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  • Variational AI Files Two US Provisional Patents for Potential COVID-19 Drug Created by Generative AI

    Variational AI Files Two US Provisional Patents for Potential COVID-19 Drug Created by Generative AI

    Patents filed for novel small molecule SARS-CoV-2 Main Protease (Mpro) inhibitors

    Vancouver, BC – January 5, 2023 – Variational AI, developer of the Enki™ generative artificial intelligence (AI) drug discovery platform to redefine the economics of drug development, today announced that the company has filed two provisional patents with the United States Patent and Trademark Office (USPTO) related to new chemical entities (NCE) successfully created using generative AI. Variational AI’s protease inhibitors are among the first NCEs created via a purely generative model and will be useful in the development of COVID-19 drugs as part of the company’s coronavirus antiviral program. Of even greater significance, this method underscores the potential of generative AI to create novel, efficacious, safe, and synthesizable molecules.

    “The filing of these patents is a concrete milestone not just for Variational AI, but for the applicability of generative AI to the domain of drug discovery,” said Handol Kim, co-founder and CEO, Variational AI. “Whereas adoption of AI for drug discovery is accelerating, until now it has been based on older discriminative models. Though powerful, these models are essentially just performing faster and better virtual screening of known or existing molecules. Enki™ does not screen, but rather truly creates new molecules, similar to how other generative AI models like DALL-E and ChatGPT create novel images and text based on prompts. In our case, we use the language of chemistry as prompts to describe the molecules we want.”

    While generative AI has recently been applied at scale to the creation of novel images, text, music, video, and software code, the successful application of generative AI to drug discovery is still nascent but potentially transformative. Variational AI’s platform created two novel lead candidates that each bind differently and distinctly to the SARS-CoV-2 main protease, the most promising therapeutic target implicated with COVID-19 across variants and potentially other coronaviruses. The platform is based on a generative model framework known as a variational autoencoder (VAE) and created these lead candidates after being trained on large sets of public and proprietary data including older SARS-CoV (SARS) main protease data.

    The candidates demonstrated potency, selectivity, and novel binding modes on the SARS-CoV-2 main protease that show potentially better safety profiles compared to the existing standard of care. Variational AI is now focused on training Enki™ for multiple drug targets in oncology and making rapid progress in this disease area, leveraging learnings from its success in antivirals, as well as other disease areas.

    “Our team of machine learning researchers has been developing and applying generative models for years, long before the recent interest,” said Jason Rolfe, co-founder and CTO, Variational AI. “Drug discovery is a massively difficult undertaking, yet we continue to make rapid progress working hand-in-hand with our drug discovery team as we move to addressing unmet medical needs in oncology and beyond.”

    Funding for this work was supported in part by Canada’s Digital Technology Supercluster in collaboration with adMare BioInnovations and the University of British Columbia.

    About Variational AI

    Variational AI uses generative AI to create novel and diverse compounds that are optimized for multiple properties to avoid the most common causes of drug attrition and increase clinical probability of success. Variational AI works with leading biopharmaceutical partners and is developing its own internal pipeline. To learn more, visit variational.ai.

    Media Contact
    Jordan Bouclin and Rita Murphy

    SVM PR

    variationalai@svmpr.com

    Jordan Bouclin

    January 5, 2023
    Press Release
  • Variational AI Adds Jennifer Hamilton as Advisor

    Variational AI Adds Jennifer Hamilton as Advisor

    Leading Biotechnology Professional Brings 25+ Years of Experience to the Vancouver-Based Organization

    Vancouver, BC – October 26, 2022 – Variational AI, developer of generative AI-based drug discovery platform for novel kinase inhibitors, today announced that it has added industry and scientific leader Jennifer Hamilton, Ph.D. as a company advisor. Hamilton joins current advisor Nancy Harrison, who brings more than 30 years of industry experience to Variational AI. The distinguished advisors will work to ensure that Variational AI’s generative AI platform strategy is informed by leading drug discovery and development industry expertise.

    “We are thrilled to welcome Jennifer as an advisor,” said Handol Kim, co-founder and CEO of Variational AI. “Her expertise in the biotechnology industry has helped numerous Vancouver companies succeed globally and we look forward to utilizing her expertise to continue to grow in the Canadian biotech sector and beyond.”

    Jennifer Hamilton, Ph.D., has worked with biotechnology companies, big pharma and venture capital funds. Most recently, she spent 11 years at Johnson & Johnson Innovation, as country lead responsible for search & evaluation and transactions in Canada. In that role, she scoured universities, incubators, and companies for technologies of interest to Johnson & Johnson and coordinated and monitored research collaborations and license agreements. Prior to that, she spent 15 years in venture capital with Nomura Phase4 Ventures and Rothschild Asset Management. Jennifer has a Ph.D. in experimental pathology from the University of British Columbia.

