The collaboration fuses EVQLV’s expertise in AI-enabled antibody design & Manhattan BioSolutions’ expertise in antibody development in oncology
Examining AI as automated, assistive, analytical, accelerated, or augmented intelligence is a framework for thinking about how to apply these tools to data in ways that are aligned with an organization’s goals. This framework is designed to allow those who do not routinely build or employ AI to avoid the overhyped rhetoric of AI and consider the practical outcomes of employing it.
EVQLV CEO, Andrew Satz, recently joined the Amplifying Scientific Innovation podcast with Dr. Sophia Ononye-Onyia. They discussed his definition of scientific innovation, personal anecdotes of his CEO journey and EVQLV’s unique approach to scientific innovation through the acceleration of biologic therapies with the power of artificial intelligence (A.I.).
Our CEO, Andrew Satz, recently spoked at “Alumni in Conversation,” hosted by Columbia University School of General Studies. During the discussion, Andrew explained how EVQLV’s algorithm models the drug discovery process.
Seeking Alpha recently covered our work with Twist Bioscience on novel antibody discovery.
EVQLV Applies Proprietary AI Technology in Collaboration with Twist Bioscience to Discover and Validate Novel Antibody Therapies
EVQLV, Inc., an artificial intelligence-enabled technology company accelerating biologics discovery, announced today a collaboration with Twist Bioscience Corporation (NASDAQ: TWST), a company enabling customers to succeed through its offering of high-quality synthetic DNA using its silicon platform, to discover novel antibody-based therapies.
Brett Averso (CTO, EVQLV) and Bhoomika Kumar (SciTech intern, EVQLV) teamed up to provide a high-level overview of how EVQLV’s evolutionary algorithm works.
EVQLV’s CEO, Andrew Satz, joined Kerrin Black of the Talent Finders Podcast to discuss his entrepreneurial journey, some of the challenges facing AI for drug discovery, his legacy and much more.
Our CEO was recently asked how far away is fully computational drug discovery and development. This isn’t an easy question to answer and Andrew doesn’t provide an exact date. However, he does provide interesting insight into the progress we’ve made and the challenges ahead.
EVQLV CEO, Andrew Satz, explains that while speed is important, it can also be dangerous, and is certainly not the only reason we’ve chosen a computational approach to drug discovery.