From microchips to microneedles: semiconductor shear testers as a universal solution for transverse load analysis of microneedle mechanical performance
Bibliographic record
Abstract
Abstract Microneedles are a promising technology for pain-free and efficient pharmaceutical delivery. However, their clinical translation is currently limited by the absence of standardized testing methods for critical quality attributes (CQAs), such as mechanical robustness, which are essential for demonstrating safety and efficacy during regulatory review. A key aspect of mechanical robustness is transverse load capacity, which is currently assessed using diverse, non-standardized methods, which have limited capability to measure transverse failure forces at different heights along a microneedle. This is critical for understanding mechanics of potential failure modes during insertion after skin penetration. In this work we utilize a wire bond shear tester, a piece of test equipment widely used in the semiconductor industry, to measure the transverse load capacities of various microneedle designs. This approach is compatible with diverse microneedle types, geometries, and materials, and offers high-throughput and automated testing capabilities with high precision. We measure transverse failure loads with micron-scale control over the test height and have established comprehensive profiles of mechanical robustness along the length of different microneedle designs, which is a capability not previously demonstrated in literature for polymeric and metal microneedles. Transverse failure forces were 10 ± 0.3 gf–128 ± 12 gf for wire bonded gold and silver microneedles, 11 ± 0.7 gf–480 ± 69 gf for conical and pyramidal polymeric microneedles, and 206 ± 80 gf–381 ± 1 gf for 3D printed conical stainless steel microneedles. Additionally, we present standardized definitions for microneedle structural failure modes resulting from transverse loads, which can facilitate root cause failure analysis and defect detection during design and manufacturing, and aid in risk assessment of microneedle products. This work establishes a standardized approach to evaluating a significant CQA of microneedle products, which is a critical step towards expediting their clinical adoption.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".