Life cycle assessment of fine chemical production: a case study of pharmaceutical synthesis

Background, aim, and scope: Pharmaceuticals have been recently discussed in the press and literature regarding their occurrence in rivers and lakes, mostly due to emissions after use. The production of active pharmaceutical ingredients (APIs) has been less analyzed for environmental impacts. In this work, a life cycle assessment (LCA) of the production of an API from cradle to factory gate was carried out. The main sources of environmental impacts were identified. The resulting environmental profile was compared to a second pharmaceutical production and to the production of basic chemicals. Materials and methods: Detailed production data of a pharmaceutical production in Basel, Switzerland were used as the basis of this work. Information about the production of precursor chemicals was available as well. Using models and the ecoinvent database to cover remaining data gaps, a full life cycle inventory of the whole production was created. Using several life cycle impact assessment methods, including Cumulative Energy Demand (CED), Global Warming Potential (GWP), Eco-Indicator 99 (EI99), Ecological Scarcity 2006, and TRACI, these results were analyzed and the main sources of environmental burdens identified. Results: Pharmaceutical production was found to have significantly more environmental impacts than basic chemical production in a kilogram-per-kilogram basis. Compared to average basic chemical production, the API analyzed had a CED 20 times higher, a GWP 25 times higher and an EI99 (H/A) 17 times higher. This was expected to a degree, as basic chemicals are much less complex molecules and require significantly fewer chemical transformations and purifications than pharmaceutical compounds. Between 65% and 85% of impacts were found to be caused by energy production and use. The fraction of energy-related impacts increased throughout the production process. Feedstock use was another major contributor, while process emissions not caused by energy production were only minor contributors to the environmental impacts. Discussion: The results showed that production of APIs has much higher impacts than basic chemical production. This was to be expected given the increased complexity of pharmaceutical compounds as compared with basic chemicals, the smaller production volumes, and the fact that API production lines are often newer and less optimized than the production of more established basic chemicals. The large contributions of energy-related processes highlight the need for a detailed assessment of energy use in pharmaceutical production. The analysis of the energy-related contributions to the overall impacts on a process step level allows a comprehensive understanding of each process' contribution to overall impacts and their energy intensities. Conclusions: Environmental impacts of API production were estimated in a cradle-to-gate boundary. The major contributors to the environmental impacts in aggregating methods were resource consumption and emissions from energy production. Process emissions from the pharmaceutical manufacturing plant itself were less of a concern in developed countries. Producers aiming to increase their sustainability should increase efforts to reduce mass intensity and to improve energy efficiency. Recommendations and perspectives: Pharmaceutical companies have increased their efforts to optimize resource efficiency and energy use in order to improve their environmental performance. The results of this study can be used as a first step to perform a full cradle to grave LCA of pharmaceutical production and use, which could include other important phases of the pharmaceutical product life cycle. To assess a commercial pharmaceutical, the results of API production have to be compared to the contributions of other ingredients and formulatio

An Integrated Mechanistic Model of Mindfulness-Oriented Recovery Enhancement for Opioid-Exposed Mother–Infant Dyads

A growing body of neurobiological and psychological research sheds light on the mechanisms underlying the development and maintenance of opioid use disorder and its relation to parenting behavior. Perinatal opioid use is associated with risks for women and children, including increased risk of child maltreatment. Drawing from extant data, here we provide an integrated mechanistic model of perinatal opioid use, parenting behavior, infant attachment, and child well-being to inform the development and adaptation of behavioral interventions for opioid-exposed mother–infant dyads. The model posits that recurrent perinatal opioid use may lead to increased stress sensitivity and reward dysregulation for some mothers, resulting in decreased perceived salience of infant cues, disengaged parenting behavior, disrupted infant attachment, and decreased child well-being. We conclude with a discussion of Mindfulness-Oriented Recovery Enhancement as a means of addressing mechanisms undergirding perinatal opioid use, parenting, and attachment, presenting evidence on the efficacy and therapeutic mechanisms of mindfulness. As perinatal opioid use increases in the United States, empirically informed models can be used to guide treatment development research and address this growing concern

A Complex Regulatory Network Coordinating Cell Cycles During C. elegans Development Is Revealed by a Genome-Wide RNAi Screen

The development and homeostasis of multicellular animals requires precise coordination of cell division and differentiation. We performed a genome-wide RNA interference screen in Caenorhabditis elegans to reveal the components of a regulatory network that promotes developmentally programmed cell-cycle quiescence. The 107 identified genes are predicted to constitute regulatory networks that are conserved among higher animals because almost half of the genes are represented by clear human orthologs. Using a series of mutant backgrounds to assess their genetic activities, the RNA interference clones displaying similar properties were clustered to establish potential regulatory relationships within the network. This approach uncovered four distinct genetic pathways controlling cell-cycle entry during intestinal organogenesis. The enhanced phenotypes observed for animals carrying compound mutations attest to the collaboration between distinct mechanisms to ensure strict developmental regulation of cell cycles. Moreover, we characterized ubc-25, a gene encoding an E2 ubiquitin-conjugating enzyme whose human ortholog, UBE2Q2, is deregulated in several cancers. Our genetic analyses suggested that ubc-25 acts in a linear pathway with cul-1/Cul1, in parallel to pathways employing cki-1/p27 and lin-35/pRb to promote cell-cycle quiescence. Further investigation of the potential regulatory mechanism demonstrated that ubc-25 activity negatively regulates CYE-1/cyclin E protein abundance in vivo. Together, our results show that the ubc-25-mediated pathway acts within a complex network that integrates the actions of multiple molecular mechanisms to control cell cycles during development

