14 Companies Using Quantum Theory To Accelerate Drug Discovery (Including 2 Going Public)

by Andrii Buvailo, PhD          Biopharma insight / New Tools, Products and Technologies

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(Updated: 24.02.2024)

Molecular mechanics (MM) is a traditional computational approach when it comes to modeling in synthetic organic chemistry, medicinal chemistry, and versatile aspects of drug design.

However, MM methods have significant limitations, for example, when used to study electron-based properties within the drug-receptor microenvironment. Quantum mechanical (QM) methods allow for substantial increases in the accuracy of predictions and provide much more relevant models of chemical and biological objects and their interactions, but QM methods are extremely (often prohibitively) computationally costly.

 

Image credit: aislan13 , iStock

However, a series of advancements over recent years have allowed us to expand our horizons in this direction, for example, the emergence of density functional theory (DFT), the overall increase in computation power, and the emergence of distributed cloud-based computational infrastructures.

In this post, I am summarizing several notable computational companies (primarily startups), applying quantum calculation methods—always in conjunction with other methods—for drug discovery, and promising to boost the success rates of pharmaceutical research. 

The companies below are listed in alphabetical order. We intend to update this post in several months; feel free to suggest novel relevant companies to be considered for inclusion in the list. 

 

Aqemia

Aqemia is a spin-off of École Normale Supérieure leveraging disruptive algorithms from 8 years of research led by its CEO and co-founder Dr. Maximilien Levesque. The company focuses on de novo, structure-based design of lead-like molecules by combining quantum and artificial intelligence (AI). A unique quantum-inspired statistical mechanics algorithm that predicts the affinity between a compound and a therapeutic target accurately and 10,000 times faster than the competition. Aqemia’s AI can generate compounds with increasing accuracy by getting feedback from the affinity predictor. 

In February 2022, Aqemia announced a pilot study with Janssen to utilize its quantum physics-driven drug discovery technology to predict the potency of small molecules for a given target based on physics-based calculations for datasets selected by Janssen.

Aqemia recently announced a €30 million addition to its Series A funding, elevating the total investment of the round to €60 million entirely through equity. The initial €30 million was secured in 2022, under the leadership of the French venture capital firm Eurazeo and the public financial institution Bpifrance, with Elaia, a longstanding investor, also contributing.

This funding phase was further extended with the support of Wendel Growth, a French growth equity firm, alongside the continued backing from all of Aqemia's prior investors.

Presently, Aqemia is advancing three of its cancer-targeting drug candidates through preclinical animal testing. Remarkably, these projects have swiftly progressed to the preclinical stage in under two years, with expectations to move into clinical trials by 2025.

 

Algorithmiq

Algorithmiq, founded in 2020 and headquartered in Helsinki, Finland, is a trailblazer in developing quantum algorithms for the life sciences industry, focusing on challenges such as molecular structure prediction and drug development. The company is led by Co-Founder and CEO Professor Sabrina Maniscalco.

With expertise spanning quantum information, complex systems, and computational physics, the company stands at the intersection of technology and drug development​​.

In June 2023, Algorithmiq raised $15 million in a Series A funding round led by Inventure VC, along with contributions from Tesi, Presidio Ventures, and Thames Trust, among other existing backers. This funding is aimed at advancing proof-of-concept work with global pharmaceutical companies, with the goal of significantly reducing the time and cost associated with drug discovery and development​​.

At the core of Algorithmiq's mission is the ambition to harness quantum computing to expedite the drug discovery process, leveraging a proprietary platform, Aurora, and a partnership with IBM to utilize their leading hardware. The company's innovative approach includes a method for extracting information from quantum devices for quantum chemistry simulations and a new framework, Quantum Network Medicine, to address the complexity of cell biology​​.

 

Hafnium Labs

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Comments:

  • Don VAN DYKE 2019-06-27 07:45

    Cloud Pharmaceuticals is another startup using Quantum Theory in drug design.

    reply
    • BiopharmaTrend 2019-06-27 10:02

      Thank you for the suggestion, Don. We will update the list.

      reply
  • Enric Gibert 2019-06-27 16:28

    Pharmacelera is also a startup company applying QM algorithms to accelerate drug discovery

    reply
    • BiopharmaTrend 2019-06-27 17:18

      Thank you very much, Enric, will update the list shortly.

      reply
  • Peter Morgan 2019-08-04 07:14

    Zapata?

    reply
  • Jung 2020-03-04 00:29

    ApexQubit is another one.

    reply
    • BiopharmaTrend 2020-03-23 16:03

      Thank you for the suggestion, Jung, will review ApexQubit and add them to our update shortly.

      reply
  • Erik 2020-08-12 21:24

    FAR Biotech is another one.

    reply
    • BiopharmaTrend 2020-08-19 14:43

      Hi, Erik, thank you for the suggestion, we will review and add the company in the next update.

      reply
  • Max Duckworth 2020-08-15 21:46

    Great article, thank you. I'm involved with another such company, FAR Biotech. I'd be happy to provide you with company background and the details of our technology (which models the drug - receptor interaction entirely at the quantum level and has a search area exceeding 1 trillion novel chemical structures.) Please keep us in mind for your next article in this field. Thank you.

    reply
    • BiopharmaTrend 2020-08-19 14:44

      Hi, Max, thank you for the suggestion, this company is now under review by our analysts and will be added shortly.

      reply
      • Max Duckworth 2020-09-07 19:29

        Dear Sir / Madam,

        Thank you very much indeed for your inclusion of FAR Biotech in this list of companies using quantum modeling for drug discovery. Would it be possible to correct and tweak the description of FAR Biotech in places?

        For example, the company was not founded by Erik Halvorsen, even though we are fortunate that he serves on our board. In addition, our drug discovery & design search space has grown to: i) 1 trillion new chemical entities; ii) 500 million known chemical compounds; and iii) 15,000 repurposed drugs.

        Again, thank you for including us, and please let me know if I could submit an update to the description above.

        Best regards,

        Max

        (443) 742-0675

        reply
        • BiopharmaTrend 2020-09-09 18:55

          Thank you for your corrections, Max, we will update the article promplty.

          reply
  • Ashish Malik 2021-01-24 14:05

    Quantumzyme is also one of the startups which evolves novel proteins based on quantum computing.

    reply
    • BiopharmaTrend 2021-01-25 16:37

      Thank you, Ashish

      reply
      • Ashish Malik 2021-01-31 11:08

        I would recommend to add Quantumzyme as well in the list.

        reply
  • pharmacy software 2022-05-16 06:02

    Thanks for the article on 12 Companies Using Quantum Theory To Accelerate Drug Discovery.Looking  forward for more articles like this.

    reply
  • Max Duckworth 2022-07-11 11:41

    Can you please let readers know why the number of companies featured in this article was reduced after the fact to 12 (from 18)? FAR Biotech is one of the companies no longer featured in this article, despite the comments further above and the company being on the cutting edge of quantum mechanical modeling of biomolecular interactions to fast-track drug discovery. Please let us know the reason. Many thanks, as always!

    reply

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