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Drivers, value proposition and contribution(s):
Drivers (based on organisational needs) | Value proposition (what difference will it make) | Contribution (what you/your company are prepared to do to support the initiative) |
|---|
- Have well curated, more diverse (different animal models, different Abs, etc.) and evolving data on reference molecules.
- Have all clinical PK data in one place and move away from comparing the same parameter across different molecules irrespective of the way this has been measured. (Dave)
- Collect enough data to derive meaningful PK predictions - risk is there is not enough public data available so companies must be open to sharing non-public data. (Terry)
- Derive biophysical data from suitably classified mAbs and understand potential correlations with clinical PK. (Yves)
| - Use the dataset to improve the likelihood of developing new predictive models
- Use the dataset for better standardisation; allowing for robust comparison, cross referencing, identifying outliers and further analyses.
| - Time and effort
- Generating new biophysical data (Yves)
- Sharing newly generated biophysical data (Yves)
- Sharing non-public data
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Scope:
>Initial focus is on mAbs
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