Saurabh Singal, Founder of Molecule AI, examines the impact that quantum computing can, and will have, on drug discovery and development.

A quantum leap in pharma

In 2019, Google announced that its quantum computer had achieved a groundbreaking milestone1 – solving a problem in 200 seconds that would take the most powerful supercomputers 10,000 years to complete. Dubbed “quantum supremacy,” this achievement hinted at the revolutionary potential of quantum computing (QC). For industries like pharmaceuticals, where the stakes are measured in human lives and billions of dollars, the promise of QC is nothing short of transformative.

Another dramatic instance of QC’s power comes from the pharmaceutical sector itself. In 2023, Forschungszentrum Jülich and Lund University researchers utilised D-Wave’s quantum annealer to address the protein folding problem2. This breakthrough accelerated the discovery of a promising drug candidate and showcased how QC could unlock mysteries previously deemed unsolvable.

Adding to these stories, IBM, in collaboration with MIT researchers, tackled one of the toughest challenges in quantum chemistry – calculating the ground-state energy of complex molecules3. They demonstrated that quantum computers could simulate the electronic structure of molecules with an accuracy unattainable by classical methods. This achievement paves the way for designing novel compounds in record time.

Understanding the quantum advantage

Unlike classical computers, which rely on binary bits representing 0s and 1s, quantum computers operate using quantum bits or qubits. These qubits leverage two key principles of quantum mechanics: superposition4 and entanglement5.

Superposition allows qubits to exist in multiple states simultaneously, exponentially increasing the computational power of quantum systems. For example, while a classical bit can be 0 or 1, a qubit can represent 0, 1, or any combination of these states simultaneously.

Entanglement enables qubits to be interconnected in such a way that the state of one qubit is directly related to the state of another, regardless of distance. This property allows quantum computers to perform complex calculations in parallel rather than sequentially, as classical computers do.

The foundation of a quantum computer is its quantum processor, also known as a quantum processing unit (QPU). The QPU consists of an array of qubits interconnected via quantum gates, forming a quantum circuit that enables computations. This setup allows quantum computers to tackle problems considered intractable for classical machines.

The promise of quantum computing in drug development

Drug development is arduous, with over 90% of drug candidates failing during clinical trials. Quantum computing offers a paradigm shift by addressing key challenges in the pharmaceutical R&D pipeline.

1. Molecular modelling and simulations

Traditional molecular simulations often rely on approximations due to the computational limits of classical computers. This can lead to inaccuracies in predicting how molecules behave and interact with biological systems. Quantum computers, however, can simulate quantum systems –such as interacting molecules – directly and with unparalleled accuracy.

  • Protein folding: Predicting protein structures and their folding mechanisms is a notoriously complex problem. QC enables precise modelling of these processes, aiding in the identification of druggable targets.
  • Drug-protein interactions: By simulating how drug candidates interact with biologically relevant proteins, quantum computers can identify potential therapeutic compounds more effectively.

2. Accelerating drug discovery

Quantum machine learning algorithms offer insights into molecular behaviour that surpass classical machine learning models. They enhance the accuracy of predictions for biological activity, toxicity, and efficacy, speeding up the identification of promising drug candidates.

For instance, predicting RNA structures – a critical task in nucleic acid drug discovery – has become more efficient with quantum technologies. Imperial College London and Zhejiang Lab researchers have used quantum processors to advance molecular docking and RNA folding predictions6.

3. Optimising clinical trials

Quantum computing’s ability to analyse vast datasets rapidly makes it invaluable for clinical trial optimisation:

  • Patient stratification: Identifying suitable patient groups based on genetic and demographic data.
  • Trial site selection: Optimising site locations to reduce costs and improve trial efficiency.
  • Causality analysis: Understanding the root causes of side effects through advanced modelling, enabling better safety surveillance.

