What factors contributed to the unexpected 30% increase in computational costs for insitro's high-throughput screening platform during Q2?

Introduction

The unexpected 30% increase in computational costs for insitro's high-throughput screening platform during Q2 presents a complex challenge that requires thorough analysis. To address this issue, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both immediate and long-term implications for the platform's performance and cost-effectiveness.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal component. Has this increase coincided with any specific research cycles or project deadlines?

Why it matters: Seasonal patterns could explain temporary spikes in usage. Expected answer: Possible correlation with research deadlines. Impact on approach: If seasonal, we'd focus on capacity planning rather than systemic issues.

• Considering the scale of increase, I'm wondering about recent platform updates. Have there been any significant changes to the screening algorithms or data processing pipelines in the last quarter?

Why it matters: Recent changes could introduce unexpected computational demands. Expected answer: Possible implementation of new machine learning models or data analysis techniques. Impact on approach: If confirmed, we'd scrutinize the new implementations for optimization opportunities.

• Given the nature of high-throughput screening, I'm curious about data volume changes. Has there been a substantial increase in the number or complexity of compounds being screened?

Why it matters: Changes in input data could directly impact computational requirements. Expected answer: Possible increase in dataset size or complexity. Impact on approach: If confirmed, we'd focus on data management and processing optimizations.

• Thinking about infrastructure, I'm considering potential changes in our cloud or on-premises setup. Have we switched providers or altered our computational resources recently?

Why it matters: Infrastructure changes could affect cost structures and efficiency. Expected answer: Possible migration to new cloud services or hardware upgrades. Impact on approach: If confirmed, we'd analyze the new infrastructure setup for cost-efficiency.