Digitalization has paved the way for new paradigms such as digital shadows and digital twins for fermentation processes, opening the door for real-time process monitoring, control, and optimization. ...With a digital shadow, real-time model adaptation to accommodate complex metabolic phenomena such as metabolic shifts of a process can be monitored. Despite the many benefits of digitalization, the potential has not been fully reached in the industry. This study investigates the development of a digital shadow for a very complex fungal fermentation process in terms of microbial physiology and fermentation operation on pilot-scale at Novonesis and the challenges thereof. The process has historically been difficult to optimize and control due to a lack of offline measurements and an absence of biomass measurements. Pilot-scale and lab-scale fermentations were conducted for model development and validation. With all available pilot-scale data, a data-driven soft sensor was developed to estimate the main substrate concentration (glucose) with a normalized root mean squared error (N-RMSE) of 2%. This robust data-driven soft sensor was able to estimate accurately in lab-scale (volume < 20× pilot) with a N-RMSE of 7.8%. A hybrid soft sensor was developed by combining the data-driven soft sensor with a mass balance to estimate the glycerol and biomass concentrations on pilot-scale data with N-RMSEs of 11% and 21%, respectively. A digital shadow modeling framework was developed by coupling a mechanistic model (MM) with the hybrid soft sensor. The digital shadow modeling framework significantly improved the predictability compared with the MM. The contribution of this study brings the application of digital shadows closer to industrial implementation. It demonstrates the high potential of using this type of modeling framework for scale-up and leads the way to a new generation of in silico-based process development.
The information obtained from the chemical analysis of specific human excretion products (biomarkers) in urban wastewater can be used to estimate the exposure or consumption of the population under ...investigation to a defined substance. A proper biomarker can provide relevant information about lifestyle habits, health and wellbeing, but its selection is not an easy task as it should fulfil several specific requirements in order to be successfully employed. This paper aims to summarize the current knowledge related to the most relevant biomarkers used so far. In addition, some potential wastewater biomarkers that could be used for future applications were evaluated. For this purpose, representative chemical classes have been chosen and grouped in four main categories: (i) those that provide estimates of lifestyle factors and substance use, (ii) those used to estimate the exposure to toxicants present in the environment and food, (iii) those that have the potential to provide information about public health and illness and (iv) those used to estimate the population size. To facilitate the evaluation of the eligibility of a compound as a biomarker, information, when available, on stability in urine and wastewater and pharmacokinetic data (i.e. metabolism and urinary excretion profile) has been reviewed. Finally, several needs and recommendations for future research are proposed.
•Wastewater biomarkers provide information on lifestyle habits, health and wellbeing.•Specific criteria should be followed to select a suitable biomarker.•Report of the current knowledge of the most relevant biomarkers used so far•Proposal of potential wastewater biomarkers for future applications•Review of pharmacokinetic data and stability in urine and wastewater for each biomarker
Caffeine metabolites in wastewater were investigated as potential biomarkers for assessing caffeine intake in a population. The main human urinary metabolites of caffeine were measured in the urban ...wastewater of ten European cities and the metabolic profiles in wastewater were compared with the human urinary excretion profile. A good match was found for 1,7-dimethyluric acid, an exclusive caffeine metabolite, suggesting that might be a suitable biomarker in wastewater for assessing population-level caffeine consumption. A correction factor was developed considering the percentage of excretion of this metabolite in humans, according to published pharmacokinetic studies. Daily caffeine intake estimated from wastewater analysis was compared with the average daily intake calculated from the average amount of coffee consumed by country per capita. Good agreement was found in some cities but further information is needed to standardize this approach. Wastewater analysis proved useful to providing additional local information on caffeine use.
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•Analysis of caffeine and metabolites in wastewater in ten European cities•Comparison of metabolic profiles in wastewater and in human urine•Selection of a suitable biomarker for assessing population level caffeine consumption•Use of 1,7-dimethyluric acid for caffeine consumption back-calculation•Comparison of caffeine intake from wastewater vs coffee trade by country per capita
Monitoring the scale of pharmaceuticals, illicit and licit drugs consumption is important to assess the needs of law enforcement and public health, and provides more information about the different ...trends within different countries. Community drug use patterns are usually described by national surveys, sales and seizure data. Wastewater-based epidemiology (WBE) has been shown to be a reliable approach complementing such surveys.
