05.03.24
Scottish CRDMO Ingenza has secured innovation funding from InnovateUK to adapt its codABLE machine learning platform to precisely control recombinant protein expression in the industrial yeast Pichia pastoris.
This project aims to accelerate the development of therapeutics, enzymes and other proteins by harnessing machine learning to fine-tune codon usage, ensuring seamless compatibility with the production host and maximizing production yields.
Ingenza will use this award to establish its proven algorithm in P. pastoris, a powerhouse of protein biomanufacturing. To achieve this, the company is deploying rapid, ultra-high throughput screening and next generation sequencing (NGS) to dive deep into millions of gene variants, generating a dataset that will enable codABLE to uncover the link between codon context and protein expression for valuable protein targets.
Rita Cruz, Head of Strain Development at Ingenza, commented: “Ingenza's codABLE machine learning algorithm represents a step change in designing genes for predictable and optimized recombinant expression, a challenge that has hindered engineering biology until now. This approach combines cutting-edge computational technology with Ingenza’s broad expertise in over a dozen biomanufacturing hosts. It is undoubtedly increasing our business competitiveness and accelerating innovations in bio-based manufacturing."
This project aims to accelerate the development of therapeutics, enzymes and other proteins by harnessing machine learning to fine-tune codon usage, ensuring seamless compatibility with the production host and maximizing production yields.
Ingenza will use this award to establish its proven algorithm in P. pastoris, a powerhouse of protein biomanufacturing. To achieve this, the company is deploying rapid, ultra-high throughput screening and next generation sequencing (NGS) to dive deep into millions of gene variants, generating a dataset that will enable codABLE to uncover the link between codon context and protein expression for valuable protein targets.
Rita Cruz, Head of Strain Development at Ingenza, commented: “Ingenza's codABLE machine learning algorithm represents a step change in designing genes for predictable and optimized recombinant expression, a challenge that has hindered engineering biology until now. This approach combines cutting-edge computational technology with Ingenza’s broad expertise in over a dozen biomanufacturing hosts. It is undoubtedly increasing our business competitiveness and accelerating innovations in bio-based manufacturing."