Utilizing plant-based resources, particularly their by-products, aligns with sustainability principles and circular bioeconomy, contributing to environmental preservation. The therapeutic potential of plant extracts is garnering increasing interest, and this study aimed to demonstrate promising outcomes from an extract obtained from an underutilized plant waste. Chaetomorpha linum, an invasive macroalga found in the Orbetello Lagoon, thrives in eutrophic conditions, forming persistent mats covering approximately 400 hectares since 2005. The biomass of C. linum undergoes mechanical harvesting and is treated as waste, requiring significant human efforts and economic resources—A critical concern for municipalities. Despite posing challenges to local ecosystems, the study identified C. linum as a natural source of bioactive metabolites. Phytochemical characterization revealed lipids, amino acids, and other compounds with potential anti-inflammatory activity in C. linum extract. In vitro assays with LPS-stimulated RAW 264.7 and TNF-α/IFN-γ-stimulated HaCaT cells showed the extract inhibited reactive oxygen species (ROS), nitric oxide (NO), and prostaglandin E2 (PGE2) productions, and reduced inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) expressions via NF-κB nuclear translocation, in RAW 264.7 cells. It also reduced chemokines (TARC/CCL17, RANTES/CCL5, MCP-1/CCL2, and IL-8) and the cytokine IL-1β production in HaCaT cells, suggesting potential as a therapeutic candidate for chronic diseases like atopic dermatitis. Finally, in silico studies indicated palmitic acid as a significant contributor to the observed effect. This research not only uncovered the untapped potential of C. linum but also laid the foundation for its integration into the circular bioeconomy, promoting sustainable practices, and innovative applications across various industries.

Repurposing saffron (Crocus sativus) waste presents a sustainable strategy for generating high-value products within the bioeconomy framework. Typically, flower components are discarded after stigma harvest, resulting in significant waste—350 kg of tepals per kilogram of stigmas. This research employed a comprehensive approach, integrating bioactivity studies (in vitro and in silico) with Life Cycle Assessment (LCA) evaluations, to extract and assess bioactive compounds from C. sativus tepals sourced in Tuscany, Italy. Phytochemical characterization using UPLC-MS/MS revealed a high abundance and variety of flavonoids in the hydro-ethanolic extract (CST). The antioxidant capacity was validated through various assays, and the ability to mitigate H₂O₂-induced oxidative stress and enhance fermentation was demonstrated in Saccharomyces cerevisiae. This study reports that C. sativus tepals extract reduces oxidative stress and boosts ethanol fermentation in yeast, paving the way for applications in the food and biofuels sectors. Further validation in RAW 264.7 macrophages confirmed CST’s significant anti-inflammatory effects, indicating its potential for pharmaceutical, cosmeceutical, and nutraceutical applications. In silico studies identified potential targets involved in antioxidant and anti-inflammatory processes, shedding light on possible interaction mechanisms with Kaempferol 3-O-sophoroside (KOS-3), the predominant compound in the extract. The integration of LCA studies highlighted the environmental benefits of this approach. Overall, this research underscores the value of using waste-derived extracts through “green” methodologies, offering a model that may provide significant advantages for further evaluations compared to traditional methodologies and supporting the circular bioeconomy.

The sustainable utilization of biomass-derived bioactives addresses the growing demand for natural health products and supports sustainable development goals by reducing reliance on synthetic chemicals in healthcare. Cannabis sativa biomass, in particular, has emerged as a valuable resource within this context. This study focuses on the hydroethanolic extract of C. sativa leaves (CSE), which exhibited significant levels of phenolic compounds contributing to robust antioxidant activity. Evaluation using potassium ferricyanide, ABTS, and DPPH methods revealed potent radical scavenging activity comparable to the Trolox standard. UPLC-MS/MS profiling identified cannabinoids as the predominant secondary metabolites in CSE, with flavonoids also present in substantial quantities. This study investigated the anti-inflammatory potential of CSE on RAW 264.7 macrophages and IL-1β-stimulated C-20/A4 immortalized human chondrocytes, demonstrating protective effects without cytotoxic or mutagenic effects. Mechanistically, CSE reduced inflammation by inhibiting the MAPK and NF-κB signaling pathways. In silico approaches showed the ability of CSE’s main metabolites to bind and influence MAPK and NF-κB activity, confirming in vitro evidence. Incorporating C. sativa leaf extract into a hyaluronic acid-based formulation showed biotechnological promise for treating joint inflammation. Future research should aim to elucidate the molecular mechanisms underlying these effects and explore the potential of CSE-derived compounds in mitigating osteoarthritis progression. This approach highlights the significance of utilizing annually increasing biomass waste for sustainable bioactivity and environmental impact reduction.

