AI Medical Compendium Journal:
Biotechnology progress

Showing 1 to 9 of 9 articles

Rapid total sialic acid monitoring during cell culture process using a machine learning model based soft sensor.

Biotechnology progress
Total sialic acid content (TSA) in biotherapeutic proteins is often a critical quality attribute as it impacts the drug efficacy. Traditional wet chemical assays to quantify TSA in biotherapeutic proteins during cell culture typically takes several h...

Raman spectroscopy and one-dimensional convolutional neural network modeling as a real-time monitoring tool for in vitro transaminase-catalyzed synthesis of a pharmaceutically relevant amine precursor.

Biotechnology progress
Raman spectroscopy has been used to measure the concentration of a pharmaceutically relevant model amine intermediate for positive allosteric modulators of nicotinic acetylcholine receptor in a ω-transaminase-catalyzed conversion. A model based on a ...

Leveraging machine learning to dissect role of combinations of amino acids in modulating the effect of zinc on mammalian cell growth.

Biotechnology progress
Although the contributions of individual components of cell culture media are largely known, their combinatorial effects are far less understood. Experiments varying one component at a time cannot identify combinatorial effects, and analysis of the l...

Smart process development: Application of machine-learning and integrated process modeling for inclusion body purification processes.

Biotechnology progress
The development of a biopharmaceutical production process usually occurs sequentially, and tedious optimization of each individual unit operation is very time-consuming. Here, the conditions established as optimal for one-step serve as input for the ...

Application of machine learning methods to pathogen safety evaluation in biological manufacturing processes.

Biotechnology progress
The production of recombinant therapeutic proteins from animal or human cell lines entails the risk of endogenous viral contamination from cell substrates and adventitious agents from raw materials and environment. One of the approaches to control su...

Application of a kNN-based similarity method to biopharmaceutical manufacturing.

Biotechnology progress
Machine learning-based similarity analysis is commonly found in many artificial intelligence applications like the one utilized in e-commerce and digital marketing. In this study, a kNN-based (k-nearest neighbors) similarity method is proposed for ra...

Optimization of biopharmaceutical downstream processes supported by mechanistic models and artificial neural networks.

Biotechnology progress
Downstream process development is a major area of importance within the field of bioengineering. During the design of such a downstream process, important decisions have to be made regarding the type of unit operations as well as their sequence and t...

Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

Biotechnology progress
This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating pa...

Use of uniform designs in combination with neural networks for viral infection process development.

Biotechnology progress
This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replic...