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Types and cooperation of patent assignees (A) Changes in assignee types. (B) Collaboration patterns. The number represents cooperation frequency of different types of assignees (C, private companies; U, universities; R, research institutions; I, individuals).
Source publication
Implementing small interfering RNA (siRNA) is a promising therapy because it silences disease-related genes theoretically. However, the efficient delivery of siRNA is challenging, which limits its therapeutic applications. Various pharmaceutical delivery systems containing key technologies have been developed and patented, which are of great concer...
Contexts in source publication
Context 1
... the past 20 years, 10 countries and regions have been responsible for 95% of patents published: the United States (51%), Japan (9%), mainland China (7%), Canada (6%), Korea, Germany, and Switzerland (5% each), the United Kingdom (3%), and France and Israel (2% each) (see Figure 4A). Figure 4B displays the technological origins and market destinations. ...
Context 2
... the past 20 years, 10 countries and regions have been responsible for 95% of patents published: the United States (51%), Japan (9%), mainland China (7%), Canada (6%), Korea, Germany, and Switzerland (5% each), the United Kingdom (3%), and France and Israel (2% each) (see Figure 4A). Figure 4B displays the technological origins and market destinations. More than 90% of the patents filed originated in the 10 patent offices and organizations listed. ...
Citations
... The development of N-acetylgalactosamine (GalNAc) conjugates, which bind to the asialoglycoprotein receptor (ASGR) abundantly expressed on the surface of hepatocytes, has become a breakthrough approach for targeted delivery of siRNA to hepatocytes [6]. So far, GalNAc based therapies have held a prominent position in the drug development pipeline of several pharmaceutical companies [6], five GalNAc-based siRNA drugs have been approved by FDA, in which siRNAs are all conjugated to a GalNAc ligand and enable ASGPRmediated targeted delivery to hepatocytes [7][8][9]. GalNAc is relatively simple to synthesize and can be administrated subcutaneously, and has shown favorable biocompatibility/toxicity profiles, as well as very high efficacy, so it is currently the most popular platform for siRNA delivery [10]. At present, most siRNA drugs in clinical trials are based on GalNAc conjugation [10,11]. ...
Small interference RNA (siRNA) is a class of short double-stranded RNA molecules that cause mRNA degradation through an RNA interference mechanism and is a promising therapeutic modality. RBD1016 is a siRNA drug in clinical development for the treatment of chronic Hepatitis B Virus (HBV) infection, which contains a conjugated with N-acetylglucosamine moiety that can facilitate its hepatic delivery. We aimed to construct a semi-mechanistic model of RBD1016 in pre-clinical animals, to elucidate the pharmacokinetic/pharmacodynamic (PK/PD) profiles in mice and PK profiles in monkeys, which can lay the foundation for potential future translation of RBD1016 PK and PD from the pre-clinical stage to the clinic stage. The proposed semi-mechanistic PK/PD model fitted PK and PD data in HBV transgenic mice well and described plasma and liver concentrations in the monkeys well. The simulation results showed that our model has a reasonable predictive ability for Hepatitis B surface antigen (HBsAg) levels after multiple dosing in mice. Further PK and PD data for RBD1016, including clinical data, will assist in refining the model presented here. Our current effort focused on model building for RBD1016, we anticipate that the model could apply to other GalNAc-siRNA drugs.
Introduction:
Nucleic acid-based therapeutics offer groundbreaking potential for treating genetic diseases and advancing next-generation vaccines. Despite their promise, challenges in efficient delivery persist due to the properties of nucleic acids. Nanoparticles (NPs) serve as vital carriers, facilitating effective delivery to target cells, and addressing these challenges. Understanding the global landscape of patents in this field is essential for fostering innovation and guiding decision-making for researchers, the pharmaceutical industry, and regulatory agencies.
Areas covered:
This review provides a comprehensive overview of patent compositions, applications, and manufacturing aspects concerning NPs as nucleic acid delivery systems. It delves into temporal trends, protection locations, market dynamics, and the most influential technological domains. In this work, we provide valuable insights into the advancements and potential of NP-based nucleic acid delivery systems, with a special focus on their pivotal role in advancing cutting-edge therapeutic solutions.
Expert opinion:
Investment in NPs for nucleic acid delivery has significantly surged in recent years. However, translating these therapies into clinical practice faces obstacles, including the need for robust clinical evidence, regulatory compliance, and streamlined manufacturing processes. To address these challenges, our review article summarizes recent advances. We aim to engage researchers worldwide in the development of these promising technologies.
Wastewater treatment is a complex process that involves many uncertainties, leading to fluctuations in effluent quality and costs, and environmental risks. Artificial intelligence (AI) can handle complex nonlinear problems and has become a powerful tool for exploring and managing wastewater treatment systems. This study provides a summary of the current status and trends in AI research as applied to wastewater treatment, based on published papers and patents. Our results indicate that, at present, AI is primarily used to evaluate removal of pollutants (conventional, typical, and emerging contaminants), optimize models and process parameters, and control membrane fouling. Future research will likely continue to focus on removal of phosphorus, organic pollutants, and emerging contaminants. Moreover, analyzing microbial community dynamics and achieving multi-objective optimization are promising directions of research. The knowledge map shows that there may be future technological innovation related to predicting water quality under specific conditions, integrating AI with other information technologies and utilizing image-based AI and other algorithms in wastewater treatment. In addition, we briefly review development of artificial neural networks (ANNs) and explore the evolutionary path of AI in wastewater treatment. Our findings provide valuable insights into potential opportunities and challenges for researchers applying AI to wastewater treatment.