6-OHDA-induced dopaminergic neurodegeneration in <i>Caenorhabditis elegans</i> is promoted by the engulfment pathway and inhibited by the transthyretin-related protein TTR-33

<div><p>Oxidative stress is linked to many pathological conditions including the loss of dopaminergic neurons in Parkinson’s disease. The vast majority of disease cases appear to be caused by a combination of genetic mutations and environmental factors. We screened for genes protecting <i>Caenorhabditis elegans</i> dopaminergic neurons from oxidative stress induced by the neurotoxin 6-hydroxydopamine (6-OHDA) and identified the <u>t</u>rans<u>t</u>hyretin-<u>r</u>elated gene <i>ttr-33</i>. The only described <i>C</i>. <i>elegans</i> transthyretin-related protein to date, TTR-52, has been shown to mediate corpse engulfment as well as axon repair. We demonstrate that TTR-52 and TTR-33 have distinct roles. TTR-33 is likely produced in the posterior arcade cells in the head of <i>C</i>. <i>elegans</i> larvae and is predicted to be a secreted protein. TTR-33 protects <i>C</i>. <i>elegans</i> from oxidative stress induced by paraquat or H₂O₂ at an organismal level. The increased oxidative stress sensitivity of <i>ttr-33</i> mutants is alleviated by mutations affecting the KGB-1 MAPK kinase pathway, whereas it is enhanced by mutation of the JNK-1 MAPK kinase. Finally, we provide genetic evidence that the <i>C</i>. <i>elegans</i> cell corpse engulfment pathway is required for the degeneration of dopaminergic neurons after exposure to 6-OHDA. In summary, we describe a new neuroprotective mechanism and demonstrate that TTR-33 normally functions to protect dopaminergic neurons from oxidative stress-induced degeneration, potentially by acting as a secreted sensor or scavenger of oxidative stress.</p></div

Catastrophic crop insurance effectiveness: does it make a difference how yield losses are conditioned?

The study evaluates the effectiveness of a catastrophic drought-index insurance developed by applying two alternative methods - the standard regression analysis and the copula approach. Most empirical analyses obtain estimates of the dependence of crop yields on weather by employing linear regression. By doing so, they assume that the sensitivity of yields to weather remains constant over the whole distribution of the weather variable and can be captured by the effect of the weather index on the yield conditional mean. In our study we evaluate, whether the prediction of farm yield losses can be done more accurately by conditioning yields on extreme realisations of a weather index. Therefore, we model the dependence structure between yields and weather by employing the copula approach. Our preliminary results suggests that the use of copulas might be a more adequate way to design and rate weather-based insurance against extreme events

Flexible weather index-based insurance design

This study investigates the performance of a flexible index design for weather index-based insurances using farm-level panel data on wheat production from Kazakhstan. The proposed flexible design is a generic framework that uses Growing Degree Days to determine annual variable start and end dates for the insured period. This approach reflects the progress of phenological plant growth phases more accurately than fixed periods and hence is expected to reduce the basis risk of the index insurance. In addition, we develop an economic framework that focuses on the role of downside risks and apply Quantile Regression to tailor optimal insurance specifications. This framework is then used to compare the downside risks associated with the use of flexible and fixed insurance periods. The results show that the introduction of flexibility in the index design leads to a reduction in farmers’ downside risk exposure and to a more efficient contract design

Flexible weather index-based insurance design

This study investigates the performance of a flexible index design for weather index-based insurances using farm-level panel data on wheat production from Kazakhstan. The proposed flexible design is a generic framework that uses Growing Degree Days to determine annual variable start and end dates for the insured period. This approach reflects the progress of phenological plant growth phases more accurately than fixed periods and hence is expected to reduce the basis risk of the index insurance. In addition, we develop an economic framework that focuses on the role of downside risks and apply Quantile Regression to tailor optimal insurance specifications. This framework is then used to compare the downside risks associated with the use of flexible and fixed insurance periods. The results show that the introduction of flexibility in the index design leads to a reduction in farmers’ downside risk exposure and to a more efficient contract design.ISSN:2212-096

Yield trend estimation in the presence of non-constant technological change and weather effects

The application of yield time series in risk analysis prerequisites the estimation of technological trend which might be present in the data. In this paper, we show that in presence of highly volatile yield time series and non-constant technology, the consideration of the weather effect in the trend equation can seriously improve trend estimation results. We used ordinary least squares (OLS) and MM, a robust estimator. Our empirical analysis is based on weather data as well as farm-level and county-level yield data for a sample of grain-producing farms in Kazakhstan