The collaboration between Fusion Antibodies, a contract research organization (CRO), and Analytics Engines will incorporate machine learning (ML) and artificial intelligence (AI) into Fusion Antibodies’ CDRx humanization platform.
CDRx, according to Fusion, can perform multiple virtual experiments through AI and ML with panels of selected antibodies to discover properties needed to meet desired functionality and developability requirements.
The partnership aims to increase the platform’s AI and ML capabilities to further its abilities. Through this, Fusion may reach its long-term goal of reducing development costs and accelerating clinical timelines, it said.
Paul Kerr, CEO of Fusion Antibodies told us that the relationship, “will aid the development and the high throughput humanization of large-scale B-Cell repertoires to give more efficacious precision molecules rapidly.”
Currently, the CDRx platform uses the traditional clinical data repository (CDR) grafting technique while implementing in silico grafting parental CDR’s into mature human antibody frameworks. It screens a database of roughly 100,000 use antibody sequences and can generate full-length humanized antibodies that can be refined to reach a level that further resembles human antibodies.
Through the collaboration, Analytics Engines will be able to assist in the creation of ML models to improve Fusion’s antibody humanization process, said, Aislinn Rice, CEO of Analytics Engines in a press release.
“This will allow clients to create a large panel of humanized antibodies directly from multiple species allowing drug candidates to be screened quickly reducing time to clinical development,” said Kerr.
Kerr also stated that the partnership with Analytics Engines will bolster Fusion’s product quality and manufacturability.
Fusion received a €213,000 ($283,231) grant from Invest NI, a Northern Ireland development agency. Fusion said it would use the grant to develop its business and grow its workforce.
This collaboration comes after Fusion expressed its interest in differentiating its services into ML and AI as a way of competing with so called ‘pop-up consultants’ that had entered the field of humanization.
CROs have been incorporating AI more recently. Saama launched its first set of AI capabilities to support clinical trial planning and conduct. Its technology uses a “deep learning intelligent assistant” to use natural language processing and natural language understanding.
In drug discovery, Insilico Medicine and Juvenescence signed a multi-year drug development agreement to use AI in an aim to advance compounds.
