Applicability of computational systems biology in toxicology

Advancements in breast cancer therapy: The promise of copper nanoparticles

BACKGROUND

Breast cancer (BC) is the most prevalent cancer among women worldwide and poses significant treatment challenges. Traditional therapies often lead to adverse side effects and resistance, necessitating innovative approaches for effective management.

OBJECTIVE

This review aims to explore the potential of copper nanoparticles (CuNPs) in enhancing breast cancer therapy through targeted drug delivery, improved imaging, and their antiangiogenic properties.

METHODS

The review synthesizes existing literature on the efficacy of CuNPs in breast cancer treatment, addressing common challenges in nanotechnology, such as nanoparticle toxicity, scalability, and regulatory hurdles. It proposes a novel hybrid method that combines CuNPs with existing therapeutic modalities to optimize treatment outcomes.

RESULTS

CuNPs demonstrate the ability to selectively target cancer cells while sparing healthy tissues, leading to improved therapeutic efficacy. Their unique physicochemical properties facilitate efficient biodistribution and enhanced imaging capabilities. Additionally, CuNPs exhibit antiangiogenic activity, which can inhibit tumor growth by preventing the formation of new blood vessels.

CONCLUSION

The findings suggest that CuNPs represent a promising avenue for advancing breast cancer treatment. By addressing the limitations of current therapies and proposing innovative solutions, this review contributes valuable insights into the future of nanotechnology in oncology.

Time to Change: A Systems Pharmacology Approach to Disentangle Mechanisms of Drug-Induced Mitochondrial Toxicity

An increasing number of commonly prescribed drugs are known to interfere with mitochondrial function, which is associated with almost half of all Food and Drug Administration black box warnings, a variety of drug withdrawals, and attrition of drug candidates. This can mainly be attributed to a historic lack of sensitive and specific assays to identify the mechanisms underlying mitochondrial toxicity during drug development. In the last decade, a better understanding of drug-induced mitochondrial dysfunction has been achieved by network-based and structure-based systems pharmacological approaches. Here, we propose the implementation of a tiered systems pharmacology approach to detect adverse mitochondrial drug effects during preclinical drug development, which is based on a toolset developed to study inherited mitochondrial disease. This includes phenotypic characterization, profiling of key metabolic alterations, mechanistic studies, and functional in vitro and in vivo studies. Combined with binding pocket similarity comparisons and bottom-up as well as top-down metabolic network modeling, this tiered approach enables identification of mechanisms underlying drug-induced mitochondrial dysfunction. After validation of these off-target mechanisms, drug candidates can be adjusted to minimize mitochondrial activity. Implementing such a tiered systems pharmacology approach could lead to a more efficient drug development trajectory due to lower drug attrition rates and ultimately contribute to the development of safer drugs. SIGNIFICANCE STATEMENT: Many commonly prescribed drugs adversely affect mitochondrial function, which can be detected using phenotypic assays. However, these methods provide only limited insight into the underlying mechanisms. In recent years, a better understanding of drug-induced mitochondrial dysfunction has been achieved by network-based and structure-based system pharmacological approaches. Their implementation in preclinical drug development could reduce the number of drug failures, contributing to safer drug design.

The Exposome and Toxicology: A Win-Win Collaboration

The development of the exposome concept has been one of the hallmarks of environmental and health research for the last decade. The exposome encompasses the life course environmental exposures including lifestyle factors from the prenatal period onwards. It has inspired many research programs and is expected to influence environmental and health research, practices, and policies. Yet, the links bridging toxicology and the exposome concept have not been well developed. In this review, we describe how the exposome framework can interface with and influence the field of toxicology, as well as how the field of toxicology can help advance the exposome field by providing the needed mechanistic understanding of the exposome impacts on health. Indeed, exposome-informed toxicology is expected to emphasize several orientations including (1) developing approaches integrating multiple stressors, in particular chemical mixtures, as well as the interaction of chemicals with other stressors, (2) using mechanistic frameworks such as the adverse outcome pathways to link the different stressors with toxicity outcomes, (3) characterizing the mechanistic basis of long-term effects by distinguishing different patterns of exposures and further exploring the environment-DNA interface through genetic and epigenetic studies, and (4) improving the links between environmental and human health, in particular through a stronger connection between alterations in our ecosystems and human toxicology. The exposome concept provides the linkage between the complex environment and contemporary mechanistic toxicology. What toxicology can bring to exposome characterization is a needed framework for mechanistic understanding and regulatory outcomes in risk assessment.

Public data sources to support systems toxicology applications

Public databases provide a wealth of freely available information about chemicals, genes, proteins, biological networks, phenotypes, diseases, and exposure science that can be integrated to construct pathways for systems toxicology applications. Relating this disparate information from public repositories, however, can be challenging since databases use a variety of ways to represent, describe, and make available their content. The use of standard vocabularies to annotate key data concepts, however, allows the information to be more easily exchanged and combined for discovery of new findings. We explore some of the many public data sources currently available to support systems toxicology, and demonstrate the value of standardizing data to help construct chemical-induced outcome pathways.

In Silico Toxicology Data Resources to Support Read-Across and (Q)SAR

A plethora of databases exist online that can assist in in silico chemical or drug safety assessment. However, a systematic review and grouping of databases, based on purpose and information content, consolidated in a single source, has been lacking. To resolve this issue, this review provides a comprehensive listing of the key in silico data resources relevant to: chemical identity and properties, drug action, toxicology (including nano-material toxicity), exposure, omics, pathways, Absorption, Distribution, Metabolism and Elimination (ADME) properties, clinical trials, pharmacovigilance, patents-related databases, biological (genes, enzymes, proteins, other macromolecules etc.) databases, protein-protein interactions (PPIs), environmental exposure related, and finally databases relating to animal alternatives in support of 3Rs policies. More than nine hundred databases were identified and reviewed against criteria relating to accessibility, data coverage, interoperability or application programming interface (API), appropriate identifiers, types of in vitro, in vivo,-clinical or other data recorded and suitability for modelling, read-across, or similarity searching. This review also specifically addresses the need for solutions for mapping and integration of databases into a common platform for better translatability of preclinical data to clinical data.

Adverse Drug Reactions for Medicines Newly Approved in Japan from 1999 to 2013: Hypertension and Hypotension

In this survey, the correlation between adverse drug reactions (ADRs) in human and animal toxicities was investigated for 393 medicines which were approved in Japan from September 1999 to March 2013. ADRs were collected from each Japanese package insert. Comparable animal toxicities with ADRs were collected by thorough investigation of common technical documents. The results of this survey show that hypertension and/or hypotension were mainly observed in medicines affecting the central nervous system. Hypertension was also observed in antipyretics, analgesics, anti-inflammatory agents, vasoconstrictors and agents using antibody. Concordance between human ADRs and animal toxicities was analysed. True-positive rate for hypertension and hypotension is 0.29 and 0.52, respectively. Positive likelihood ratio and inverse negative likelihood ratio are 1.98 and 1.21, respectively, in hypertension and 1.67 and 1.44, respectively, in hypotension. Concordance between human ADRs and animal toxicities is not so high in hypertension and hypotension. Identified mechanisms as on-target for hypertension and hypotension are 29.8% and 30.5%, respectively. More than half of the causative factors of hypertension and hypotension were unable to be elucidated. Our results show that the intake of medicines is often linked to blood pressure variations that are not predicted in animal toxicity studies. Improvement of drug development processes may be necessary to provide safer medicines because current animal toxicity studies are insufficient to predict all ADRs in human beings.

In silico ADME/T modelling for rational drug design

In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.