Why Life Sciences?

Quantum machine learning is especially fit to address classical computing limitations across many life science areas such as drug discovery, clinical research, and diagnostics.

Drug Discovery

A long, expensive process limited by high complexity.

  • Costs $314M to $2.8B per drug [1]

  • Takes 12 years from candidate to launch [2]

Contributing Factors: High dimensionality, Accuracy vs speed trade-off, High cost of computational resources

Tasks: Binding affinity prediction, RNA structure prediction, Protein docking, Target validation

Clinical Trials

A costly, high-failure industry due to suboptimal trial design.

  • $29M to $135M per therapy [3]

  • Up to 10 or more years to conduct [4]

  • 90% failure rate [5]

Contributing Factors: High dimensionality, Limited interpretability, High cost of computational resources

Tasks: Patient stratification, Biomarker selection, Cohort identification, Site selection

Diagnostics

Where high dimensionality is creating life-threatening delays.

  • In 2022, breast cancer caused over 670,000 deaths [6]

  • Early cancer diagnosis saves lives, cuts treatment costs [7]

Contributing Factors: Unstructured data, High complexity of data, Low scalability, Accuracy vs speed trade-off, High cost of computational resources

Tasks: Medical imaging, Personalized medicine, Accurate diagnostics

Our Research

Drug Discovery

Our own hybrid quantum-classical neural network for binding affinity prediction.

  • 40% reduction in training times and costs

  • 6% improvement in accuracy

👉 Research published in Nature

Clinical Trials

Quantum-enhanced solution for optimizing patient stratification.

  • 100x faster than classical algorithms

  • Mitigates biases in stratification

👉 Research Overview

Diagnostics

Our own unsupervised method for detection of breast cancer in medical images.

  • 10x faster than classical algorithms

  • Maintains accuracy of supervised methods

👉 Research published on ArXiv

Sources

[1] Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018

[2] Fast to first-in-human: Getting new medicines to patients more quickly

[3] How Much Does a Day of Delay in a Clinical Trial Really Cost?

[4] Step 3: Clinical Research

[5] Why 90% of clinical drug development fails and how to improve it?

[6] Breast cancer fact sheet

[7] Early cancer diagnosis saves lives, cuts treatment costs