Config
Samples
Planning
Operations
Assignments
Report
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Config
Samples
Planning
Operations
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Report
Pharmaceutical Manufacturing companies often face challenges in efficiently scheduling for their Quality Control operations with respect to Routine Testing activities, Machines, People and Non-Routine activities for Improving overall QC Efficiency, Effectiveness, minimizing waiting times, manual interventions and optimizing resource utilization.
The Pharma QC Scheduling Simplified (QSS) is a cloud-based application designed to optimize laboratory operations by intelligently planning, scheduling, and monitoring QC testing activities (samples for Produced goods, input materials, scheduled samples, validation and qualification samples) across chemical, instrumental, chromatographic, and microbiological laboratories. The solution enables proactive capacity planning, dynamic scheduling, and real-time visibility into QC workloads, resources, and turnaround times, ensuring alignment with manufacturing and release commitments.
The solution integrates seamlessly with existing enterprise systems such as LIMS, ERP (e.g., SAP), and Manufacturing Scheduling systems to act as a single source of truth for QC operations. It supports end-to-end QC processes from sample receipt to test execution, review, and release, thereby improving QC throughput, adherence to manufacturing schedules, and overall operational efficiency
This application ensures that Analyst and Instrument workloads are distributed efficiently, reducing bottlenecks and improving overall productivity. By considering factors such as Sample priority, Analyst availability, Instrument availability, Available times, Instrument run times, and resource constraints, the QC Scheduler provides Quality control function with a smart and dynamic scheduling solution.
Enhance overall QC throughput by maximizing operational efficiency and analytical effectiveness.
QC schedule adherence to manufacturing and stability plans
accuracy in QC capacity forecasting and workload visibility
through optimized resource utilization
based on real-time constraints
and data-driven decision making