Lignocellulose is the most abundant renewable material on Earth and the primary component of agricultural wastes such as sugarcane bagasse and wheat straw. It consists of a composite material made of cellulose, hemicellulose, and lignin. Cellulose and hemicellulose can be broken down into monomers by a set of appropriate enzymes, and the resulting monomers may be used to produce a variety of fuels or chemicals through either biological or chemical routes. However, the high production cost of these lignocellulose‐degrading enzymes remains a major challenge for the use of lignocellulosic biomass as raw material. In this context, this article reviews techno‐economic analyses concerning the production of cellulases and other lignocellulose‐degrading enzymes published over the last two decades. The major characteristics of each enzyme production process are described, underscoring the similarities and differences across the various process designs. Moreover, the enzyme production costs derived from these process designs and their composition in terms of raw materials, capital‐related factors, utilities, labor costs, etc., are compared. First, this analysis reveals that most techno‐economic evaluations in the literature address either cellulase production by submerged culture with Trichoderma reesei or enzyme production by solid‐state culture with filamentous fungi. Second, this analysis shows wide cost variations across process designs but it indicates that raw materials and capital‐related costs are generally the main drivers of the enzyme production cost. Furthermore, this assessment corroborates the importance of process parameters, such as product yield, production titer, and volumetric productivity, in the process economics of enzyme production. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

The COVID-19 pandemic has motivated the rapid development of numerous vaccines that have proven effective against SARS-CoV-2. Several of these successful vaccines are based on the adenoviral vector platform. The mass manufacturing of these vaccines poses great challenges, especially in the context of a pandemic where extremely large quantities must be produced quickly at an affordable cost. In this work, two baseline processes for the production of a COVID-19 adenoviral vector vaccine, B1 and P1, were designed, simulated and economically evaluated with the aid of the software SuperPro Designer. B1 used a batch cell culture viral production step, with a viral titer of 5 × 1010 viral particles (VP)/mL in both stainless-steel and disposable equipment. P1 used a perfusion cell culture viral production step, with a viral titer of 1 × 1012 VP/mL in exclusively disposable equipment. Both processes were sized to produce 400 M/yr vaccine doses. P1 led to a smaller cost per dose than B1 ($0.15 vs. $0.23) and required a much smaller capital investment ($126 M vs. $299 M). The media and facility-dependent expenses were found to be the main contributors to the operating cost. The results indicate that adenoviral vector vaccines can be practically manufactured at large scale and low cost.

Cellulase production was evaluated in two reference strains (T. reesei Rut-C30 and T. reesei QM9414), two strains isolated from a sugarcane cultivation area (Trichoderma sp. IPT778 and T. harzianum rifai IPT821) and one strain isolated in a program for biodiversity preservation in São Paulo state (Myceliophthora thermophila M77). Solid state cultures were performed using sugarcane bagasse (C), wheat bran (W) and/or soybean bran (S). The highest FPA was 10.6 U/gdm for M77 in SC (10:90) at 80% moisture, which was 4.4 times higher than production in pure W. C was a strong inducer of cellulase production, given that the production level of 6.1 U/gdm in WC (40:60) was 2.5 times higher than in pure W for strain M77; T. reesei Rut-C30 did not respond as strongly with about 1.6-fold surplus production. S advantageously replaced W, as the surplus production on SC (20:80) was 2.3 times relative to WC (20:80) for M77.

A Agência de Inteligência Brasileira (ABIN) é responsável pela elaboração do Plano de Proteção ao Conhecimento no âmbito do Sistema Brasileiro de Inteligência (SISBIN). Para isto, utiliza conhecimentos relativos à segurança da informação e comunicação para a proteção da infraestrutura crítica nacional. Nesse contexto, a ABIN produz recomendações estratégicas para a Administração Pública Federal (APF), prospecta suas vulnerabilidades e resguardar suas infraestruturas críticas de TI. Contudo, o conhecimento sobre essa proteção encontra-se fragmentado nos processos de análise de risco, de tratamento da segurança computacional e de governança da segurança da informação, representadas por um conjunto de ontologias. Este artigo relata a experiência da ABIN no uso de técnicas e ferramentas de Engenharia de Ontologias para a combinação de ontologias e extração do conhecimento relacionado à proteção da infraestrutura de TI da APF. Esse conhecimento auxilia o trabalho colaborativo dos vários atores envolvidos nesse processo no âmbito do SISBIN.