Real-world applications and collaborations

The pharmaceutical industry has already embraced QC, with several notable collaborations highlighting its potential:

  • Pfizer and Gero7,8: Using hybrid quantum-classical architectures for therapeutic target discovery in fibrotic diseases.
  • Bayer and Google9: Leveraging quantum chemistry to predict molecular properties at the atomic level.
  • Pasqal and Qubit Pharmaceuticals10: Developing quantum-classical approaches to analyse protein hydration.
  • Cleveland Clinic and IBM11,12: Established the first quantum computer dedicated to healthcare research.

Furthermore, companies like Merck13, Roche, and Johnson & Johnson are driving innovation, with a 70% surge in QC-related patent filings reported in recent years.

The challenges ahead

Despite its promise, the road to widespread adoption of QC in pharmaceuticals is fraught with challenges. The fact that quantum computers are still in their infancy means that error rates in quantum gates and limited qubit scalability are significant hurdles. There is also a shortage of talent due to the highly specialised knowledge required for QC. Pharma companies already struggle to attract digital talent for less niche technologies, making QC expertise even harder to secure. Lastly, the high cost of quantum systems limits access for smaller players in the pharmaceutical sector.

The future of quantum computing in pharma

Industry experts predict that global pharmaceutical spending on QC will reach billions by 2030. The most significant impact is expected in the preclinical and clinical stages, where failure rates are highest. By reducing errors and increasing efficiency, QC could drastically lower costs and accelerate timelines.

Broader implications

Beyond R&D, QC may influence other aspects of the pharmaceutical value chain:

  • Regulatory approval: QC can streamline the submission process to regulatory bodies like the FDA by providing more accurate simulations and reducing error rates.
  • Supply chain optimisation: Managing complex logistics for drug distribution could benefit from QC’s advanced computational capabilities.

Conclusion

Quantum computing is not just a technological evolution; it’s a revolution. While significant challenges remain, the progress made by industry leaders and research institutions underscores QC’s vast potential. By addressing inefficiencies in drug development and clinical trials, QC promises to save time, reduce costs, and improve patient outcomes.

The pharmaceutical industry stands at the cusp of a quantum leap. The question is no longer whether quantum computing will transform drug development, but how quickly it will become an integral part of the process. For companies willing to invest in the groundwork today, the rewards could redefine the future of medicine.

From DDW Volume 26 – Issue 2, Spring 2025 Read the digital issue

References:

  1. Gibney E. Hello quantum world! Google publishes landmark quantum supremacy claim. Nature News 2019 
  2. TecXplore. Quantum computer solves protein puzzle  
  3. IBM Has Used Its Quantum Computer to Simulate a Molecule—Here’s Why That’s Big. MIT Tech Review 
  4. Biogen collaborates with Accenture Labs to accelerate drug discovery. Biopharma Reporter 
  5. Quantum medicine: how quantum computers could change drug development: https://www.clinicaltrialsarena.com/features/quantum-computers-drug-development/?cf-view
  6. Towards using quantum computing to speed up drug development. Imperial News. Imperial College London 
  7.  Longevity Biotech Startup Gero Demonstrates the Power of Quantum Computing in Drug Design. Drug Discovery Today 
  8. Longevity Biotech Gero Entered a Research Collaboration with Pfizer to Discover Potential Targets for Fibrotic Diseases. Pfizer website 
  9. Bayer taps Google’s quantum power for drug discovery. pharmaphorum 
  10. Pasqal and Qubit Pharmaceuticals partnership. Pasqal website 
  11. Cleveland Clinic and IBM Unveil First Quantum Computer Dedicated to Healthcare Research. IBM website
  12. How Quantum Computing Is Accelerating Drug Discovery. Forbes
  13. Merck and HQS Quantum Simulations Cooperate in Quantum Computing. Quantum Simulations

Saurabh SingalAbout the author:

Saurabh Singal is a serial entrepreneur, having founded two AI companies, Molecule AI and KnowDis AI. Molecule AI has developed Molecule GEN, an award-winning AI-driven integrated drug discovery platform. Singal is a graduate of IIT Delhi and Carnegie Mellon University.