Related Experiment Video
Updated: Jun 19, 2025

Automated Robotic Liquid Handling Assembly of Modular DNA Devices
Published on: December 1, 2017
Modeling package size-conscious automated dispensing cabinet replenishment to improve efficiency
John Killian L Rodgers1, Randy Braun2, Erinn Rowe2
1UNC Health, Chapel Hill, NC, USA.
Purpose:
Optimization of automated dispensing cabinets (ADCs) has traditionally focused on modifying the inventory within these devices and ignored the replenishment process itself. Rounding replenishment quantities to the nearest package size, termed package size-conscious replenishment (PSCR), was investigated as a way to optimize labor needs for ADC replenishment.
Methods:
A simulation of PSCR for a subset of medications stocked in ADCs at the University of North Carolina Medical Center was conducted. The simulation utilized real-world vend data and rounding factors to model the impact of PSCR on key ADC metrics. The final simulation utilized 2 months of ADC transactions across 410 medications in 149 ADCs. Four replenishment methodologies were simulated: standard replenishment and 3 PSCR strategies, including rounding down, rounding any direction, and rounding up.
Results:
All 3 PSCR methodologies had significantly lower stockout frequencies than standard replenishment at 0.722% (P = 0.026) for rounding down, 0.698% (P = 0.024) for rounding any direction, and 0.680% (P = 0.024) for rounding up vs 0.773% for standard replenishment. PSCR methods were associated with significant time savings for both technician and pharmacist activities (P < 0.001 for all 3 strategies), with a savings of up to 0.27 technician and 0.52 pharmacist full-time equivalents estimated for the rounding-up methodology. Maximum carrying cost was higher for all 3 PSCR methodologies.
Conclusion:
PSCR was modeled to significantly decrease both pharmacist and technician time needed to replenish ADCs while also decreasing stockout frequency. Modest increases in maximum carrying cost were also shown. The simulation created for this evaluation could also be utilized to model other components of the ADC replenishment process.
More Related Videos
11:58Optimizing the Use of a Liquid Handling Robot to Conduct a High Throughput Forward Chemical Genetics Screen of Arabidopsis thaliana
Published on: April 30, 2018
16:23Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Published on: February 26, 2014
Related Concept Videos
Clearance Models: Compartment Models
Compartment Models: Two-Compartment Model
Model Approaches for Pharmacokinetic Data: Compartment Models
Two primary types of compartment models are recognized: mammillary and catenary. The more...
Compartment Models: Single-Compartment Model
Clearance Models: Noncompartmental Models
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
Multicompartment Models: Overview
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...