmacology and biology, the perspectives of AI-driven material discovery in fashion are vast:

"We’ve essentially, as an industry (chemistry), only tested enough compounds to fit in a bucket of water compared to the entire oceans of the earth."

– Karen Akinsanya, President of R&D, Schrödinger Therapeutics

While the pursuit of innovative solutions remains vital, the contribution of AI to preserving institutional knowledge should not be overlooked. Its ability to record past experiments, extract critical insights, and facilitate the transfer of expertise is invaluable. However, true craftsmanship—encompassing specialised manual skills from precise sewing techniques to high-end artisanal practices that define the essence and beauty of traditional fashion—will likely not be swiftly mastered by robots. These artisanal skills must be cherished, spotlighted, and preserved, and those who bridge technology with craftsmanship will ultimately shape the future of fashion in the most innovative and meaningful ways.

> Read Part 1 <