When AI cracks the mystery of aging

A new study paves the way for a deeper understanding of biological processes. Artificial intelligence (AI) and quantum computing could revolutionize our approach to human health.

In a recent paper published in WIREs Computational Molecular Science, researchers at the AI-based drug discovery company, Insilic Medicinedemonstrated how quantum computing can be integrated into the study of living organisms to provide a better understanding of biological processes such as aging and disease.

In May 2023, Insilico, the University of Toronto Acceleration Consortium, and the Foxconn Research Institute published research that successfully demonstrated the potential benefits of quantum generative adversarial networks in generative chemistry.

AI, quantum computing and complex systems physics

In this latest paper, Insilico researchers present a holistic picture of how combining methods from AI, quantum computing, and complex systems physics can help researchers advance new understandings of human health. They also detail the latest discoveries in physics-driven AI.

While AI has been an invaluable tool for helping researchers process and analyze large, complex biological data sets to find new pathways to disease and link aging and disease at the cellular level, it still faces challenges in applying this knowledge to more complex interactions. complexes within the body.

Understanding living organisms: a great challenge

To fully understand the inner workings of living organisms, researchers need multimodal modeling methods that can deal with three main areas of complexity: scale complexity, algorithm complexity, and increasing dataset complexity.

Although we are not a quantum company, it is important to leverage capabilities to take advantage of the speed offered by new hybrid IT solutions and hyperscalers. As this computing becomes more widespread, it may be possible to perform highly complex biological simulations and discover personalized interventions with desired properties for a wide range of diseases and age-associated processes. We are delighted to see our research center in the UAE producing valuable information in this area says Alex Zhavoronkov, PhD, founder and co-CEO of Insilico Medicine.

In each hierarchical scale there is a method most used to study that level of organization. AI has potential at each of these levels. Quantum computing offers opportunities to accelerate and improve the efficiency of AI solvers and traditional techniques. Credit: Insilico Medicine

Quantum computing: a great asset for research

Biological processes in living systems extend from cells to organs and the entire body, with many complex interactions between systems. Interpreting these processes requires working at several scales simultaneously. And access to biological data has reached previously unimaginable levels.

Quantum computing, the researchers write, is ideally positioned to augment AI approaches – allowing researchers to interpret multiple levels of the biological system simultaneously. Because the qubits simultaneously contain values ​​of 0 and 1, while conventional bits only contain values ​​of 0 or 1, qubits have significantly greater speed and computing power.

The authors note that major advances in Quantum computing are already underway, including IBM’s recent launch of a utility-scale quantum processor and the company’s first modular quantum computer, which has already begun operations.

Call for Physics-Guided AI

Ultimately, the authors call for a physics-driven AI approach to better understand human biology – a new field that combines physics-based models and human biology models. neural networkswhich is already underway.

By combining AI methods, Quantum computing and the physics of complex systems, scientists can better understand how, as the authors write, “collective interactions of smaller-scale elements within a cell, organism, or society generate emergent characteristics that can be observed at larger scales and levels of reality“.

Illustration caption: Biological networks are interconnected. Just as it is not enough to know the ingredients to know how to prepare a dish, it is not enough to know the list of genes or proteins to understand how they interact. Credit: Insilico Medicine

Article: “Complexity of life sciences in the quantum and AI era” – DOI: 10.1002/wcms.1701


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