    “It is an honour to join Variational AI in an advisory capacity,” said Hamilton. “The work being done by the machine learning scientists is differentiated and I look forward to working with the team to change drug discovery for the better.”

    Variational AI uses generative machine learning to discover novel, next generation kinase inhibitors. The company’s discovery engine, Enki, is trained on a large number of kinases to rapidly generate novel and highly selective inhibitors across a broad range of kinase targets.

    About Variational AI

    Variational AI creates novel new molecules the world has never seen before to become medicines faster than ever leveraging the power of generative AI. Variational AI works with leading biopharmaceutical partners and is developing its own internal oncology pipeline. To learn more, visit variational.ai.

    Jordan Bouclin

    October 26, 2022
    Press Release
  • Variational AI Adds Leading Oncology Researchers to Scientific Advisory Board

    Variational AI Adds Leading Oncology Researchers to Scientific Advisory Board

    Leading Cancer and Drug Discovery Biologists Dr. John F. Boylan and Dr. Mads Daugaard Join SAB

    Vancouver, BC – June 27, 2022 – Variational AI, developer of generative AI-based drug discovery platform for novel kinase inhibitors, today announced that it has added industry and scientific leaders Dr. John F. Boylan and Dr. Mads Daugaard to the company’s Scientific Advisory Board.

    “We are pleased to welcome Drs Boylan and Daugaard to our scientific advisory board,” said Handol Kim, co-Founder and CEO, Variational AI. “Their respective expertise in cell biology and biology complements our existing strengths in machine learning and chemistry and will help us focus on rapidly developing novel multi-targeted kinase inhibitors for oncology. We look forward to working with our SAB members to bring new therapeutics to market to positively impact patient outcomes.”

    Dr. John F. Boylan is a cell biologist by training focused on oncology drug discovery with a record of clinical success, contributing to 12 development candidates, 8 drugs that reached first-in-human clinical trials, and one approved drug; Vemurafenib (mutant BRAF inhibitor).  His broad drug discovery success encompasses small molecule, antibody, and antibody drug conjugate modalities. Dr. Boylan has led multidisciplinary teams and departments seeking to discover novel therapeutic biology that resulted in drug candidate selection. With expertise in all stages of drug discovery, Dr. Boylan has the ability to collaborate across disciplines and functions, manage multiple projects, evaluate key business drivers, and maintain focus on the critical path. He is the co-founder of f5 Therapeutics, a pharmaceutical company dedicated to the development of first-in-class protein degradation small molecules for the treatment of diseases with high unmet medical need.  He has excelled  in research leadership roles at Amgen, Roche, and Celgene. Dr. Boylan currently serves as vice president of scientific strategy at Exelixis, helping to define the scientific approach underlying the development of the company’s biotherapeutics pipeline.

    Dr. Mads Daugaard is head of the Molecular Pathology and Cell Imaging Unit, senior research scientist at Vancouver Prostate Center (VPC), and associate professor at the Department of Urologic Sciences, University of British Columbia (UBC). He operates in the translational cancer research space, integrating basic cancer discovery research with experimental therapeutic and diagnostic development in high-risk adult and childhood solid tumors. As part of his translational research focus, Daugaard has established the therapeutic development companies VAR2 Pharmaceuticals and OncoMal (2012), and the cancer diagnostics company VARCT Diagnostics (2017) to facilitate translation of his research towards the clinical arena. In 2021, Daugaard cofounded Rakovina Therapeutics where he currently serves as President and CSO. He is a co-principal investigator of the VPC small-molecule drug development pipeline ADDUCT. He received the 2019 Robert J. Arceci Innovation Award from the St. Baldrick’s Foundation in 2019 and the Prostate Cancer Canada Rising Star Award in 2014.

    Drs. Boylan and Daugaard join current SAB members Dr. Artem Cherkasov, Dr. Alexander Tropsha, and Dr. Robert N. Young. The distinguished board members will work to ensure that Variational AI’s generative AI platform is informed by leading medicinal and computational chemistry expertise.

    Variational AI uses generative machine learning to discover novel, multi-targeted kinase inhibitors. The company’s discovery engine, Enki, is trained on a large number of kinases to rapidly generate novel and highly selective inhibitors across a broad range of kinase targets.

    About Variational AI

    Variational AI uses state-of-the-art machine learning in a data-efficient method to rapidly generate novel and diverse compounds that are optimized for multiple properties to avoid the most common causes of drug attrition and increase clinical probability of success. Variational AI works with leading biopharmaceutical partners and is developing its own internal pipeline. To learn more, visit variational.ai.

    Media Contact
    Jordan Bouclin & Rita Murphy
    SVM Public Relations
    (401)490-9700
    variationalai@svmpr.com

    Jordan Bouclin

    June 27, 2022
    Press Release

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