Considerations from the pharmaceutical industry (IQ MPS affiliate) workshop on animal microphysiological systems and 3Rs in drug development
Bibliographic record
Abstract
Most complex in vitro models (CIVM) and microphysiological systems (MPS) are composed of human cells, with the goal of evaluating diseases, efficacy, safety, and pharmacokinetic questions specifically for humans. The hope with CIVM/MPS is that they will eventually improve our predictivity for clinical responses and reduce or replace animal use in research, supporting the 3Rs concept of only using animals in research when necessary. Given the potential of animal-based models to advance this field by comparing existing in vivo animal data with new animal-based MPS responses, there are currently few CIVM and MPS utilizing animal tissues. Animal-based MPS may also have specific utility for cross-species comparisons or species-specific mechanistic questions on zoonotic diseases, and therapies for animals. Animal-based MPS may help expand in vitro-to in vivo correlations, advance the field and establish confidence in the predictive nature of such platforms. The IQ MPS-FDA workshop provided an interactive venue for pharmaceutical companies and regulatory agencies such as the U.S. Food and Drug Administration (FDA), NC3Rs (UK), Health Canada, NIH/NCATS, NIHS and PMDA (Japan), Danish Medicines Agency, European Commission, NIEHS/ICEATM, HHS, NIST, EURL ECVAM, and the IQ MPS Affiliate, a collaboration of pharmaceutical companies to jointly discuss considerations of animal-based MPS and applications where animal-based MPS are of potential value. Plain language summaryMicrophysiological systems are complex in vitro models that recapitulate human or animal physiology by mimicking their key biological processes and disease states. These models need extensive validation to be utilized routinely as drug discovery tools. The IQ MPS Affiliate comprised of 26 pharmaceutical companies held a joint workshop with the FDA, other regulators and the NC3Rs to address current challenges in the MPS field and discuss context of use for animal-cell based MPS in drug discovery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.031 | 0.010 |
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 source (direct Gemma or distilled Codex), 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".