Spectroscopic Heterogeneity Monitoring via Temporal Segmentation
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Solution Overview
Problem
Current spectrometric methods for monitoring pharmaceutical mixing processes either provide limited information about the distribution of mixture components or are expensive to implement, as they often rely on single measurements or near-infrared chemical imaging.
Innovation Solution
A spectroscopic method and apparatus that acquire sampled measurements from multiple micro-locations within a macro-sample, using optical channels and detectors, to derive statistical measures of chemical heterogeneity, allowing for detailed characterization of pharmaceutical mixtures during blending processes without the need for expensive imaging instruments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If near-infrared chemical imaging is used to acquire detailed distribution information, then information about mixture component distribution is improved, but implementation cost increases
Solution Approach 1:
The patent segments the continuous mixing process into discrete sampling points taken at different times. Instead of continuous imaging, multiple single-point spectra are acquired sequentially as the blend passes by, creating a temporal sequence that represents spatial distribution information.
Solution Approach 2:
The patent creates a statistical representation (copy) of the full distribution information through multiple single-point measurements. By taking many individual spectra at different locations and times, the system reconstructs distribution characteristics without requiring a full imaging system.
2Device complexity
If single point spectra are used to monitor mixing, then implementation simplicity is improved, but information about component distribution is worsened
Solution Approach 1:
The patent adds a temporal dimension to single-point measurements. By acquiring spectra at multiple time points as the blend progresses through the mixing vessel, the system captures spatial distribution information that would otherwise require multiple spatial dimensions in an imaging system.
Solution Approach 2:
The system uses statistical analysis of the sequential single-point measurements to provide feedback about mixing homogeneity. Distribution parameters calculated from the spectral data give real-time information about component uniformity, enabling process control decisions.
3Measurement precision
If multiple micro-location measurements are taken across macro-samples, then measurement precision of chemical heterogeneity is improved, but measurement time increases
Solution Approach 1:
The patent uses periodic sampling during the mixing process, taking measurements at regular time intervals as the blend passes the detection point. This periodic acquisition strategy captures sufficient statistical information about heterogeneity without requiring continuous measurement.
Solution Approach 2:
The system takes more measurements than the minimum single point by acquiring multiple spectra at different micro-locations, but fewer than a full imaging system would require. This partial action approach provides adequate statistical precision for process control while maintaining speed.
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
This approach allows for detailed information about the uniformity of pharmaceutical mixtures, potentially increasing the safety and efficacy of drugs at a lower cost, using relatively simple and inexpensive measurement apparatus, and is more tolerant to optical misalignments and vibrations.
Implementation Method 1
The step of acquiring can operate on light brought from micro-samples through a plurality of optical channels. The step of acquiring can operate on light brought from the micro-locations to a set of detectors.
Data Source
AI summary
In one general aspect, a spectroscopic method for monitoring heterogeneity of a sample is disclosed. In this method, sampled spectroscopic measurements are acquired over a range of different micro locations in a macro-sample of the sample. This step is repeated for micro-locations in further macro-samples of the sample, and a statistical measure of chemical heterogeneity is derived from the acquisitions. In another general aspect, differently sized samples are acquired, and a statistical measure of chemical heterogeneity is derived from these acquisitions.