Interview Questions for Bill Shipman, Co-founder and CTO of Polaris Quantum Biotech:
Fast-Track Drug Discovery with Quantum Computing
Sit down with Bill Shipman, co-founder and CTO of Polaris Quantum Biotech, a North Carolina company revolutionizing drug discovery through quantum computing. Shipman discusses how Polaris' platform, QuADD, supercharges drug discovery, the benefits of quantum for this sector, and the future impacts of scaling quantum hardware.
Question: What's the deal with Polaris?
Answer: Polaris offers the QuADD platform, a quantum-powered drug design tool. QuADD's unique capabilities help clients rapidly identify drug candidates compared to traditional methods by zeroing in on lead molecules. The platform analyses vast chemical databases-billions of molecules-to find ideal candidates with superior properties like solubility and molecular fit.
Question: Quantum for drug discovery? What's the big deal?
Answer: Traditional drug discovery relies on finding novel molecules that bind effectively with disease-causing proteins. Today's computer-aided drug design systems can only explore a fraction of what's possible, as they can only scan a maximum of 1 million molecules. However, QuADD, using quantum power, can sift through chemical spaces billions of times larger, upping the odds of discovering the optimal molecule and speeding up the drug design process.
Question:Quantum tech limitations?
Answer: Current quantum systems can only model simple systems like water molecules. Modelling complex molecules requires enormous amounts of qubits, a technological milestone yet to be reached. Instead, we make the most of today's quantum capabilities by solving optimization challenges, leveraging their computational power to process data and identify the most promising molecules.
Question: Innovation Challenges?
Answer: Finding skilled quantum developers is difficult, given the limited quantum expertisePool. Developers usually have a physics background, focusing on hardware, but overcoming problems and translating them into quantum-compatible solutions is an uncommon yet essential skill. Entrepreneurs, too, face the challenge of navigating a new field like quantum computing, where success takes time, patience, and sustained investment.
Question: What awaits in the Future?
Answer: The future of quantum computing in drug discovery will be significant, especially if combined with AI. Developing hybrid quantum-classical models will drive innovations beyond today's limitations, reducing computational time, and increasing screening accuracy. The progress in different quantum modalities-trapped ions, neutral atoms, and superconducting qubits-holds the potential to overcome hardware challenges and scale up to model complex molecules. These advancements could help Polaris upgrade its platform, further accelerating drug discovery and design.
Insights: Quantum computing's impact on drug discovery lies in overcoming the limitations of classical methods and AI. It can better simulate molecular interactions and speed up drug discovery pipelines. The future holds hybrid quantum-classical models, which aim to drive innovations beyond current capabilities. These models can enhance workflows and increase screening accuracy, leading to faster and more accurate drug development. Challenges such as scalability, error correction, and robustness must be addressed to fully harness the potential of quantum computing in drug discovery.
- Polaris' QuADD platform, a quantum-powered drug design tool, helps clients rapidly identify drug candidates, zeroing in on lead molecules with superior properties.
- Quantum power enables QuADD to scan chemical spaces billions of times larger than traditional methods, upping the odds of discovering the optimal molecule and speeding up the drug design process.
- Current quantum systems can only model simple systems; modeling complex molecules requires enormous amounts of qubits, a technological milestone yet to be reached.
- The future of quantum computing in drug discovery will be significant, especially if combined with AI, forming hybrid quantum-classical models that could drive innovations beyond today's limitations and accelerate drug discovery and design.