The concept of a “circular bioeconomy” holds great promise for the health, cosmetic, and nutrition sectors by re-using Castanea sativa (Mill.) by-products. This sustainable resource is rich in bioactive secondary metabolites with antioxidant and anti-inflammatory properties. By transforming these by-products into high-value products for human health, we can promote sustainable economic growth and reduce the environmental impact of traditional waste disposal, adding value to previously underutilized resources. In the present study, we investigated the antioxidant capacity, phytochemical composition, and in vitro antioxidant and anti-inflammatory activity of C. sativa burr (CSB) aqueous extract. The spectrophotometric study revealed high total phenolic content (TPC) values with significant antioxidant and anti-radical properties. Using UPLC-MS/MS techniques, the phytochemical investigation identified 56 metabolites, confirming the presence of phenolic compounds in CSBs. In addition, CSBs significantly downregulated pro-inflammatory mediators in LPS-stimulated RAW 264.7 macrophage cells without significant cell toxicity. Lastly, in silico studies pinpointed three kinases from RAW 264.7 cells as binding partners with ellagic acid, the predominant compound found in our extract. These findings strongly advocate for the recycling and valorization of C. sativa by-products, challenging their conventional classification as mere “waste”.

Currently, many environmental and energy-related problems are threatening the future of our planet. In October 2022, the Worldmeter recorded the world population as 7.9 billion people, estimating that there will be an increase of 2 billion by 2057. The rapid growth of the population and the continuous increase in needs are causing worrying conditions, such as pollution, climate change, global warming, waste disposal, and natural resource reduction. Looking for novel and innovative methods to overcome these global troubles is a must for our common welfare. The circular bioeconomy represents a promising strategy to alleviate the current conditions using biomass-like natural wastes to replace commercial products that have a negative effect on our ecological footprint. Applying the circular bioeconomy concept, we propose an integrated in silico and in vitro approach to identify antioxidant bioactive compounds extracted from chestnut burrs (an agroforest waste) and their potential biological targets. Our study provides a novel and robust strategy developed within the circular bioeconomy concept aimed at target and drug discovery for a wide range of diseases. Our study could open new frontiers in the circular bioeconomy related to target and drug discovery, offering new ideas for sustainable scientific research aimed at identifying novel therapeutical strategies.

The role of computational tools in the drug discovery and development process is becoming central, thanks to the possibility to analyze large amounts of data. The high throughput and affordability of current omics technologies, allowing quantitative measurements of many putative targets, has exponentially increased the volume of scientific data available. The quality of the data and the speed with which in silico predictions can be validated in vitro is instrumental in accelerating clinical laboratory medicine, significantly and substantially impacting Precision Medicine (PM). PM affords the basis to develop new drugs by providing a wide knowledge of the patient as an essential step towards individualized medicine. It is, therefore, essential to collect as much information and data as possible on each patient to identify the causes of the different responses to drugs from a pharmacogenomics perspective and to identify biological biomarkers capable of accurately describing the risk signals to develop specific diseases. Furthermore, the role of biomarkers in early drug discovery is increasing, as they can significantly reduce the time it takes to develop new drugs. This review article will discuss how Artificial Intelligence fits in the drug discovery pipeline, covering the benefits of an automated, integrated laboratory framework where the application of Machine Learning methodologies to interpret omics-based data can avail the future perspective of Translational Precision Medicine.