Name
Title | ||
|---|---|---|
AI-ML applications in bioprocessing: ML as an enabler of real time quality prediction in continuous manufacturing of mAbs |
Abstract | ||
|---|---|---|
•Machine learning techniques enable real time process control and product quality prediction.•Proposed method assists process development in accordance with QbD approach.•Tree based regression techniques outperformed neural network and gradient boosting techniques.•Gradient boosting regression model performance depends on hyperparameters tuning.•Neural network requires large datasets for training and validation. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.compchemeng.2022.107896 | Computers & Chemical Engineering |
Keywords | DocType | Volume |
DNN,SVR,Random forest,Decision tree,Machine learning,Monoclonal antibody (MAB) | Journal | 164 |
ISSN | Citations | PageRank |
0098-1354 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saxena Nikita | 1 | 0 | 0.34 |
| Garima Thakur | 2 | 0 | 0.34 |
| Naveen G Jesubalan | 3 | 0 | 0.34 |
| Amey Kulkarni | 4 | 0 | 0.34 |
| Vinesh B. Yezhuvath | 5 | 0 | 0.34 |
| Anurag S Rathore | 6 | 0 | 0.34 |