DNA-encoded libraries (DELs) allow starting chemical matter to be identified in drug discovery. The volume of experimental data generated also makes DELs an attractive resource for machine learning (ML). ML allows modeling complex relationships between compounds and numerical endpoints, such as the binding to a target measured by DELs. DELs could also empower other areas of drug discovery. Here, we propose that DELs and ML could be combined to model binding to off-targets, enabling better predictive toxicology. With enough data, ML models can make accurate predictions across a vast chemical space, and they can be reused and expanded across projects. Although there are limitations, more general toxicology models could be applied earlier during drug discovery, illuminating safety liabilities at a lower cost.

Active pharmaceutical ingredient(s) [API(s)] of dry powder inhalers (DPIs) deposition and their fate in the respiratory system are influenced by a complex matrix of formulation, device, manufacturing and physiological variations. DPIs on the market have shown bioinequivalence between batches of the same product. Despite being clinically insignificant, they affect bioequivalence studies when a generic product is compared with the originator. This review discusses implications of batch-to-batch variability on bioequivalence study outcomes and shortcomings of current regulatory requirements. Possible formulation and manufacturing factors resulting in batch-to-batch variability highlight the inherent nature of this issue. Despite scholarly investigations and official regulatory guidance, there remains a need for reliable and realistic in vitro tests that accurately guide a representative reference product batch selection.

Sulfotransferases (SULTs) are Phase II drug-metabolizing enzymes (DMEs) catalyzing the sulfation of a variety of endogenous compounds, natural products, and drugs. Various drugs, such as nonsteroidal anti-inflammatory drugs (NSAIDS) can inhibit SULTs, affecting drug-drug interactions. Several polymorphisms have been identified for SULTs that might be crucial for interindividual variability in drug response and toxicity or for increased disease risk. Here, we review current knowledge on non-synonymous single nucleotide polymorphisms (nsSNPs) of human SULTs, focusing on the coded SULT allozymes and molecular mechanisms explaining their variable activity, which is essential for personalized medicine. We discuss the structural and dynamic bases of key amino acid (AA) variants implicated in the impacts on drug metabolism in the case of SULT1A1, as revealed by molecular modeling approaches.

Drug side effects are an important study subject in pharmacology. Recent omics technologies provide a range of omics data and help to understand the biological mechanisms involved in drug effects. These modern technologies provide significant support to all biological disciplines, including drug toxicology. In this review, we provide an overview the use of omics applications to understand drug side effects at the molecular level. We discuss by available omics technologies, their possible uses, as well as their advantages and limitations.

Irregularities in cholesterol metabolism occur in a range of human cancers. Cholesterol precursors and derivatives support tumorigenesis and weaken immune responses. Intriguing preclinical and clinical findings demonstrate that cholesterol biosynthesis inhibition achieved by targeting major events and metabolites in cholesterol metabolism is an ideal anti-tumor strategy. Investigations addressing the effects of β-hydroxy β-methylglutaryl-CoA (HMG-CoA) reductase (HMGCR), 2,3-oxidosqualene cyclase (OSC), squalene synthase (SQS), liver X receptors (LXR), and cholesterol trafficking and esterification inhibition on cancer progression have shown encouraging results. Notably, manipulation of cholesterol metabolism strengthens the function of immune cells in the tumor microenvironment (TME). In this review, I discuss the role of cholesterol metabolism in cancer progression and the latest research related to cholesterol metabolism-based anti-cancer therapies and intend to bring this stylish biochemistry topic to the Sri Lankan research landscape.

Many exploratory clinical studies have been conducted on immune checkpoint inhibitors (ICIs) as new therapeutic approaches for the first-line treatment of patients with advanced gastric cancer. Despite varying interpretations of the successes and failures of this clinical research, most analyses have focused on the results from the perspective of exploring the superiority of immunotherapy. Consequently, the role of chemotherapy as an important partner of immunotherapy in first-line combination therapy regimens for gastric cancer has attracted less attention. Here, we explore and analyze first-line immunotherapies for gastric cancer from the perspective of chemotherapy, to understand reasons for the failure of studies and to indicate directions for future clinical research.

Coronavirus 2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has had significant impacts worldwide since its emergence in December, 2019. Despite a high recovery rate, there is a growing concern over its residual, long-term effects. However, because of a lack of long-term data, we are still far from establishing a consensus on post-COVID-19 complications. The deposition of excessive extracellular matrix (ECM), known as fibrosis, has been observed in numerous survivors of COVID-19. Given the exceptionally high number of individuals affected, there is an urgent need to address the emergence of fibrosis post-COVID-19. In this review, we discuss the clinical relevance of COVID-19-associated fibrosis, the current status of antifibrotic agents, novel antifibrotic targets, and challenges to its management.