This study aims to compare and correlate the consumption estimates of pharmaceuticals, illicit drugs, alcohol, nicotine and caffeine from wastewater analysis and other sources of information. Wastewater samples were collected in 2015 from 8 different European cities over a one week period, representing a population of approximately 5 million people. Published pharmaceutical sale, illicit drug seizure and alcohol, tobacco and caffeine use data were used for the comparison.
High agreement was found between wastewater and other data sources for pharmaceuticals and cocaine, whereas amphetamines, alcohol and caffeine showed a moderate correlation. methamphetamine and 3,4-methylenedioxymethamphetamine (MDMA) and nicotine did not correlate with other sources of data. Most of the poor correlations were explained as part of the uncertainties related with the use estimates and were improved with other complementary sources of data.
This work confirms the promising future of WBE as a complementary approach to obtain a more accurate picture of substance use situation within different communities. Our findings suggest further improvements to reduce the uncertainties associated with both sources of information in order to make the data more comparable.
This study presents a novel statistical approach for identifying sequenced chemical transformation pathways in combination with reaction kinetics models. The proposed method relies on sound ...uncertainty propagation by considering parameter ranges and associated probability distribution obtained at any given transformation pathway levels as priors for parameter estimation at any subsequent transformation levels. The method was applied to calibrate a model predicting the transformation in untreated wastewater of six biomarkers, excreted following human metabolism of heroin and codeine. The method developed was compared to parameter estimation methods commonly encountered in literature (i.e., estimation of all parameters at the same time and parameter estimation with fix values for upstream parameters) by assessing the model prediction accuracy, parameter identifiability and uncertainty analysis. Results obtained suggest that the method developed has the potential to outperform conventional approaches in terms of prediction accuracy, transformation pathway identification and parameter identifiability. This method can be used in conjunction with optimal experimental designs to effectively identify model structures and parameters. This method can also offer a platform to promote a closer interaction between analytical chemists and modellers to identify models for biochemical transformation pathways, being a prominent example for the emerging field of wastewater-based epidemiology.
Recent advances in artificial intelligence (AI) and data analytics (DA) could provide opportunities for the fault management and the decision-making of the urban wastewater treatment systems (UWS) ...operations. The UWS is typically a large system, including Sewer networks (SNs), Wastewater Treatment plants (WWTPs) and also considering the Receiving media (RM). However, applications of AI and DA in the UWS can be challenging due to the complexities and size of systems, the large variation in the level of UWS instrumentation, and the relatively poor data quality. This review goes beyond the state of the art by critically analyzing previous work on AI-based data-driven methodologies to system-wide fault detection, life cycle fault management and transformation of big and small data into analytics, particularly, considering two different points of view: process faults (such as bulking sludge, sewer corrosion & technology specifics) and instrumentation faults (such as sensors and actuators), thereby offering more opportunities to distinguish complex patterns and dynamics. Our analysis reveals the relative strengths and weaknesses of the different approaches to design fault diagnosis tools and to apply these in the UWS. Finally, the opportunities and challenges about the inter-play among UWS, data and AI are discussed.
•A plant-wide model is presented for continuous biomanufacturing benchmarking.•The model includes a tailored control strategy for dynamic simulation performance.•Realistic sensors and actuators ...consider measurement's noise and lag time.•Case study framework and examples are provided for user guidance.
The pharmaceutical industry's shift towards biological therapeutics has led to a transition from conventional batch production to continuous manufacturing. This change highlights the crucial need for effective process monitoring and control strategies to ensure consistent product quality and stability. Open-source benchmark simulation models have become essential tools for refining these processes, offering a platform for testing research hypotheses. This study uses the production of Lovastatin as a case study for continuous biopharmaceutical production. A comprehensive dynamic model covering upstream and downstream components provides an integrated perspective of the production process. The study introduces a basic control system emphasizing realistic sensor and actuator integration to enhance simulation accuracy. It assesses the benchmark through open-loop and closed-loop simulations, offering an in-depth analysis of the KTB1 model's dynamic response and functionality. KTB1 represents a model-driven decision support tool that enables the evaluation of monitoring strategies, process design, process optimization, and control for biomanufacturing.
