Translating theoretical compute capabilities into inspection-ready operational frameworks for global clinical development.
Published in PM World Journal • 2026
AI Accountability Is Already Project Management Work
3 min read·4:12 listen
AI GovernanceRisk MitigationProject Management
An analytical study of the rapid transition from isolated algorithmic automation to complex machine learning dependencies within regulated trial workflows. This paper establishes the pragmatic frameworks required by clinical project directors to formally manage tracking, algorithmic drift, and human-in-the-loop operational validation parameters.
Tackling the most pressing regulatory hurdle for global trial execution across European site networks. This paper clarifies strict legal liabilities, cross-institutional data governance requirements, and explicit audit-trail criteria to provide sponsors and CROs with a clear compliance disarmer before deploying predictive models.
The Drug Got a Supercomputer. The Trial Got a Spreadsheet.
3 min read·4:43 listen
AI GovernanceClinical OperationsNVIDIADrug Development
The pharmaceutical industry is investing billions in supercomputing for drug discovery, yet clinical trial execution still relies on retrospective spreadsheets and manual workflows. This article examines the economic and operational cost of that gap—where a single Phase III amendment can cost $535,000 in direct costs and months of delay—and makes the case for deploying NVIDIA AI Foundry and NIM microservices as real-time operational intelligence across the execution layer.
The Real AI Readiness Question Is Not 'What Tool?' Rather It's 'What Decision Are We Improving?'
3 min read·4:11 listen
AI GovernanceEnterprise AIDecision Science
Most AI readiness conversations start with the wrong question. Tool selection is downstream of decision architecture — until an organization can name the specific decision it wants to improve, the operating conditions around that decision, and the accountability for the outcome, no platform choice will move the needle. This article reframes readiness as a decision-improvement discipline rather than a technology procurement exercise.
AI Won't Fix a Broken Protocol. But It Will Expose One Faster.
3 min read·3:52 listen
Clinical OperationsAI GovernanceProtocol Design
Layering AI onto a poorly designed clinical protocol doesn't rescue the study — it accelerates the visibility of every ambiguity, contradiction, and unenforceable endpoint baked into the design. This piece walks through how modern AI tooling surfaces protocol weakness earlier in the lifecycle, and why that exposure is a feature, not a failure, for sponsors willing to act on it.