Industrial ecology has revolutionized our understanding of material stocks and flows in our economy and society. For this important discipline to have even deeper impact, we must understand the inherent nature of these materials in terms of human health and the environment. This paper focuses on methods to design synthetic chemicals to reduce their intrinsic ability to cause adverse consequence to the biosphere. Advances in the fields of computational chemistry and molecular toxicology in recent decades allow the development of predictive models that inform the design of molecules with reduced potential to be toxic to humans or the environment. The approach presented herein builds on the important work in quantitative structure-activity relationships by linking toxicological and chemical mechanistic insights to the identification of critical physical-chemical properties needed to be modified. This in silico approach yields design guidelines using boundary values for physiochemical properties. Acute aquatic toxicity serves as a model endpoint in this study. Defining value ranges for properties related to bioavailability and reactivity eliminates 99% of the chemicals in the highest concern for acute aquatic toxicity category. This approach and its future implementations are expected to yield very powerful tools for life cycle assessment practitioners and molecular designers that allow rapid assessment of multiple environmental and human health endpoints and inform modifications to minimize hazard.green chemistry | safer chemicals | rational design | toxicity prediction I ndustrial ecology and green chemistry are two rigorous scientific disciplines with global scientific communities that empower sustainability science. Sustainability science is the science, technology, and innovation in support of sustainable development-meeting human needs and reducing hunger and poverty while maintaining the life support systems of the planet (1, 2). With a systems view, industrial ecology investigates material and energy flows of coupled human-natural systems and has made significant strides in assessing the impacts of these flows on the environment and human health (3-8). The need for more sustainable products and processes has triggered (further) development of a large number of environmental assessment tools (9), including substance flow analysis (10), chemical/product risk assessment (11), life cycle assessment (LCA) (12-14), and a variety of screening tools (15-19). The knowledge generated by these investigations and assessments provides key information about the chemicals, materials and processes with the most significant adverse impacts throughout the life cycle. We need to understand the inherent nature of these materials to not only quantify their impact on human health and the environment but also to facilitate the design of a more sustainable materials basis of our society. Analogous to the industrial ecology assessment tools, several National Academies of Science reports have identified the need for new green chemist...

Using computer models to accurately predict toxicity outcomes is considered to be a major challenge. However, state-of-the-art computational chemistry techniques can now be incorporated in predictive models, supported by advances in mechanistic toxicology and the exponential growth of computing resources witnessed over the past decade. The CADRE (Computer-Aided Discovery and REdesign) platform relies on quantum-mechanical modeling of molecular interactions that represent key biochemical triggers in toxicity pathways. Here, we present an external validation exercise for CADRE-SS, a variant developed to predict the skin sensitization potential of commercial chemicals. CADRE-SS is a hybrid model that evaluates skin permeability using Monte Carlo simulations, assigns reactive centers in a molecule and possible biotransformations via expert rules, and determines reactivity with skin proteins via quantum-mechanical modeling. The results were promising with an overall very good concordance of 93% between experimental and predicted values. Comparison to performance metrics yielded by other tools available for this endpoint suggests that CADRE-SS offers distinct advantages for first-round screenings of chemicals and could be used as an in silico alternative to animal tests where permissible by legislative programs.

As vast numbers of new chemicals are introduced to market annually, we are faced with the grand challenge of protecting humans and the environment while minimizing economically and ethically costly animal testing. In silico models promise to be the solution we seek, but we find ourselves at crossroads of future development efforts that would ensure standalone applicability and reliability of these tools. A conscientious effort that prioritizes experimental testing to support the needs of in silico models (versus regulatory needs) is called for to achieve this goal. Using economic analogy in the title of this work, we argue that a prudent investment is to go all-in to support in silico model development, rather than gamble our future by keeping the status quo of a “balanced portfolio” of testing approaches. We discuss two paths to future in silico toxicologyone based on big-data statistics (“broadsword”), and the other based on direct modeling of molecular interactions (“scalpel”)and offer rationale that the latter approach is more transparent, is better aligned with our quest for fundamental knowledge, and has a greater potential to succeed if we are willing to transform our toxicity-testing paradigm.

In silico toxicity models are critical in addressing experimental aquatic toxicity data gaps and prioritizing chemicals for further assessment.

An attractive method for valorization of glycerol is the catalytic transformation to lactic acid. By overcoming the solubility challenge associated with known homogeneous catalysts for this reaction, we show that thermally robust Ir(I), Ir(III), and Ru(II) N-heterocyclic carbene (NHC) complexes with sulfonate-functionalized wingtips are highly prolific for this process, requiring no cosolvents other than aqueous base. The activity of the catalysts is compared under both conventional heating and microwave conditions. The most active catalyst reaches a TOF of 45 592 h −1 (microwave) and 3477 h −1 (conventional) with 1 equiv of KOH, and proceeds at a constant rate for at least 8 h. Although higher activity is observed with KOH, the catalysts are also highly active with the weaker base, K 2 CO 3 (13 000 h −1 and concurrent formation of formate). The protocol can be modified to achieve quantitative conversion of glycerol in only 3 h. The high activity of these catalysts compared to nonsulfonated analogs is attributed to the stabilization the lactate product in aqueous media. The most active catalyst retains equal activity for crude glycerol. A mechanism is proposed for the most active catalyst precursor involving O−H oxidative addition of glycerol.