Borrowing from Pharma: Adapting the Concept of a Target Product Profile (TPP) for Healthcare AI

The pharmaceutical industry has long relied on Target Product Profiles (TPPs) as a guiding framework to streamline drug development. A TPP outlines the desired characteristics of a drug, including its indications, efficacy, safety profile, and differentiation from competitors. By starting with the end in mind, TPPs serve as a north star, aligning stakeholders across R&D, regulatory, and commercial domains.

Could this concept find a new home in healthcare AI?

Healthcare AI solutions often face challenges similar to those in pharmaceuticals: fragmented workflows, high regulatory hurdles, and a pressing need to deliver clear value. Borrowing the TPP framework could provide much-needed structure to the lifecycle of AI product development. Imagine creating an AI "Target Product Profile" that defines:

• Intended Use Case: What clinical problem are we solving? Is it diagnostic support, workflow optimization, or patient engagement?
• Performance Metrics: What accuracy, sensitivity, or specificity thresholds are required to ensure clinical utility?
• Regulatory Pathway: What compliance standards must be met (e.g., FDA, CE marking)?
• Integration Needs: How will the AI integrate into existing systems like EHRs or PACS?
• Economic Value: What ROI does it deliver for providers, payers, or patients?

This structured approach could help teams avoid common pitfalls like developing “cool” algorithms that lack practical applicability or failing to account for the realities of clinical deployment.

Moreover, an AI TPP could foster better collaboration between developers, healthcare providers, and regulators by establishing shared goals from the outset. It could also enable clearer benchmarks for success, accelerating the path from prototype to clinical impact.

The challenge lies in striking a balance between the flexibility AI requires for iterative development and the rigid structure a TPP enforces. But given the increasing complexity of healthcare AI products, it’s a balance worth exploring.

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