Pegvisomant
| Evidence Level: L5 | Predicted Indications: 10 |
Table of Contents
Pegvisomant: From Unspecified Original Indication to Borderline Ovarian Serous Tumour
One-Sentence Summary
Pegvisomant’s original approved indication is not recorded in this evidence pack, and the drug does not currently hold a UK marketing authorisation. Based on its known pharmacology as a growth hormone (GH) receptor antagonist, the TxGNN model predicts a possible signal for Borderline Ovarian Serous Tumour, but this is currently supported only by a model prediction score, with no clinical trials and no published literature identified.
Quick Overview
| Item | Content |
|---|---|
| Original Indication | Not available — no UK licence or approved-indication text in this evidence pack |
| Predicted New Indication | Borderline Ovarian Serous Tumour |
| TxGNN Prediction Score | 98.63% |
| Evidence Level | L5 (model prediction only, no supporting studies) |
| UK Market Status | Not marketed |
| Number of Marketing Authorisations | 0 |
| Recommended Decision | Hold |
Why is This Prediction Reasonable?
Formal mechanism-of-action data was not available for structured extraction in this evidence pack. However, the model’s own rationale text indicates that pegvisomant acts as a GH receptor antagonist, which reduces circulating IGF-1. The GH/IGF-1 axis has a theoretical link to proliferation in some ovarian tumour cell types, which is the basis offered for this prediction — but the evidence pack explicitly characterises this link as speculative, with no in vitro, preclinical, or clinical data to support it.
Notably, 7 of the top 10 predicted indications for this drug are ovarian tumour subtypes (borderline serous tumour, rete ovarii cystadenoma, papillary cystadenoma, malignant Brenner tumour, mucinous cystadenofibroma, benign neoplasm, mucinous cystadenoma, surface papilloma) clustered within a very narrow score range (98.5–98.6%). The evidence pack itself flags this as a probable knowledge-graph clustering artefact — i.e. the model may be scoring the “ovarian tumour” node category as a whole rather than validating each specific pharmacological relationship. The remaining two predictions in this set (pyelonephritis, an infectious disease, and aleukaemic mast cell leukaemia, which is driven by KIT mutations) have no plausible mechanistic connection to GH receptor antagonism at all, further suggesting these are false-positive or noise predictions rather than genuine repurposing signals.
Given the absence of any independent supporting evidence and the model’s own caveats about clustering effects, this prediction should be treated as hypothesis-generating only, not as a validated pharmacological signal.
Clinical Trial Evidence
Currently no related clinical trials registered.
Literature Evidence
Currently no related literature available.
Safety Considerations
Please refer to the SmPC and BNF for safety information. Report suspected adverse reactions via the Yellow Card Scheme.
Note: Detailed warnings, contraindications, and interaction data for this drug were not obtainable in this evidence pack (flagged as a Blocking-severity data gap), so no clinical safety assessment can be made at this time.
Conclusion and Next Steps
Decision: Hold
Rationale: This prediction rests solely on a TxGNN model score (L5), with no clinical trials, no literature, and no marketing authorisation or safety data available. The evidence pack itself identifies the surrounding ovarian tumour predictions as a likely category-clustering artefact rather than independently validated signals, and two of the ten top predictions have no plausible mechanistic basis at all — together these substantially weaken confidence in any individual candidate, including the top-ranked indication.
To proceed, the following is needed:
- UK product label / SmPC data (warnings, contraindications) — currently a Blocking-severity gap
- Confirmed mechanism-of-action documentation and the drug’s original approved indication(s)
- Preclinical or in vitro evidence directly linking GH/IGF-1 axis inhibition to ovarian tumour biology, ideally specific to the borderline serous subtype rather than the ovarian tumour category as a whole
- An investigation into why multiple unrelated ovarian tumour subtypes score similarly, to rule out a knowledge-graph node-clustering artefact before any further evaluation
- Clarification of UK marketing status, since this drug currently has zero UK marketing authorisations on record
Disclaimer
This content is for research purposes only and does not constitute medical advice. Clinical validation is required before any clinical application.