Tag: quantum computing

Categories
Digital Health MedTech

Pharma’s Quantum Bet: Can Qubits Fix Drug R&D’s 90% Failure Rate

Quantum computing in pharma drug discovery R&D

The Promise

Pharma spends billions on R&D only to see 90% of drug candidates fail in trials. At the heart of the problem: chemistry is a quantum system, but we’ve been simulating it with classical approximations. Quantum computing, in principle, can simulate molecules and protein folding with physics-native precision, potentially cutting years and billions from discovery pipelines.

The Reality

We are not about to quantum-simulate an entire antibody. Today’s quantum machines remain noisy, small, and fragile. The most credible progress has come from hybrid models, where quantum handles a computational bottleneck and classical HPC does the rest. For example:

  • Cleveland Clinic & IBM: Predicted Zika virus protein fragments more accurately than AlphaFold using a hybrid quantum-classical framework (Cleveland Clinic).
  • Japan Tobacco & D-Wave: Used quantum annealing to train generative AI, producing more “drug-like” molecules than classical methods (MedPath).
  • Biogen & Accenture: Quantum-enabled molecular comparison delivered richer structural insights than classical screening (Accenture).

Each success is narrow, but collectively they show a pragmatic pattern: don’t replace classical, augment it.

The European Edge

Europe is well-positioned. Startups like Pasqal (France) are already running protein hydration analyses on neutral-atom quantum computers (Qubit Pharmaceuticals). The Quantum Technologies Flagship (€1bn over 10 years) funds such projects (EU Commission). Combined with Horizon Europe grants and EuroHPC’s hybrid supercomputers, pharma here has access to sovereign infrastructure and public co-funding that US peers often lack.

Strategic Takeaway

For European pharma and biotech:

  • Think long-term: validated drug design use cases are 5–15 years out (Roche).
  • Back hybrids: near-term ROI lies in workflows where quantum complements AI, not replaces it.
  • Partner early: collaborations with quantum startups and HPC centres are essential to de-risk.

Quantum won’t cure R&D inefficiency overnight. But when 9 in 10 candidates still fail, even a narrow, validated quantum edge could mean the difference between another failed trial and Europe’s next blockbuster drug.

This content has been enhanced with GenAI tools.

Categories
Digital Health

Quantum Computing in Healthcare: Breakthrough or Expensive Distraction?

Quantum Computing in Healthcare - IBM Quantum One in Cleveland Clinic.
Quantum Computing in Healthcare - IBM Quantum One in Cleveland Clinic. Source: Cleveland Clinic

Quantum computing is the latest shiny object in healthcare IT. Headlines trumpet its ability to solve the unsolvable, to accelerate drug discovery, and to personalise medicine at a level classical AI can only dream of. The reality, however, is a little noisier, literally. In 2025, we are firmly in what researchers call the NISQ era. NISQ stands for Noisy Intermediate-Scale Quantum, where machines are powerful but error-prone, and purely quantum solutions remain more PowerPoint than product.

Why the Hype?

The hype is not entirely misplaced. Biology and chemistry are inherently quantum systems. Simulating how a drug molecule interacts with a protein is not just hard for classical supercomputers; it’s unnatural. Classical methods rely on approximations. Quantum computers, in theory, model these interactions directly. That’s why pharma giants are experimenting: Cleveland Clinic has an IBM Quantum System One installed on-site, the first dedicated to healthcare. Early results show hybrid quantum-classical workflows can outperform DeepMind’s AlphaFold on narrow protein-folding tasks.

Why the Reality Check?

The breakthroughs so far are niche, fragile, and deeply dependent on clever hybridisation with classical HPC. A systematic review of nearly 5,000 research papers (2015–2024) found no consistent evidence that quantum machine learning currently beats classical methods for healthcare. Many proofs of concept run in “noiseless simulations” that collapse when ported to real hardware. And the qubit counts remain too low for practical drug-scale simulations.

Even in genomics, often billed as the killer app for quantum computing, the maths doesn’t add up. Encoding billions of data points into qubits introduces overhead that wipes out theoretical speedups. For now, Europe’s quantum advantage is likely to remain incremental: narrow use cases, tightly scoped, with the real value in hybrid algorithms.

Why Europe Must Care Now: Security

The most immediate and non-negotiable issue is not discovery but security. A sufficiently powerful quantum machine will break today’s public-key cryptography (RSA, ECC). Healthcare is especially exposed, with decades-long data sensitivity. The threat isn’t theoretical, it’s already here. Adversaries are harvesting encrypted medical data today, betting on decrypting it later (“Harvest Now, Decrypt Later”). The US NIST has finalised post-quantum cryptography standard (CRYSTALS-Kyber, CRYSTALS-Dilithium) in 2024. GDPR’s mandate for “appropriate technical measures” means EU hospitals, medtech, and pharma firms will have to migrate.

Strategic Takeaway

Quantum computing in healthcare is not snake oil, but nor is it a silver bullet. In the short term, Europe’s smartest bets are twofold:

  • Defensive: Migrate to post-quantum cryptography before Y2Q arrives.
  • Pragmatic: Invest in hybrid models where quantum adds value to a specific pain point, not the whole pipeline.

Quantum may indeed change healthcare. But for now, the winning strategy is less “revolution at the bedside” and more “upgrade in the back office.” The future belongs to those who can separate signal from quantum noise.

This content has been enhanced with GenAI.