Medicament Delivery Device Batch Recall Evaluation System
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Solution Overview
Problem
Medicament delivery devices face challenges in ensuring reliability and patient safety due to exposure to high temperatures, humidity, and physical stress, which can affect their functioning, and there is a need for a system to evaluate batches for potential recall to ensure user safety, especially for critical devices like auto-injectors.
Innovation Solution
A system comprising medicament delivery devices with integrated sensors, processors, and transceivers that generate and transmit data for analysis using machine learning to determine if a batch should be recalled, improving condition monitoring and reliability by comparing actual device performance with reference data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If medicament delivery devices are exposed to high temperatures, humidity, and physical stress during transportation and storage, then the devices may suffer from reliability degradation and malfunction, but implementing comprehensive monitoring and evaluation systems increases device complexity and cost
Solution Approach 1:
The system performs preliminary monitoring and data collection during transportation and storage before the devices reach the patient. Sensors continuously track temperature, humidity, shock, and other parameters throughout the supply chain, enabling early detection of conditions that may compromise device reliability without requiring complex post-delivery evaluation systems
Solution Approach 2:
The patent introduces an intermediary evaluation system that acts as a mediator between the physical devices and the final user. This system includes remote computers that receive sensor data from multiple devices, perform batch evaluation using machine learning algorithms, and generate recall recommendations, thereby simplifying the complexity by externalizing the evaluation burden from individual devices to a centralized system
2Reliability
If comprehensive sensor monitoring is implemented in each device to track condition during use and transportation, then patient safety and reliability are improved, but the device complexity and manufacturing cost increase
Solution Approach 1:
The sensor system is designed to serve multiple functions: monitoring temperature, humidity, shock, and device operational parameters simultaneously. The same sensor infrastructure supports both transportation condition monitoring and clinical use evaluation, eliminating the need for separate monitoring systems and reducing overall device complexity
Solution Approach 2:
Each medicament delivery device autonomously performs self-monitoring of its own condition and operational parameters through integrated sensors. The devices automatically generate and transmit their own data without requiring external monitoring equipment, enabling them to serve themselves in terms of condition tracking and safety verification
3Reliability
If batch evaluation and recall determination systems are implemented to ensure safety, then user safety is improved, but the time and resources required for evaluation increase
Solution Approach 1:
The monitoring and data collection process operates continuously from the moment devices are packaged through transportation, storage, and clinical use. This continuous data flow enables real-time batch evaluation without interruption, eliminating the need for separate evaluation phases and reducing total evaluation time while maintaining comprehensive safety assessment
Solution Approach 2:
The patent replaces manual batch evaluation processes with automated machine learning algorithms that run on remote computers. These algorithms automatically analyze sensor data from entire batches, generate recall recommendations, and support decision-making without requiring extensive human review time, thereby significantly reducing evaluation time while maintaining or improving accuracy
Data Source
AI summary
A system for evaluating if a batch of medicament delivery devices should be recalled, wherein the medicament delivery devices are each configured to establish a connection to a remote computer over a communication network when the medicament delivery device is activated; wherein each medicament delivery device is configured to transfer batch data, sensor data and time data to the remote computer; wherein the remote computer is configured to create a batch data set containing the batch data, the sensor data and the time data for the batch; and wherein the remote computer is configured to evaluate the batch data set and the regular reference data stored in the remote memory based on machine learning and to determine, based on the evaluation, if a batch of medicament delivery devices should be recalled.