Beyond speed: The value of a computational approach to drug discovery

Jun 2, 2020 | Blog | 0 comments

Daniel Gigante

We recently held an event with BioIDEA: Biotech vs COVID-19. During the event, our CEO, Andrew Satz, was asked the value of computational drug discovery beyond just speed. Andrew explained 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.

In addition to speed, computational technologies can aid in de-risking by creating models or simulations of lab outcomes. This leads to computer failure instead of lab failure, or, de-risking of the drug discovery and development process. Because of this decreased risk, we should expect a significant reduction in cost. This is beneficial for companies, but more importantly, it increases availability and reduces financial hardship for those in need of healing. Watch the clip below.

0 Comments

Submit a Comment

Your email address will not be published. Required fields are marked *

EVQLV and Manhattan BioSolutions Enter into Strategic Collaboration to Discover Novel Antibody-Based Therapies

The collaboration fuses EVQLV’s expertise in AI-enabled antibody design & Manhattan BioSolutions’ expertise in antibody development in oncology

Demystifying AI In Pharma

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.

Andrew Satz on the Amplifying Scientific Innovation Podcast with Dr. Sophia Ononye-Onyia

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.).

How Our Algorithm Models the Drug Discovery Process

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.

Large Pharma’s Embrace of Artificial Intelligence

The benefits of computational drug development are well known and accepted by many in the pharmaceutical space. However, since the onset of the global pandemic, consensus went from it being an interesting concept that was almost certainly the future, to something we need implemented as soon as possible. This is one of the few silver linings of the coronavirus outbreak.

Pin It on Pinterest