An engineered dual function peptide to repair fractured bones
Bibliographic record
Abstract
Targeted drug delivery, often referred to as “smart” drug delivery, is a process whereby a therapeutic drug is delivered to specific parts of the body in a manner that increases its concentration at the desired sites relative to others. This approach is poised to revolutionize medicine as exemplified by the recent FDA approval of Cytalux (FDA approves pioneering drug for ovarian cancer surgery - Purdue University News) which is a folate-receptor targeted intraoperative near infrared (NIR) imaging agent that was developed in our laboratories. Fracture-associated morbidities and mortality affect a significant portion of world population. United states, Canada and Europe alone spent $48 billion in treating osteoporosis related fractures although this number doesn't count the economic burden due to loss in productivity. It is estimated that by 2050 ca 21 million hip fractures would occur globally which will be leading cause of premature death and disability. Despite the need for improvement in the treatment for fracture repair, methods for treating fractures have changed little in recent decades. Systemic delivery of fracture-homing bone anabolics holds great promise as a therapeutic strategy in this regard. Here we report the design of a fracture-targeted peptide comprised of a payload that binds and activates the parathyroid hormone receptor (PTHR1) and is linked to a targeting ligand comprised of 20 D-glutamic acids (D-Glu20) that directs accumulation of the payload specifically at fracture sites. This targeted delivery results in reduction of fracture healing times to <1/2 while creating repaired bones that are >2-fold stronger than saline-treated controls in mice. Moreover, this hydroxyapatite-targeted peptide can be administered without detectable toxicity to healthy tissues or modification of healthy bones in dogs. Additionally, since similar results are obtained upon treatment of osteoporotic and diabetic fractures in mice, and pain resolution is simultaneously accelerated by this approach, we conclude that this fracture-targeted anabolic peptide displays significant potential to revolutionize the treatment of bone fractures.
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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 | 0.001 | 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) | 0.001 | 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".