AminoAnalytica
AI for improved protein production and performance
Biotechs use proteins found in nature, such as enzymes in bacteria or peptides in lizards, in a wide range of applications from chemical manufacturing to therapeutics. However, these naturally occurring proteins aren't optimized for industry. At AminoAnalytica, we specialize in AI-powered protein optimization. Using our proprietary computational tools, we can improve the properties of a target protein sequence, from the stability of therapeutic peptides to the activity of industrial enzymes. When we optimize a protein, it’s not just a theoretical suggestion—we work with labs to ensure that it’s functional, stable, and ready to change the world.
Active Founders
Abhi Rajendran, CEO & Co-founder
Materials Engineer from Imperial College London. I previously worked at the Mercedes Formula 1 Team and now work at the intersection of AI and Protein Design - there's a funny story in there somewhere.
Matteo Peluso, Founder
Compute credits are all you need
Adam Wu, Founder
Materials scientist from Imperial College London. Worked in product design, manufacturing, and industrial labs. Shameless plug: check out 'adwuu' on spotify for a good time
Company Launches
Hey everyone – it’s Abhi Rajendran, Adam Wu and Matteo Peluso
Tl;dr: just look at the pictures ;)
💞 The A(mino) Team
👨🏾 Abhi Rajendran – From Imperial College London to the Mercedes F1 Team, Abhi builds AI tools in data-intensive environments. AminoAnalytica was inspired by his computational bio master’s project and was the top AI x Robotics venture from Imperial in 2024.
👦🏻 Adam Wu – With experience in academic and industry wet labs, Adam is now building his own. He has a background in materials science, tissue engineering and biosensing as a Thermo Fisher Scholar from Imperial.
👱🏼♂️ Matteo Peluso – Bioinformatics PhD from the University of Zurich. His skills in biology, machine learning, and software development tie up everything seamlessly.
👨🏻🦱 Dr. Stefano Angioletti-Uberti – Senior lecturer at Imperial, specializing in modeling biological and soft matter systems. He ensures models are based on the latest scientific principles.
❌ Problem: better proteins are needed to accelerate global innovation
- Industrial and pharma companies prefer to use enzymes and peptides over harsh chemicals as they are more specific and sustainable.
- However, natural proteins often lack stability, efficiency, or specificity for their desired applications leading to poor performance
- Improving these proteins has been a costly and inefficient 'trial-and-error' process, where biotech companies randomly mutate existing proteins, test them, and repeat until success.
✅ Solution: AminoAnalytica’s protein adaptation platform, powered by PLMs
- Like how ChatGPT understands human language, our "protein language models" (PLMs) understand biology and can optimize proteins for industrial and therapeutic use.
- This allows us to perform in-silico protein property prediction, eliminating the need for thousands of lab tests.
- We’re transforming the traditional ‘trial-and-error’ method into an ultra-high throughput and rational process.
🤝 Any industry working with proteins can benefit from our tech
Currently, we’re working on:
- Aquaculture feed → enzymes for maximizing fish feed nutritional efficiency
- Pharmaceuticals → peptide drugs with improved stability and specificity
- Climate tech → enzymes for eco-friendly carbon capture
- Consumer goods → safer enzymes for everyday products
🐡 Get in touch with us!
- Upvote/share this post with your network and help spread the word!
- If you (or anyone in your network) are as excited as we are about next generation industrial proteins and would like to learn more about what we’re doing, email us here - founders@aminoanalytica.app
- We’re also looking to expand our advisory board in the areas of aquaculture, fish testing, and feed manufacturing!
