Drug Cartridge Encoding for Tolerance-Compensated Injection Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing drug delivery systems lack accurate control over injection processes due to manufacturing tolerances and variations in injector components, affecting the delivery characteristics such as velocity and force profiles.
Innovation Solution
Measuring and encoding relevant features of drug delivery components, like drug cartridges, using tags (e.g., RFID, barcode) to adjust the injection process based on measured values, ensuring accurate delivery by compensating for manufacturing variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manufacturing tolerances are tightened to improve component consistency, then manufacturing precision improves, but manufacturing cost and complexity increase
Solution Approach 1:
The system performs preliminary measurement of component features (orifice diameter, cartridge dimensions) during manufacturing and encodes this data on tags before the components are used. This preliminary action captures the actual variations, allowing the delivery system to compensate for them later without requiring tighter manufacturing tolerances.
Solution Approach 2:
The system implements a feedback loop where measured component features are encoded on tags, retrieved during drug delivery, and used to adjust delivery parameters. This feedback mechanism allows the system to adapt to manufacturing variations dynamically, resolving the contradiction by making precision achievable through measurement and adjustment rather than strict manufacturing control.
2Ease of manufacture
If component manufacturing tolerances are relaxed to reduce cost, then ease of manufacture improves, but injection accuracy deteriorates
Solution Approach 1:
The system measures and encodes component features during manufacturing when the components are readily accessible. This preliminary measurement captures the actual dimensions and characteristics, allowing later compensation without requiring expensive tight tolerances during manufacturing.
Solution Approach 2:
The system changes the approach from controlling physical dimensions through manufacturing precision to controlling delivery parameters based on measured values. By adjusting delivery parameters (force, velocity, timing) based on encoded component data, the system achieves accurate injection despite manufacturing variations.
3Manufacturing precision
If component features are measured and encoded for each instance, then injection accuracy improves, but device complexity and measurement requirements increase
Solution Approach 1:
The system extracts only the critical features that affect injection accuracy (orifice diameter, cartridge dimensions, air bubble size) and encodes this minimal necessary data on tags. This selective extraction approach avoids the need to measure and store all possible component parameters, reducing system complexity while maintaining injection accuracy.
Solution Approach 2:
The system creates a digital copy of the critical physical features by encoding measured values on tags attached to components. This copy allows the delivery system to reference and compensate for manufacturing variations without needing the physical components to be perfectly precise, simplifying the overall system by separating measurement from delivery.
4Manufacturing precision
If dynamic adjustment of delivery parameters is implemented, then injection accuracy improves, but control system complexity increases
Solution Approach 1:
The system performs preliminary measurement and encoding of component features, so that when delivery occurs, the adjustment parameters are already determined. This preliminary action shifts complexity from the real-time control moment to the preparation phase, simplifying the actual delivery control while maintaining accuracy through pre-calculated adjustments.
Data Source
AI summary
An approach to providing predictable and uniform drug delivery across many instances of an automated drug delivery procedure involves measuring features of the drug delivery system prior to delivery. An automated drug delivery procedure is configured to compensate for or otherwise accommodate the impact of these features based on the measured features. In some examples, the measured features are encoded by value or by reference to an external database onto the drug containing component, for example, by affixing a tag (e.g., RFID, barcode, etc.) to the component. At the time of drug delivery, the features are accessed, for example using the affixed tag, and the drug delivery procedure is controlled according to the features.