Temperature is one of the key factors, influencing the transformation kinetics of organic chemicals. In the context of wastewater-based epidemiology, however, temperature differences among sewer ...catchments and within the same catchment (due to, e.g., seasonal variations) have been neglected to date as a factor influencing the estimation of illicit drug consumption. In this study, we assessed the influence of temperature on the transformation of biomarkers in wastewater and its ensuing implications on the back-calculation of chemical consumption rate in urban catchments using the example of selected illicit drugs. Literature data, obtained in laboratory-scale experiments, on the stability of drug biomarkers in untreated wastewater at trace levels was systematically reviewed, and transformation rates obtained at different temperatures were collected.
Arrhenius-based equations were fitted to empirical data and identified to describe the transformation of selected cocaine and morphine biomarkers at applicability temperature range (from 2–9 °C to 30–31 °C), with estimated exponential Arrhenius coefficients between 1.04 and 1.18. These empirically-derived relationships were used to assess the influence of temperature on the transformation of drug biomarkers during in-sewer transport and its effect on the back-calculation of drug consumption rate in hypothetical urban catchment scenario simulations. Up to 4-fold increase in removal efficiency was estimated when wastewater temperature increased from 15 °C to 25 °C. Findings from this study can help reducing the uncertainty intrinsic to wastewater-based epidemiology studies, and will be beneficial in comparing chemical consumption estimates from different catchments worldwide.
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•Assessing impacts of temperature on biomarker transformation on WBE predictions•Broad literature review on transformation rates combined with temperature data•Describing temperature-dependent transformation of biomarkers based on Arrhenius correlation•Findings facilitate significant reduction of uncertainties in WBE predictions.
Human biomonitoring, i.e. the determination of chemicals and/or their metabolites in human specimens, is the most common and potent tool for assessing human exposure to pesticides, but it suffers ...from limitations such as high costs and biases in sampling. Wastewater-based epidemiology (WBE) is an innovative approach based on the chemical analysis of specific human metabolic excretion products (biomarkers) in wastewater, and provides objective and real-time information on xenobiotics directly or indirectly ingested by a population. This study applied the WBE approach for the first time to evaluate human exposure to pesticides in eight cities across Europe. 24 h-composite wastewater samples were collected from the main wastewater treatment plants and analyzed for urinary metabolites of three classes of pesticides, namely triazines, organophosphates and pyrethroids, by liquid chromatography-tandem mass spectrometry. The mass loads (mg/day/1000 inhabitants) were highest for organophosphates and lowest for triazines. Different patterns were observed among the cities and for the various classes of pesticides. Population weighted loads of specific biomarkers indicated higher exposure in Castellon, Milan, Copenhagen and Bristol for pyrethroids, and in Castellon, Bristol and Zurich for organophosphates. The lowest mass loads (mg/day/1000 inhabitants) were found in Utrecht and Oslo. These results were in agreement with several national statistics related to pesticides exposure such as pesticides sales. The daily intake of pyrethroids was estimated in each city and it was found to exceed the acceptable daily intake (ADI) only in one city (Castellon, Spain). This was the first large-scale application of WBE to monitor population exposure to pesticides. The results indicated that WBE can give new information about the “average exposure” of the population to pesticides, and is a useful complementary biomonitoring tool to study population-wide exposure to pesticides.
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•WBE was applied for the first time to assess human exposure to pesticides in Europe.•Different patterns were observed among the cities and the classes of pesticides.•Results were in line with the national statistics related to pesticides exposure.•This study gives new information about the “average exposure” of the population.
Background and aims
Wastewater‐based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study ...were to: (i) assess spatial and temporal trends of population‐normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4‐methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011–17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data.
Design
Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017.
Setting and Participants
Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries.
Measurements
Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of Δ9‐tetrahydrocannabinol (11‐nor‐9‐carboxy‐Δ9‐tetrahydrocannabinol) were measured in wastewater using liquid chromatography–tandem mass spectrometry. Daily mass loads (mg/day) were normalized to catchment population (mg/1000 people/day) and converted to the number of combined doses consumed per day. Spatial differences were assessed world‐wide, and temporal trends were discerned at European level by comparing 2011–13 drug loads versus 2014–17 loads.
Findings
Benzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North–Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge.
Conclusions
The analysis of wastewater to quantify drug loads provides near real‐time drug use estimates that globally correspond to prevalence and seizure data.
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