As biologists with bioinformatics experience venturing into blockchain development for the first time, we faced several significant hurdles while building PolyKye Onchain:

Technical Learning Curve: Coming from biological sciences backgrounds, we had to rapidly learn Solidity programming and blockchain architecture fundamentals. The transition from working with genomic data pipelines to smart contract development required understanding entirely new programming paradigms and security considerations.

Bridging Domain Knowledge Gaps: While we understood the biological aspects of drug discovery and ligand identification, translating this knowledge into blockchain-compatible workflows presented unique challenges. Creating data structures that could effectively represent complex molecular information on-chain while keeping computation-heavy processes off-chain required careful design decisions.

Integration Complexity: Connecting our AI-powered ligand discovery system with blockchain infrastructure proved technically challenging. Ensuring that IPFS storage for synthesis pathways worked seamlessly with on-chain data references presented the challenges that ultimately prevented us from reaching our vision in time.

Balancing Transparency with Computation: One of our biggest challenges was determining which processes should happen on-chain versus off-chain. The computational intensity of AI-powered ligand discovery made it impossible to perform entirely on-chain, requiring a hybrid architecture that maintained transparency while acknowledging blockchain's computational limitations.

Despite these challenges, our bioinformatics background provided valuable perspective on data integrity and scientific workflow management that ultimately strengthened our blockchain implementation. This project represents not just a technological achievement but also a bridge between two specialized fields that rarely intersect.