| Bioprocessing in the digital age: the role of process models H Narayanan, MF Luna, M von Stosch, MN Cruz Bournazou, G Polotti, ... Biotechnology journal 15 (1), 1900172, 2020 | 184 | 2020 |
| Machine learning for biologics: opportunities for protein engineering, developability, and formulation H Narayanan, F Dingfelder, A Butté, N Lorenzen, M Sokolov, P Arosio Trends in pharmacological sciences, 2021 | 110 | 2021 |
| A new generation of predictive models: The added value of hybrid models for manufacturing processes of therapeutic proteins H Narayanan, M Sokolov, M Morbidelli, A Butté Biotechnology and Bioengineering 116 (10), 2540-2549, 2019 | 89 | 2019 |
| Process‐wide control and automation of an integrated continuous manufacturing platform for antibodies F Feidl, S Vogg, M Wolf, M Podobnik, C Ruggeri, N Ulmer, R Wälchli, ... Biotechnology and Bioengineering 117 (5), 1367-1380, 2020 | 81 | 2020 |
| Sequential multivariate cell culture modeling at multiple scales supports systematic shaping of a monoclonal antibody toward a quality target M Sokolov, M Morbidelli, A Butté, J Souquet, H Broly Biotechnology journal 13 (4), 1700461, 2018 | 50 | 2018 |
| Hybrid Models for the simulation and prediction of chromatographic processes for protein capture H Narayanan, T Seidler, MF Luna, M Sokolov, M Morbidelli, A Butté Journal of Chromatography A 1650, 462248, 2021 | 48 | 2021 |
| A model‐based framework for parallel scale‐down fed‐batch cultivations in mini‐bioreactors for accelerated phenotyping E Anane, ÁC García, B Haby, S Hans, N Krausch, M Krewinkel, ... Biotechnology and bioengineering 116 (11), 2906-2918, 2019 | 45 | 2019 |
| Integrated Robotic Mini Bioreactor Platform for Automated, Parallel Microbial Cultivation With Online Data Handling and Process Control B Haby, S Hans, E Anane, A Sawatzki, N Krausch, P Neubauer, ... SLAS TECHNOLOGY: Translating Life Sciences Innovation 24 (6), 569-582, 2019 | 42 | 2019 |
| A new flow cell and chemometric protocol for implementing in‐line Raman spectroscopy in chromatography F Feidl, S Garbellini, S Vogg, M Sokolov, J Souquet, H Broly, A Butté, ... Biotechnology progress 35 (5), e2847, 2019 | 42 | 2019 |
| Design of Biopharmaceutical Formulations Accelerated by Machine Learning H Narayanan, F Dingfelder, I Condado Morales, B Patel, KE Heding, ... Molecular pharmaceutics 18 (10), 3843-3853, 2021 | 37 | 2021 |
| Hybrid modeling—a key enabler towards realizing digital twins in biopharma? M Sokolov, M von Stosch, H Narayanan, F Feidl, A Butté Current Opinion in Chemical Engineering 34, 100715, 2021 | 34 | 2021 |
| Hybrid Models Based on Machine Learning and an Increasing Degree of Process Knowledge: Application to Capture Chromatographic Step H Narayanan, M Luna, M Sokolov, P Arosio, A Butté, M Morbidelli Industrial & Engineering Chemistry Research 60 (29), 10466-10478, 2021 | 34 | 2021 |
| Combining Mechanistic Modeling and Raman Spectroscopy for Monitoring Antibody Chromatographic Purification F Feidl, S Garbellini, MF Luna, S Vogg, J Souquet, H Broly, M Morbidelli, ... Processes 7 (10), 683, 2019 | 34 | 2019 |
| Monte Carlo simulations for the analysis of nonlinear parameter confidence intervals in Optimal Experimental Design N Krausch, T Barz, A Sawatzki, M Gruber, S Kamel, P Neubauer, ... Frontiers in bioengineering and biotechnology 7, 122, 2019 | 31 | 2019 |
| Knowledge transfer across cell lines using hybrid Gaussian process models with entity embedding vectors C Hutter, M von Stosch, MNC Bournazou, A Butté Biotechnology and Bioengineering 118 (11), 4389-4401, 2021 | 30 | 2021 |
| Decision Tree‐PLS (DT‐PLS) algorithm for the development of process: Specific local prediction models H Narayanan, M Sokolov, A Butté, M Morbidelli Biotechnology progress 35 (4), e2818, 2019 | 30 | 2019 |
| Accelerated bioprocess development of endopolygalacturonase-production with saccharomyces cerevisiae using multivariate prediction in a 48 mini-bioreactor automated platform A Sawatzki, S Hans, H Narayanan, B Haby, N Krausch, M Sokolov, ... Bioengineering 5 (4), 101, 2018 | 27 | 2018 |
| Working within the Design Space: Do Our Static Process Characterization Methods Suffice? M von Stosch, R Schenkendorf, G Geldhof, C Varsakelis, M Mariti, ... Pharmaceutics 12 (6), 562, 2020 | 26 | 2020 |
| A roadmap to AI-driven in silico process development: bioprocessing 4.0 in practice M von Stosch, RMC Portela, C Varsakelis Current Opinion in Chemical Engineering 33, 100692, 2021 | 23 | 2021 |
| Decision Making and Risk Management in Biopharmaceutical Engineering—Opportunities in the Age of Covid-19 and Digitalization M Sokolov Industrial & Engineering Chemistry Research 59 (40), 17587-17592, 2020 | 21 | 2020 |
Alessandro ButteDataHow AGVerified email at datahow.ch
