Future of Drug Discovery

Are you curious about the latest advancements in AI-enabled antibody discovery? In this podcast series, we dive into the world of Antiverse - we are accelerating drug discovery against difficult targets, including GPCRs and ion channels, using machine learning and phage display techniques.

Join us as we discuss our mission to target cancer, cardiovascular disease, and other challenging conditions. Discover how we leverage AI and wet lab innovation to accelerate the discovery and development of biologics. Plus, learn about our unique approach to antibody discovery, our progress with our internal pipeline of antibodies against GPCRs and other challenging targets, as well as our exciting ongoing collaborations. Tune in and join us at the forefront of antibody discovery!

Things mentioned:

⁠Murat Tunaboylu, Co-Founder and CEO of Antiverse.

Twist Bioscience, a Synthetic Biology company that develops and manufactures synthetic DNA.

⁠Antiverse, an AI-first biologics discovery company that designs antibodies against difficult -to-drug targets.

Watch the full presentation, with slides! https://youtu.be/cRHxi4MWExQ

Additional Materials: 

⁠Contact us about your discovery projects by emailing [email protected].

About Antiverse:

Antiverse was co-founded in 2017 with the goal of engineering the future of drug discovery to change people's lives. Based in Cardiff, Antiverse combines machine learning and phage display techniques to model antibody-antigen interactions. The current version of the platform uses next-generation sequencing and AI to design diverse antibody candidates for any given target. The technology is being developed to enable the discovery of biologics for difficult-to-drug targets associated with cancer, heart, and lung diseases.

In this captivating podcast series, we dive deep into the world of computational antibody discovery with Ben Holland, our Co-Founder and CTO at Antiverse⁠. Join us as we uncover the immense potential of merging computational and experimental techniques in the pursuit of revolutionary antibodies, as Ben sheds light on the strong benefits and formidable challenges encountered when targeting complex molecules such as GPCRs. With an emphasis on precision and accuracy in predicting antibody-antigen interactions, Ben shares remarkable insights and breakthroughs achieved by computational discovery techniques. Tune in and join us at the forefront of antibody discovery!

Things mentioned:

⁠⁠Ben Holland, Co-Founder and CEO of Antiverse.

⁠⁠⁠⁠Antiverse⁠, an AI-first biologics discovery company that designs antibodies against difficult -to-drug targets.

Watch the full presentation, with slides! https://youtu.be/v8-ZrR7L83s

Watch the full Computational Antibody Discovery Symposium, hosted by The Antibody Society, NaturalAntibody and AstraZeneca! https://youtube.com/playlist?list=PLWG3bWQmCPkPPfDhqiRqKWmqHYumJXlHq

Additional Materials: 

⁠⁠⁠Contact us about your discovery projects by emailing ⁠[email protected]⁠.

About Antiverse:

Antiverse was co-founded in 2017 with the goal of engineering the future of drug discovery to change people's lives. Based in Cardiff, Antiverse combines machine learning and phage display techniques to model antibody-antigen interactions. The current version of the platform uses next-generation sequencing and AI to design diverse antibody candidates for any given target. The technology is being developed to enable the discovery of biologics for difficult-to-drug targets associated with cancer, heart, and lung diseases.

In this talk, Murat speaks with Tzvika Hartman, Senior Vice President of Computation at Biolojic Design, a company curating AI-designed antibodies focused on autoimmune diseases and immuno-oncology applications. 

Biolojic uses machine learning to design 'programmable' antibodies with more precise molecular effects. These antibodies work dynamically with their environment, both temporally and spatially, opening avenues for new ways to alter biology. Their lead candidate, AU-007, pioneered by spin-out company Aulos Bioscience, is being advanced through Phase II clinical studies in solid tumour cancers. 

Don't miss this exciting opportunity to learn about the technology and strategies at Biolojic Design directly from Tzvika. Furthermore, we'll be exploring Tzvika's fascinating and eventful career. 

About Tzvika:

Tzvika has more than 30 years of experience in computer science research and software engineering. He worked at Google, Tel Aviv for 8 years as a software engineer, before founding Google's Health group in Tel Aviv, leading various projects over 5 years. Tzvika now leads the computational advancements at Biolojic Design. 
Things mentioned:

⁠⁠⁠Tzvika Hartman⁠, Senior Vice President of Computation at ⁠Biolojic Design⁠.

Weitzman Institute

Google, Tel Aviv

Google Trends

'Multibodies', Biolojic's proprietary antibody format.

ChatGPT

Novartis

Eli Lilly

AstraZeneca

AU-007, selective effector cells agonist for IO - Anti-IL2 epitope-specific antibody.

