CRISPR/Cas9 Editing: Sparking Discussion on Safety in Light of the Need for New Therapeutics
Bibliographic record
Abstract
Recent advances in genome sequencing have greatly improved our ability to understand and identify the causes of genetic diseases. However, there remains an urgent need for innovative, safe, and effective treatments for these diseases. CRISPR-based genome editing systems have become important and powerful tools in the laboratory, and efforts are underway to translate these into patient therapies. Therapeutic base editing is one form of genome engineering that has gained much interest because of its simplicity, specificity, and effectiveness. Base editors are a fusion of a partially deactivated Cas9 enzyme with nickase function, together with a base-modifying enzyme. They are capable of precisely targeting and repairing a pathogenic mutation to restore the normal function of a gene, ideally without disturbing the rest of the genome. In the past year, research has identified new safety concerns of base editors and sparked new innovations to improve their safety. In this review, we provide an overview of the recent advances in the safety and effectiveness of therapeutic base editors and prime editing.
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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 | 0.000 | 0.000 |
| 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".