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    Home > Active Ingredient News > Drugs Articles > Forbes AI Emerging 50: 6 biotech and pharmaceutical companies on the list

    Forbes AI Emerging 50: 6 biotech and pharmaceutical companies on the list

    • Last Update: 2022-08-15
    • Source: Internet
    • Author: User
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    Recently, Forbes released its annual AI 50 list, jointly launched by Forbes and Sequoia Capital, to introduce 50 private companies in North America that effectively and uniquely utilize artificial intelligence (AI) technolo.


    AI has been integrated into our lives in many ways, and by 2024, the investment in AI research and application will reach 500 billion US dolla.


    Brightseed

    Brightseed

    There are many biologically active compounds in plants, and their interactions with the human body can have important effects on human heal.


    Brightsee's goal is to dig deep into the biologically active compounds found in nature's plants and understand how they interact with the human bo.


    The company uses AI-based software systems to explore connections between plants and human health, discovering bioactive compounds that may improve human heal.


    Deepcell

    Deepcell's technology platform can accurately identify and isolate single cells based on cell morphology without the use of staining or cell labeli.


    Accurately discover and isolate single cells based on cell morphology without staining or labeling cel.


    The sensitivity of this system can even find 1 rare cell in 1 billion cel.


    Entos

    Entos' artificial intelligence platform combines algorithms that predict the characteristics of drug candidates and robot-assisted automated labs to rapidly synthesize and optimize small molecule anti-cancer therapi.


    Combining algorithms that predict the characteristics of drug candidates and robotic-assisted automated labs to rapidly synthesize and optimize small-molecule anticancer therapeuti.


    Generate Biomedicines

    Generate Biomedicines was founded by Flagship Pioneering, a well-known healthcare investment fi.


    By analyzing hundreds of millions of known proteins, machine-learning systems discover statistical patterns that link amino acid sequences to protein structure and functi.


    There is no need to rely on trial-and-error high-throughput screening to develop protein drugs targeting specific targe.


    Genesis Therapeutics

    Genesis Therapeutics was founded with the support of the famous Silicon Valley venture capital firm Andreessen Horowitz and othe.


    The company's technology platform, called PotentialNet, has the ability to unlock the 3D structural dynamics of protein-ligand complex.


    It remains highly accurate in predicting compound potency and selectivity against previously elusive protein targets

    To target the most challenging protein targets, the company combines machine learning-based predictive models with molecular simulation platforms to develop novel molecular simulation systems based on decades of research in molecular dynamics and quantum mechani.


    Earlier this month, the company partnered with Eli Lilly and Company to use its AI drug discovery platform to discover innovative treatments for up to five targets across a broad range of therapeutic are.

    Verge Genomics

    Verge Genomics

    Many investigational therapies that show promise in animal models fail to achieve the expected success in human clinical trials, in part because animal models sometimes fail to reflect the complexity of human disea.

    VisionGen's strategy is based on datasets of the brain transcriptomes of patients with multiple neurodegenerative diseases, using AI-based unbiased algorithms to provide insights related to innovative disease causal mechanisms in patient populations segmented by genetic characteristics , thereby discovering therapeutic targets for complex diseas.

    Based on datasets of the brain transcriptomes of patients with multiple neurodegenerative diseases, discover the underlying causes of complex diseases by using unbiased AI-based algorithms to provide insights related to innovative disease causal mechanisms in patient populations segmented by genetic signatures therapeutic targ.

    Interview with Zhang Xinli, the 35th Technological Innovator of the Year: When you see an opportunity, don't be afraid to chase it

    Image source: Verge Genomics official website

    Many neurological diseases are caused by complex interactions between many genes, and Verge's AI platform is able to map the hundreds of genes that cause disease, and then find drugs that target all of th.

    The Verge partnered with Eli Lilly last year to use its AI platform to develop novel treatments for amyotrophic lateral sclerosis (AL.

    The Forbes report noted that an ALS drug developed by the company using the AI ​​platform is expected to enter clinical trials this ye.

    Entering 2022, the industry's enthusiasm for artificial intelligence has continued, and many drugs designed by artificial intelligence have entered the clinical sta.

    At the WuXi AppTec Health Industry Forum held this year, .

    Daphne Koller, founder and CEO of insitro, a well-known artificial intelligence platform company, said that looking forward to the future, machine learning and artificial intelligence will become one of the core technologies for new drug developme.

    In all stages of new drug development , from target discovery to compound design, from segmenting patient groups to tracking their progress, and guiding which patients to use after the drug is on the mark.

    "Artificial intelligence can make many processes bett.

    " However, industry experts also pointed out that the industry should not be overly optimist.

    Artificial intelligence has its own real value in the industry, and industry colleagues also need to have objective and rational expectatio.

    Machine learning and artificial intelligence will become one of the core technologies for new drug development, and the industry should not be overly optimistic that it can be used in all stages of new drug developme.

    Artificial intelligence has its own real value in the industry, and industry colleagues also need to have objective and rational expectatio.

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