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Tag: drug discovery

  • Scientists Gather to Confront the Doomsday Risks of ‘Mirror Life’

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    The prospect of creating “mirror life”—synthetic cells made from molecules that are mirror images of those found in nature—remains completely hypothetical. Still, the potential consequences are so dire that experts from around the world are gathering to discuss how to prevent the worst-case scenario.

    This week, scientists, engineers, policymakers, and other stakeholders will convene in Manchester, U.K., for Engineering and Safeguarding Synthetic Life 2025. This annual international conference explores the risks, challenges, and opportunities in researching and building synthetic life. Mirror life is emerging as a topic worthy of substantial discussion, as many scientists warn that creating such cells could pose unprecedented and irreversible risks to human health and the environment.

    “Pretty much everybody agrees” that mirror-image cells would be “a bad thing,” John Glass, a synthetic biologist at the J. Craig Venter Institute, told Nature. At the same time, some scientists argue that mirror-life research offers potential benefits that shouldn’t be ignored. The question is: How should experts regulate such research to maximize those benefits while minimizing risk?

    Why study mirror life?

    Most biological molecules that make up life on Earth—including all proteins, DNA, and RNA—point either left or right. These molecules are “chiral,” meaning they cannot be superimposed on their mirror image. Just as your right glove only fits on your right hand, chiral molecules can only interact with other molecules of compatible chirality.

    Mirror-image cells would be built from synthetic molecules with the opposite chirality of those found in nature. Whereas DNA is right-handed, mirror DNA would be left-handed, for example. Scientists are still decades away from synthesizing a complete mirror-image cell, but in recent years, they have created some mirror-image biomolecules, such as chirally inverted enzymes that can replicate and transcribe mirror-image DNA and RNA.

    One of the main incentives for creating mirror-image cells is that they could help scientists unravel how chirality emerged in nature, but the building blocks for these cells also hold promise for bioengineering and therapeutic drug discovery. Researchers believe the body’s enzymes and immune system would not readily recognize mirror-image biomolecules, allowing medicines made from them to remain more stable in the bloodstream. The FDA has already approved one such drug to treat chronic kidney disease.

    What are the risks?

    Even these early advancements worry some scientists. The same properties that make these synthetic biomolecules effective as therapeutics would likely allow mirror-image cells to spread uncontrollably throughout the body or nature.

    With the ability to evade immune systems, medicines, predation, and viral infection, experts have warned that mirror-image bacteria could gradually take over the environment. Scientists can only theorize about the consequences of this worst-case scenario, but there is strong evidence to suggest that mirror-image bacteria could catastrophically destabilize the environment and pose significant risks to human health.

    Some believe these risks warrant abandoning the prospect of creating mirror life. Others argue that well-placed restrictions and guidelines could allow research to progress without posing a threat to life as we know it. The question of how to move forward—if at all—will likely stir up a spirited debate at this week’s conference in Manchester.

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    Ellyn Lapointe

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  • Isomorphic inks deals with Eli Lilly and Novartis for drug discovery | TechCrunch

    Isomorphic inks deals with Eli Lilly and Novartis for drug discovery | TechCrunch

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    Isomorphic Labs, the London-based, drug discovery-focused spin-out of Google AI R&D division DeepMind, today announced that it’s entered into strategic partnerships with two pharmaceutical giants, Eli Lilly and Novartis, to apply AI to discover new medications to treat diseases.

    The deals have a combined value of around $3 billion. Isomorphic will receive $45 million upfront from Eli Lilly and potentially up to $1.7 billion based on performance milestones, excluding royalties. Novartis, meanwhile, will pay $37.5 million upfront in addition to funding “select” research costs and as much as $1.2 billion (once again excluding royalties) in performance-based incentives over time.

    “We’re thrilled to embark on this partnership and apply our proprietary technology platform,” DeepMind co-founder and Isomorphic CEO Demis Hassabis was quote as saying in a press release. “The focus we share on advancing groundbreaking drug design approaches and appreciation of state-of-the-art science makes [these] partnership[s] particularly compelling.”

    Fiona Marshall, president of biomedical research at Novartis, added in a statement: “Cutting-edge AI technologies … hold the potential to transform how we discover new drugs and accelerate our ability to deliver life-changing medicines for patients. This collaboration harnesses our companies’ unique strengths, from AI and data science to medicinal chemistry and deep disease area expertise, to realize new possibilities in AI-driven drug discovery.”

    Isomorphic, which Hassabis launched in 2021 under DeepMind parent company Alphabet, draws on DeepMind’s AlphaFold 2 AI technology that can be used to predict the structure of proteins in the human body. By uncovering these structures, the hope is that researchers can identify new target pathways to deliver drugs for fighting disease.

    The tech isn’t perfect. A recent article in the journal Nature pointed out that AlphaFold occasionally makes obvious mistakes and, in many cases, is more useful as a “hypothesis generator” rather than a replacement for experimental data. But the scale at which the model can generate reasonably accurate protein predictions is beyond most methods that came before.

    Researchers recently used AlphaFold to design and synthesize a potential drug to treat hepatocellular carcinoma, the most common type of primary liver cancer. And DeepMind is collaborating with Geneva-based Drugs for Neglected Diseases initiative, a nonprofit pharmaceutical organization, to apply AlphaFold to formulating therapeutics for Chagas disease and Leishmaniasis, two of the most deadly diseases in the developing world.

    The latest version of AlphaFold can generate predictions for nearly all molecules in the Protein Data Bank, the world’s largest open access database of biological molecules, DeepMind announced in October. The model can also accurately predict the structures of ligands — molecules that bind to “receptor” proteins and cause changes in how cells communicate — as well as nucleic acids (molecules that contain key genetic information) and post-translational modifications (chemical changes that occur after a protein’s created).

    Already, Isomorphic is applying the new AlphaFold model — which it co-designed with DeepMind — to therapeutic drug design, helping to characterize different types of molecular structures important for treating disease.

    The pressure’s on for Isomorphic to start generating a profit. In 2021, the company recorded a £2.4 million (~$3 million) loss as it ramped up hiring ahead of opening its second office location in Lausanne, Switzerland.

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    Kyle Wiggers

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