What do you get when you combine a revolutionary healthcare startup with artificial intelligence (AI) technology? In the case of A-Alpha Bio, the answer is simple: a $22.4 million funding round and a bright future.
A-Alpha Bio, born from the University of Washington's Institute for Protein Design, uses computational tools and yeast experiments to identify therapeutic proteins. It collaborates with drug companies to find ideal agents for testing across various conditions.
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A Big Step Forward For A-Alpha Bio
A-Alpha Bio forged key partnerships with Bristol-Myers Squibb Co., Lawrence Livermore National Laboratory and Gilead Sciences Inc. to advance protein interaction research, antibody development in biothreats and HIV therapeutic exploration.
Using AI tools, the startup aims to accelerate drug, enzyme and biosensor development. With access to nearly 500 million protein-protein interaction measurements, its technology employs single-celled yeast, experimental and computational methods to identify crucial interactions.
The company's computational tools, AlphaSeq and AlphaBind, analyze these interactions using machine learning.
In a recent interview, A-Alpha Co-Founder and CEO David Younger discussed his thoughts on the impact of machine learning in the healthcare space.
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"Machine learning successes across the industry are valuable proof-points for the power of machine learning applied to biological problems and drive considerable interest into companies like ours," Younger said. "Additionally, we benefit from advances in machine learning — as many of the techniques used by others (large language models, etc.) can also be applied to biological data."
A-Alpha Bio was founded in 2017, using the technology its co-founders helped to develop while working as graduate researchers at the University of Washington.
The recent Series A extension funding of $51 million, led by Perceptive Xontogeny Venture Fund, propels its growth and milestone achievements.
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