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Design of Dynamic Experiments: A Data-Driven Methodology for the Optimization of Time-Varying Processes
2 references·5 citing·28 second hop
Design of Dynamic Experiments: A Data-Driven Methodology for the Optimization of Time-Varying Processes (2013)Design of Dynamic Experiments: A Data-Dri…Response Surfaces, Mixtures, and Ridge Analyses (2006)Response Surfaces, Mixtures, …Designing robust optimal dynamic experiments (2002)Designing robust optimal dyna…Opportunities and Challenges for Statisticians in Advanced Pharmaceutical Manufacturing (2019)Opportunities and Challenges …GPdoemd: A Python package for design of experiments for model discrimination (2019)GPdoemd: A Python package for…Multivariate Analysis and Statistics in Pharmaceutical Process Research and Development (2017)Multivariate Analysis and Sta…Intensified design of experiments for upstream bioreactors (2016)Intensified design of experim…Dynamic Response Surface Models: A Data-Driven Approach for the Analysis of Time-Varying Process Outputs (2016)Dynamic Response Surface Mode…DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS (1959)Optimum Designs in Regression Problems (1959)Model-based design of experiments for parameter precision: State of the art (2007)Model-Based Design of Parallel Experiments (2007)Computational procedures for optimal experimental design in biological systems (2008)Empirical Model Building and Response Surfaces (1988)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Modeling and optimization I: Usability of response surface methodology (2006)Kinetic and Data-Driven Reaction Analysis for Pharmaceutical Process Development (2019)Uniting laboratory automation, DoE data, and modeling techniques to accelerate chemical process development (2019)Automation Technologies to Enable Data-Rich Experimentation: Beyond Design of Experiments for Process Modeling in Late-Stage Process Development (2021)Uniform Shell Designs (1970)Design and Analysis of Experiments (2007)Bioprocess optimization using design‐of‐experiments methodology (2008)A bootstrap-aggregated hybrid semi-parametric modeling framework for bioprocess development (2019)Comparison of Modeling Methods for DoE‐Based Holistic Upstream Process Characterization (2020)Digital Twin Application for Model-Based DoE to Rapidly Identify Ideal Process Conditions for Space-Time Yield Optimization (2021)On the Experimental Attainment of Optimum Conditions (1951)Some New Three Level Designs for the Study of Quantitative Variables (1960)Discrimination Among Mechanistic Models (1967)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)Innovation in the pharmaceutical industry: New estimates of R&D costs (2016)Statistics for Spatial Data (1993)The Design and Analysis of Computer Experiments (2003)Design and Modeling for Computer Experiments (2005)Response surface design evaluation and comparison (2008)Response surface methodology (2010)Response surface methodology for advanced manufacturing technology optimization: theoretical fundamentals, practical guidelines, and survey literature review (2019)
this work references cited by second hop

References

  • 2006Response Surfaces, Mixtures, and Ridge Analyses626 cited
  • 2002Designing robust optimal dynamic experiments199 cited

Cited by

  • 2016Intensified design of experiments for upstream bioreactors56 cited
  • 2016Dynamic Response Surface Models: A Data-Driven Approach for the Analysis of Time-Varying Process Outputs42 cited
  • 2017Multivariate Analysis and Statistics in Pharmaceutical Process Research and Development25 cited
  • 2019GPdoemd: A Python package for design of experiments for model discrimination25 cited
  • 2019Opportunities and Challenges for Statisticians in Advanced Pharmaceutical Manufacturing5 cited

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