Developing new drugs and therapies is a costly, time-consuming process that spans many years. Artificial intelligence (AI) offers a promising solution, enabling faster and more cost-effective discovery of new drug candidates. However, to fully harness AI's potential, immense computational power is required – power that only quantum computers can provide.
Researchers often refer to merging AI and quantum computers as "AI on steroids." AI technology is already there, but the success of this synergy still depends on the development of quantum computers, which would help harness the full potential of AI models, particularly in the medical sciences. Is the use of quantum computing in health sciences a matter of years or decades, and why has a breakthrough not yet occurred?
Quantum computing decodes the human body
AI advancements in the past two years have led every major pharmaceutical company to experiment with AI in drug discovery. Systems like AlphaFold 3 by Google DeepMind can model three-dimensional structures of proteins, DNA, and RNA, enabling the analysis of chemical modifications that regulate cellular functions crucial to human health. However, these simulations require immense computational power. This is why the United States and, recently, Europe have been building “AI gigafactories” where, among other applications, companies in the health sciences can train AI models or conduct computations.
Despite this, even the most powerful data centers may soon be insufficient. Classical computers, based on high-performance processors, struggle to simulate complex molecules due to the exponential increase in computational demands. Quantum computers, however, could handle these tasks far more efficiently. Some calculations that would take classical computers hundreds or even billions of years could be completed by quantum computers in just minutes or hours – at least in theory.
Scientists agree that quantum computers are essential for developing new, personalized therapies more quickly, such as cancer treatments. Quantum computers can model quantum mechanical interactions with far greater precision. By simulating electron behavior in molecules, they can help understand how chemical drug molecules interact with biological systems in patients with specific characteristics.
It is no surprise that quantum computing is gaining significant attention from the pharma industry. For instance, in 2024, Merck formed a three-year partnership with HQS Quantum Simulations to develop drug discovery software. In 2023, Bayer and Google Cloud announced a collaboration to accelerate drug development by using Google Cloud’s tensor processing units (TPUs) for large-scale quantum chemistry calculations. The partnership aims to improve in-silico modeling of biological and chemical systems. Moderna and IBM also teamed up to explore the potential of quantum computing and AI to accelerate mRNA research. Another example is Qubit Pharmaceuticals, which offers support in drug discovery "with quantum accuracy" using the Gaia supercomputer with 200 NVIDIA chips.
Through an agreement with IBM, the first experimental quantum computer was set up at the Cleveland Clinic, where scientists are using the super-computer to explore new treatment methods and conduct biomedical research.
Super-fast calculations with super-fatal errors
Although quantum computing research has been ongoing for years, efficient and stable machines have yet to be developed. Several obstacles remain. These devices rely on yet-to-be-fully-understood principles of quantum physics. Building quantum computers is expensive and energy-intensive, with the stability of quantum states requiring temperatures close to absolute zero (−273°C). While major tech companies like Google, IBM, Intel, Microsoft, and NVIDIA are developing quantum computers, their performance has not yet surpassed that of classical processors. The biggest challenge, however, lies in calculation errors, which currently exclude quantum computers from use in medicine, where errors could be life-threatening.
Nevertheless, the quantum race continues. IBM aims to develop the first practical quantum computer by 2028. In December 2024, Google introduced its new quantum processor, Willow, which, in tests, performed calculations in less than 5 minutes that would take one of the fastest available supercomputers 10 septillion years (10,000,000,000,000,000,000,000,000,000 years).
NVIDIA organizes its first-ever Quantum Day on 20 March 2025. The company’s founder and CEO, Jensen Huang, invited industry leaders to discuss the development of quantum computing. Also, investor optimism remains high. In February 2025, quantum computing startup QuEra secured $230 million in funding, supported by giants like Google Quantum AI and the SoftBank Vision Fund. As of 2025, an estimated 100 to 200 quantum computers are in use worldwide, with many more in development. Thousands of quantum computing projects are underway, reflecting the rapid advancement of the field. According to the report Quantum Computing Market – Forecasts from 2025 to 2030, the market is valued at approximately $1.79 billion in 2025 and is projected to grow at a compound annual growth rate (CAGR) of 31.64%, reaching $7.08 billion by 2030.
Quantum computing's role in medicine
Some experts warn that developing quantum computers for practical use could take years, if not decades. A 2020 study estimated that error-free, reliable quantum computations are unlikely before 2026. Some experts predict that the first practical quantum computers may not appear until 2039.
Quantum computing holds the potential to solve multidimensional problems, such as those encountered in medicine. Most of the work on quantum computers is focused on their applications in healthcare. The stakes are high, with the potential for effective treatments that still elude medical science.
