Formulation and PEGylation optimization of the therapeutic PEGylated phenylalanine ammonia lyase for the treatment of phenylketonuria
Bibliographic record
Abstract
Phenylketonuria (PKU) is a genetic metabolic disease in which the decrease or loss of phenylalanine hydroxylase (PAH) activity results in elevated, neurotoxic levels of phenylalanine (Phe). Due to many obstacles, PAH enzyme replacement therapy is not currently an option. Treatment of PKU with an alternative enzyme, phenylalanine ammonia lyase (PAL), was first proposed in the 1970s. However, issues regarding immunogenicity, enzyme production and mode of delivery needed to be overcome. Through the evaluation of PAL enzymes from multiple species, three potential PAL enzymes from yeast and cyanobacteria were chosen for evaluation of their therapeutic potential. The addition of polyethylene glycol (PEG, MW = 20,000), at a particular ratio to modify the protein surface, attenuated immunogenicity in an animal model of PKU. All three PEGylated PAL candidates showed efficacy in a mouse model of PKU (BTBR Pahenu2) upon subcutaneous injection. However, only PEGylated Anabaena variabilis (Av) PAL-treated mice demonstrated sustained low Phe levels with weekly injection and was the only PAL evaluated that maintained full enzymatic activity upon PEGylation. A PEGylated recombinant double mutant version of AvPAL (Cys503Ser/Cys565Ser), rAvPAL-PEG, was selected for drug development based on its positive pharmacodynamic profile and favorable expression titers. PEGylation was shown to be critical for rAvPAL-PEG efficacy as under PEGylated rAvPAL had a lower pharmacodynamic effect. rAvPAL and rAvPAL-PEG had poor stability at 4°C. L-Phe and trans-cinnamate were identified as activity stabilizing excipients. rAvPAL-PEG is currently in Phase 3 clinical trials to assess efficacy in PKU patients.
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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) | 0.000 | 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".