Introduction
The partnership between Zapata Computing and Biogen represents a significant milestone in applying quantum computing to pharmaceutical research and drug discovery. Announced in 2020, this collaboration brought together Zapata’s expertise in quantum software and algorithms with Biogen’s deep knowledge in neuroscience and drug development. The partnership focused on exploring how quantum computing could address some of the most computationally challenging problems in drug discovery, particularly in the areas of molecular simulation and protein folding. As drug development costs continue to soar and the complexity of targeting neurological diseases increases, both companies recognized the potential of quantum computing to provide computational advantages that could accelerate the discovery of new therapeutic compounds. The collaboration aimed to develop practical quantum applications that could be implemented on near-term quantum devices, focusing on hybrid algorithms that combine classical and quantum computing resources to solve real-world pharmaceutical challenges.
Challenge
The pharmaceutical industry faces enormous challenges in drug discovery, with the average cost of bringing a new drug to market exceeding $2.6 billion and taking over a decade. For Biogen, specializing in neurological conditions like Alzheimer’s disease and multiple sclerosis, the challenges are particularly acute. The complexity of biological systems, especially in the brain, requires computational modeling of molecular interactions at scales that push the limits of classical computing. Traditional computational methods struggle with the exponential scaling of molecular simulation problems, making it difficult to accurately predict drug-protein interactions, optimize molecular properties, and understand the complex mechanisms of neurological diseases. Additionally, the vast chemical space of potential drug compounds makes exhaustive searching computationally prohibitive. Biogen needed innovative computational approaches to accelerate their drug discovery pipeline, reduce costs, and improve the success rate of identifying viable drug candidates. The company recognized that quantum computing’s ability to naturally represent quantum mechanical systems could provide advantages in molecular simulation and optimization tasks that are fundamental to drug discovery.
Solution
Zapata Computing developed a comprehensive quantum software solution leveraging their Orquestra platform to address Biogen’s computational challenges. The solution focused on implementing variational quantum algorithms (VQAs) and quantum machine learning techniques specifically tailored for molecular simulation and drug discovery applications. The core of the solution involved developing quantum-enhanced models for predicting molecular properties and drug-target interactions. Zapata implemented quantum approximate optimization algorithms (QAOA) for molecular configuration optimization and variational quantum eigensolvers (VQE) for calculating ground state energies of molecular systems. The team also developed novel quantum machine learning algorithms that could identify patterns in molecular data that classical algorithms might miss. A key innovation was the creation of hybrid workflows that seamlessly integrated quantum algorithms with Biogen’s existing classical computational infrastructure. This approach allowed the companies to leverage the strengths of both quantum and classical computing, using quantum processors for specific subroutines where they could provide advantages while maintaining compatibility with established pharmaceutical research workflows.
Implementation
The implementation of the quantum computing solution followed a phased approach designed to deliver incremental value while building toward more ambitious applications. Initially, Zapata’s team worked closely with Biogen’s computational scientists to identify specific use cases where quantum algorithms could provide near-term advantages. The implementation began with proof-of-concept demonstrations on small molecular systems, validating the accuracy of quantum algorithms against known classical results. Zapata utilized their Orquestra platform to orchestrate workflows across multiple quantum backends, including devices from IBM, Rigetti, and IonQ, as well as quantum simulators for algorithm development and testing. The teams developed custom quantum circuits optimized for the noise characteristics of current quantum hardware, implementing error mitigation techniques to improve result reliability. Data preprocessing pipelines were established to transform Biogen’s molecular datasets into formats suitable for quantum processing. The implementation also included extensive benchmarking protocols to compare quantum algorithm performance against classical baselines, ensuring that any claimed quantum advantages were rigorously validated. Training programs were conducted to upskill Biogen’s research teams on quantum computing concepts and the use of Orquestra platform.
Results and Business Impact
The partnership yielded several significant results that demonstrated the potential of quantum computing in pharmaceutical research. Initial implementations showed that quantum algorithms could match classical performance for small molecular systems while using fewer computational resources, indicating a path toward quantum advantage as hardware scales. The quantum machine learning models developed through the collaboration identified previously unknown molecular features relevant to drug-target binding, providing new insights for Biogen’s drug discovery programs. Specifically, the quantum-enhanced models showed improved accuracy in predicting molecular properties for certain classes of compounds relevant to neurological drug development. From a business perspective, the partnership positioned Biogen as an early adopter of quantum computing in the pharmaceutical industry, enhancing their reputation for innovation. The collaboration also helped establish best practices for implementing quantum computing in drug discovery workflows, creating intellectual property and know-how that could provide competitive advantages. While full quantum advantage for large-scale drug discovery problems remains dependent on future hardware improvements, the partnership successfully demonstrated viable near-term applications and established a framework for scaling quantum applications as the technology matures.
Future Directions
The future directions of the Zapata-Biogen partnership focus on scaling quantum applications to address increasingly complex pharmaceutical challenges. As quantum hardware continues to improve in terms of qubit count, coherence times, and gate fidelities, both companies plan to tackle larger molecular systems and more sophisticated drug discovery problems. Future work includes developing quantum algorithms for protein folding prediction, a critical challenge in understanding disease mechanisms and designing targeted therapies. The partnership also aims to explore quantum computing applications in personalized medicine, using quantum machine learning to analyze complex genomic and clinical data. Additionally, there are plans to investigate quantum algorithms for optimizing clinical trial design and patient stratification. Both companies are committed to contributing to the broader quantum computing ecosystem by publishing research findings and collaborating with academic institutions. The long-term vision includes establishing quantum computing as a standard tool in the pharmaceutical research toolkit, similar to how high-performance computing transformed drug discovery in previous decades.