1. From Shallow to Deep Bioprocess Hybrid Modeling: Advances and Future Perspectives
MDPI Open Access Journal
Fermentation
2023-10-23 | Journal article
DOI: https://doi.org/10.3390/fermentation9100922
part of ISSN: 2311-5637
PID of zenodo repository: https://zenodo.org/records/11082856
Contributors: Roshanak Agharafeie; Joao Rodrigues correria Ramos; Jorge M. Mendes; and Rui Oliveira*
Abstract: Deep learning is emerging in many industrial sectors in hand with big data analytics to streamline production. In the biomanufacturing sector, big data infrastructure is lagging compared to other industries. A promising approach is to combine deep neural networks (DNN) with prior knowledge in hybrid neural network (HNN) workflows that are less dependent on the quality and quantity of data. This paper reviews published articles over the past 30 years on the topic of HNN applications to bioprocesses. It reveals that HNNs have been applied to various bioprocesses, including microbial cultures, animal cells cultures, mixed microbial cultures, and enzyme biocatalysis. HNNs have been applied for process analysis, process monitoring, development of software sensors, open- and closed-loop control, batch-to-batch control, model predictive control, intensified design of experiments, quality-by-design, and recently for the development of digital twins. Most previous HNN studies have combined shallow feedforward neural networks (FFNNs) with physical laws, such as macroscopic material balance equations, following the semiparametric design principle. Only recently, deep HNNs based on deep FFNNs, convolution neural networks (CNN), long short-term memory (LSTM) networks and physics-informed neural networks (PINNs) have been reported. The biopharma sector is currently a major driver but applications to biologics quality attributes, new modalities, and downstream processing are significant research gaps.
2. Life Cycle Assessment applied to polyhydroxyalkanoates production phases: A mini revie
Closed Access Conference Proceedings
IRIS | UNIBO | CRIS Current Research Information System
June 2023
30 anni di Life Cycle Assessment, sviluppi metodologici e applicativi
Page 287 – 295
Link: Life Cycle Assessment applied to polyhydroxyalkanoates production phases: a mini review (unibo.it)
PID of zenodo repository : 10.5281/zenodo.11105211
IRIS Alma Mater Studorium: https://cris.unibo.it/handle/11585/968302
Contributors: Martina Pelliconi; Serena Righi
Abstract: Polyhydroxyalkanoates (PHAs) are bio-based polyesters that are natural, renewables, biocompatible and biodegradable while having similar properties to commonly used plastic. However, their industrial production is still more expensive than the petroleum-based one. To make PHAs marketable on a large scale, it is therefore necessary to optimize every single phase of their production. This process must be accompanied by environmental assessments, to verify that PHAs are a greener alternative to conventional plastic. To do this, the best tool currently available is Life Cycle Assessment (LCA). The purpose of this study is to examine the state of the art regarding the application of the LCA methodology to all phases of PHAs production.
3. Exploring Supply-Side Barriers for Commercialization of New Biopolymer Production Technologies: A Systematic Review
MDPI Open Access Journal
Sustainability 2025
2025-01-21 | Journal article
DOI: https://doi.org/10.3390/su17030820
part of ISSN: 2071-1050
PID of zenodo repository: https://zenodo.org/records/14749965
Contributors: Catarina Possidonio*; Ana Rita Farias; Samuel Domingos; Bernardo Cruz; Silvia Luis; and Ana Loureiro
Abstract: The development of new biopolymer production technologies is becoming increasingly relevant for tackling the negative impact of linear plastics. Despite these potential benefits, their production and commercialization still face several obstacles that might hinder their widespread adoption. The present systematic review aimed to offer a thorough analysis of the multi-level supply-side barriers across researchers, policymakers, and industry professionals. Searches were performed in Web of Science, SCOPUS, PubMed, and IEEEXplore between June and July 2023. Publications between 2019 and 2023 were considered for analysis (n = 176). Content was coded following a PICO structure and the results were reported following the PRISMA checklist. We found that technological and knowledge barriers were the most identified, followed by economic, regulatory, supply stability, and behavioral challenges. Moreover, we found that 82% of the documents identified more than one barrier, reflecting the complex interaction between the different challenges in the field. Fostering interdisciplinary collaboration, establishing clear regulatory frameworks, and enhancing communication strategies are relevant recommendations for overcoming these barriers. These findings draft a multifaceted roadmap of the key barriers in the commercialization of new, sustainable biopolymer production technologies, and carry significant implications for future research, policy development, and industry practices.