XRCT-Based Release Profile Prediction for Controlled Release Implants
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Solution Overview
Problem
Existing methods for determining the release profile of controlled release devices are time-consuming and require lengthy testing periods, making it difficult to predict and optimize the manufacturing process for achieving a desired therapeutic dose and lifespan.
Innovation Solution
A method using XRCT imagery to estimate the release profile by determining pore volume and connectivity data, which are used to construct and calibrate models predicting the release profile, allowing for adjustments to the manufacturing process without extensive experimental testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If experimental determination of release profile is performed by measuring active compound release over expected lifespan, then accurate release profile data is obtained, but testing time is excessive and manufacturing iteration is slow
Solution Approach 1:
The patent applies preliminary action by performing XRCT imaging and pore structure analysis on the manufactured device before conducting release tests. This allows the pore volume and connectivity data to be obtained in advance, enabling the predictive model to estimate the release profile without waiting for complete experimental testing, thus reducing the overall testing period while maintaining accuracy
Solution Approach 2:
The patent uses XRCT imaging to create a virtual 3D copy of the device's internal pore structure. This digital replica allows for non-destructive analysis of pore volume and connectivity, enabling predictive modeling of the release profile without requiring physical destruction or lengthy experimental testing of the actual device, thereby reducing testing time while preserving measurement accuracy
2Manufacturing precision
If manufacturing process parameters are adjusted to optimize release profile, then therapeutic dose and lifespan are improved, but extensive experimental testing is required for each adjustment
Solution Approach 1:
The patent enables preliminary assessment of manufacturing outcomes by performing XRCT imaging and predictive modeling on prototype devices. This allows manufacturers to evaluate the impact of process parameter adjustments on pore structure and estimated release profile before committing to full-scale production or extensive testing, thereby accelerating the iteration process while maintaining precision control
Solution Approach 2:
The patent replaces the traditional mechanical/experimental testing system with a computational predictive model based on XRCT-derived pore structure data. This substitution allows for rapid virtual testing of different manufacturing parameters and their impact on release profile, eliminating the need for repeated physical prototyping and extensive experimental testing, thus improving manufacturing iteration speed while maintaining precision
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate prediction of release profiles using existing XRCT equipment, reducing iteration time and improving the design of controlled release devices, such as long-acting parenteral implants, by simulating the release of active pharmaceutical ingredients based on microstructural features.
Implementation Method 1
An XRCT image of the device is received
Implementation Method 2
a long-acting parenteral (LAP) medical implant for releasing an active pharmaceutical ingredient (API) over time
Data Source
AI summary
Embodiments disclosed herein relate to a model for predicting the release profile of a controlled release device. The implant modeling system and models disclosed herein allow the accurate prediction of a release profile for a controlled release device based on features extracted from micro-resolution imagery. The models combine microstructural features that can be extracted at the XRCT resolution, including pore volume and connectivity, using erosion-dilation image analysis. This strategy allows prediction of release curves of the controlled release device using XRCT despite its resolution limitations.