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AbCellera Closes Series A led by DCVC Bio


VANCOUVER, British Columbia--(BUSINESS WIRE)--AbCellera announced today that it has closed its Series A financing led by DCVC Bio, a Silicon Valley venture capital fund focused on deep technology ventures that lie at the nexus of artificial intelligence and biotechnology. AbCellera will use the USD $10 million financing to accelerate the growth of their therapeutic antibody discovery business, including investments to build capacity and integration of advanced technological capabilities spanning computation, protein engineering, and immune repertoire profiling. "With this financing, we will double-down on our partnership business that has enjoyed profitable, triple-digit growth over the past 3 years. In DCVC Bio, we have found the ideal funding partner to help us accelerate the success of our full-stack antibody discovery engine, one that integrates artificial intelligence with industry-leading microfluidic screening technology," said Carl Hansen, CEO of AbCellera. AbCellera's high-throughput single B cell screening platform and repertoire sequencing technologies enable discovery of large multidimensional data sets of valuable antibody sequences.

Welsh startup Antiverse raises $2m for antibody discovery toolkit


New biotech Antiverse has raised seed funding of £1.4 million ($2 million) to develop its artificial intelligence-based platform for discovering therapeutic antibodies. The Cardiff, Wales startup is combining machine learning and phage display techniques to model antibody-antigen binding and says it can cut the time it takes to develop a drug candidate. It's one of the few AI drug discovery companies operating in the antibody category, as most are focused on small molecules. Antiverse – which was co-founded in 2017 by engineers Murat Tunaboylu and Ben Holland – says it will use the cash injection to build a new laboratory in Cardiff and expand its technical team through recruitment of specialist machine learning engineers, laboratory scientists and structural biologists. Antiverse's platform uses next generation sequencing and AI to provide diverse antibody candidates for any given target, according to the company, which reckons its approach is quicker than existing antibody discovery methods which are effective but can be limited and costly.

Biopharma companies turning to artificial intelligence for drug discovery


The importance of artificial intelligence and machine learning (AI/ML) has not been lost on drug development companies. Recently, to help accelerate the discovery of therapies to treat COVID-19, several deals have been established to help deploy those tools. For example, Abcellera Biologics Inc., of Vancouver, British Columbia, and Eli Lilly and Co., of Indianapolis, agreed to co-develop antibody products for treating and preventing COVID-19. The collaboration will build on Abcellera's pandemic response platform, developed under the DARPA Pandemic Prevention Platform (P3) program, and Lilly's global capabilities for rapid development, manufacturing and distribution of therapeutic antibodies. Within one week of receiving a blood sample from one of the first U.S. patients who recovered from COVID-19, Abcellera screened more than 5 million immune cells looking for those that produced functional antibodies that helped the patient neutralize the virus and recover from the disease and identified more than 500 unique fully human antibody sequences.

Columbia University Researchers Use AI to Develop Treatment for Coronavirus - Impakter


Columbia University is at the frontier between AI and biotech, especially in coronavirus research. Two graduates of the Data Science Institute (DSI) at Columbia University – Andrew Satz and Brett Averso – are using AI in coronavirus research, relying on computational design to accelerate the discovery of treatments for the coronavirus. Andrew Satz and Brett Averso are Chief Executive Officer and Chief Technology Officer, respectively, of EVQLV, a startup creating algorithms capable of computationally generating, screening, and optimizing hundreds of millions of therapeutic antibodies. They apply their technology to discover treatments most likely to help those infected by the virus responsible for COVID-19. Conducting antibody discovery in a laboratory typically takes years; it takes just a week for the algorithms to identify antibodies that can fight against the virus.

Artificial Intelligence Helps Design Better Antibody Drugs


Machine learning helps develop optimal antibody drugs. Antibodies are not only produced by our immune cells to fight viruses and other pathogens in the body. For a few decades now, medicine has also been using antibodies produced by biotechnology as drugs. This is because antibodies are extremely good at binding specifically to molecular structures according to the lock-and-key principle. However, developing such antibody drugs is anything but simple.