Additional Materials: 

⁠⁠⁠Watch the recording of the live event! https://youtu.be/XKJFFcFMt5c?feature=shared

About Antiverse:

Antiverse was co-founded in 2017 with the goal of engineering the future of drug discovery to change people's lives. Based in Cardiff, Antiverse combines machine learning and phage display techniques to model antibody-antigen interactions. The current version of the platform uses next-generation sequencing and AI to design diverse antibody candidates for any given target. The technology is being developed to enable the discovery of biologics for difficult-to-drug targets associated with cancer, heart, and lung diseases.

Never miss a future event!

We'll notify you when there's a new event scheduled. Fill out this form to sign up for marketing communications from Antiverse. We post about upcoming events on LinkedIn and Twitter.

LinkedIn: https://www.linkedin.com/company/antiverse/

Twitter (x.com) : https://twitter.com/AntiverseHQ

In this talk, Murat speaks with Abhishek Pandey, Principle Research Scientist and Pharma Discovery Group Lead at AbbVie. 

Abhishek currently leads RAIDERS, a Pharma Discovery group integrating machine learning across all of AbbVie's working groups to augment drug discovery capabilities. Abhishek's groups work spans cheminformatics, imaging research, multi-omics, as well as the computation behind many of AbbVie's current partnerships and collaborations. 

We'll be exploring how the machine learning group is transforming the processes across multiple working groups at the pharmaceutical giant, AbbVie. We'll also be unravelling the story of how Abhishek began his pioneering work at AbbVie.

You will learn:

About Abhishek's strategy for bridging chemistry, biology and computer science expertise to integrate machine learning across AbbVie's pharma discovery processes.

About Abhishek's vision for the future of drug discovery, as we explore the pressing needs of the pharmaceutical industry from both a technical and social standpoint.

About Abhishek:

Abhishek started his career as a software engineer at Toshiba. Following this, Abhishek began his PhD in medical engineering and image processing at the University of Arizona. This led Abhishek to become a core member of the precision medicine AI team at Tempus, developing ways to improve cancer imaging pipelines to help oncologists detect cancers more efficiently. Abhishek then joined AbbVie, where he founded the machine learning / deep learning team - the influence of which has expanded across the entire company. 

Things mentioned:

Abhishek Pandey⁠, Principle Research Scientist and Pharma Discovery Group Lead at ⁠AbbVie⁠.

RAIDERS: Pharma Discovery and Developmental Sciences team at AbbVie.

Google

Meta

Toshiba

Tempus Labs (now Tempus).

PADME (Protein And Drug Molecule interaction prEdiction), a framework based on Deep Neural Networks, to predict real-valued interaction strength between compounds and proteins.

NeurIPS Conference (Conference on Neural Information Processing Systems)

InSitro

Facebook

Additional Materials: 

⁠⁠⁠⁠⁠Watch the recording of the live event! ⁠https://www.youtube.com/watch?v=F9kADawRPOs

First time hearing about Antiverse?

Antiverse is an artificial intelligence-driven techbio company that specialises in antibody design against difficult-to-drug targets, including G-protein coupled receptors (GPCRs) and ion channels. Headquartered in Cardiff, UK and with offices in Boston, MA, Antiverse combines state-of-the-art machine learning techniques and advanced cell line engineering to develop de novo antibody therapeutics. With a main focus on establishing long-term partnerships, Antiverse has collaborated with two top 20 global pharmaceutical companies. In addition, they are developing a strong internal pipeline of antibodies against several challenging drug targets across various indications.

For more information, please visit https://www.antiverse.io

Never miss a future event!

We'll notify you when there's a new event scheduled. Fill out ⁠this form⁠ to sign up for marketing communications from Antiverse. We post about upcoming events on LinkedIn and Twitter.

LinkedIn: ⁠https://www.linkedin.com/company/antiverse/⁠

Twitter (x.com) : ⁠https://twitter.com/AntiverseHQ

This episode is a discussion between ⁠Rahmad Akbar, Senior Data Scientist in Antibody Design at Novo Nordisk and Murat Tunaboylu⁠, Co-Founder and CEO of Antiverse⁠.

You will learn:

The impact antibody design has on the world.

How AI is helping to push antibody design forward, bringing new therapies to patients.

What will antibody design look like in the future?

Rahmad's LinkedIn page.

Rahmad's Personal Website.

Antibody Origami: Here.

Rahmad's Previous and Existing Team: Victor Greiff (GreiffLab). Paolo Marcatili, Ludovica Beltrame, Rasmus Høiberg-Nielsen (Antibody Design at Novo Nordisk).

"And a big shout out to budding antibody designers (scientists) everywhere especially from my home country Indonesia!' - Rahmad.

Be sure to like, rate and review the podcast if you enjoyed this episode!

Visit our website: https://www.antiverse.io/

Follow us:
LinkedIn: ⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/antiverse/⁠⁠⁠⁠⁠⁠⁠
X: ⁠⁠⁠⁠⁠⁠⁠https://twitter.com/AntiverseHQ⁠⁠