Summary Report of PQRI Workshop on Nanomaterial in Drug Products: Current Experience and Management of Potential Risks
Bibliographic record
Abstract
At the Product Quality Research Institute (PQRI) Workshop held last January 14-15, 2014, participants from academia, industry, and governmental agencies involved in the development and regulation of nanomedicines discussed the current state of characterization, formulation development, manufacturing, and nonclinical safety evaluation of nanomaterial-containing drug products for human use. The workshop discussions identified areas where additional understanding of material attributes, absorption, biodistribution, cellular and tissue uptake, and disposition of nanosized particles would continue to inform their safe use in drug products. Analytical techniques and methods used for in vitro characterization and stability testing of formulations containing nanomaterials were discussed, along with their advantages and limitations. Areas where additional regulatory guidance and material characterization standards would help in the development and approval of nanomedicines were explored. Representatives from the US Food and Drug Administration (USFDA), Health Canada, and European Medicines Agency (EMA) presented information about the diversity of nanomaterials in approved and newly developed drug products. USFDA, Health Canada, and EMA regulators discussed the applicability of current regulatory policies in presentations and open discussion. Information contained in several of the recent EMA reflection papers was discussed in detail, along with their scope and intent to enhance scientific understanding about disposition, efficacy, and safety of nanomaterials introduced in vivo and regulatory requirements for testing and market authorization. Opportunities for interaction with regulatory agencies during the lifecycle of nanomedicines were also addressed at the meeting. This is a summary of the workshop presentations and discussions, including considerations for future regulatory guidance on drug products containing nanomaterials.
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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 | 0.011 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.011 |
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".