Computational Developability Prediction
Computational Developability Prediction is a scholarly methodological framework that systematically employs computational models and algorithms to quantitatively assess the likelihood of successful development and manufacturability of therapeutic candidates, particularly biopharmaceuticals, by predicting physicochemical and biological properties indicative of developability.
14
Publications
1.1K
Citations
86
Authors
27
Institutions
Publications per year
2017–2026
11
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University of Oxford
Oxford, United Kingdom
3 h-index
12 publications
2.1K citations
University of Cambridge
Cambridge, United Kingdom
2 h-index
5 publications
205 citations
UCB Pharma (United Kingdom)
Slough, United Kingdom
2 h-index
5 publications
416 citations
AstraZeneca (United Kingdom)
Cambridge, United Kingdom
1 h-index
2 publications
68 citations
Roche Pharma AG (Germany)
Grenzach-Wyhlen, Germany
1 h-index
1 publications
368 citations
AstraZeneca (Sweden)
Södertälje, Sweden
1 h-index
6 publications
204 citations
Max Planck Institute of Biochemistry
Martinsried, Germany
1 h-index
1 publications
34 citations
Oxford Research Group
London, United Kingdom
1 h-index
2 publications
50 citations
1–8 of 27
3 publications · 143 citations
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2 publications · 65 citations
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1 publications · 69 citations
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Repository · 1 publications · 28 citations
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1 publications · 34 citations
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