Annexins (AnxAs) are Ca2+/phospholipid-binding proteins extensively studied and generally involved in several diseases. Although evidence exists regarding the distribuition of AnxAs in the visual system, their exact roles and the exact cell types of the eye where these proteins are expressed are not well-understood. AnxAs have pro-resolving roles in infectious, autoimmune, degenerative, fibrotic and angiogenic conditions, making them an important target in ocular tissue homeostasis. This review summarizes the current knowledge on the distribution and function of AnxA1-8 isoforms under normal and pathological conditions in the visual system, as well as perspectives for ophthalmologic treatments, including the potential use of the AnxA1 recombinant and/or its mimetic peptide Ac2-26.

Multiple sclerosis (MS) is an autoimmune neuroinflammatory disorder attributed to neurodegeneration and demyelination, resulting in neurological impairment. miRNA has a significant role in biological processes in MS. In this review, we focus on the feasibility of delivering miRNAs through nanoformulations for managing MS. We provide a brief discussion of miRNA synthesis and evidence for miRNA dysregulation in MS. We also highlight formulation strategies and resulting technologies for the effective delivery of miRNAs through nanocarrier systems for achieving high therapeutic benefits.

Cellular senescence was initially considered an effective antitumor mechanism, and senescence-induced therapy has previously been regarded as an efficient treatment. However, increasing studies have discovered that persistent senescent cells (SNCs) might have unanticipated negative repercussions for antitumor treatment. The long-term build-up of SNCs exacerbates toxic side effects, treatment resistance, and poor prognosis, and tumor cells that undergo senescence escape can acquire stemness to repopulate the tumor, leading to cancer recurrence. Thus, senotherapies that eliminate SNCs could be used as a new strategy for synergistic antitumor therapy. In this review, we summarize the adverse effects of SNCs in tumor development and the mechanisms by which senescent tumor cells escape senescence, discuss the relationship between senescence and polyploidy, and highlight the potential of senotherapies as an emerging adjuvant antitumor treatment strategy. Such a strategy is expected to provide new approaches for antitumor drug development from the perspective of cellular senescence.

There are many machine learning models that use molecular fingerprints of drugs to predict side effects. Characterizing their skill is necessary for understanding their usefulness in pharmaceutical development. Here, we analyze a statistical control of side effect prediction skill, develop a pipeline for benchmarking models, and evaluate how well existing models predict side effects identified in pharmaceutical documentation. We demonstrate that molecular fingerprints are useful for ranking drugs by their likelihood to cause a given side effect. However, the predictions for one or more drugs overall benefit only marginally from molecular fingerprints when ranking the likelihoods of many possible side effects, and display at most modest overall skill at identifying the side effects that do and do not occur.

Post-licensure safety data form the cornerstone of safety surveillance. However, such data have some limitations related to the subjectiveness of reporting and recording, primary purpose of the collected data, or heterogeneity. Routine capture of richer data would in part help mitigate these limitations, enabling earlier, more reliable safety insights. Digital health tools that remotely acquire health-related information are increasingly available and used by patients and the wider population. However, they are rarely used for pharmacovigilance purposes. Here, we review different cases that reveal the opportunities and challenges of using these technologies for enhanced safety assessment in routine healthcare delivery. We believe such approaches will advance our understanding of the safety of drugs and vaccines in the future.

Molecular fingerprints are used to represent chemical (structural, physicochemical, etc.) properties of large-scale chemical sets in a low computational cost way. They have a prominent role in transforming chemical data sets into consistent input formats (bit strings or numeric values) suitable for in silico approaches. In this review, we summarize and classify common and state-of-the-art fingerprints into eight different types (dictionary based, circular, topological, pharmacophore, protein-ligand interaction, shape based, reinforced, and multi). We also highlight applications of fingerprints in early drug research and development (R&D). Thus, this review provides a guide for the selection of appropriate fingerprints of compounds (or ligand-protein complexes) for use in drug R&D.

Extensive research efforts have been made and are still ongoing in the search for an ideal anti-cancer therapy. Almost all chemotherapeutics require a carrier or vehicle, a drug delivery system that can transport the drug specifically to the targeted cancer cells, sparing normal cells. Cell-penetrating peptides (CPPs) provide an effective and efficient pathway for the intra-cellular transportation of various bioactive molecules in several biomedical therapies. They are now well-recognized as facilitators of intracellular cargo delivery and have excellent potential for targeted anti-cancer therapy. In this review, we explain CPPs, recent progress in the development of new CPPs, and their utilization to transport cargoes such as imaging agents, chemotherapeutics, and short-interfering RNAs (siRNA) into tumor cells, contributing to the advancement of novel tumor-specific delivery systems.

Adipokines are the principal mediators in adipose signaling. Nevertheless, besides their role in energy storage, these molecules can be produced by other cells, such as immune cells or chondrocytes. Given their pleiotropic effects, research over the past few years has also focused on musculoskeletal diseases, showing that these adipokines might have relevant roles in worsening the disease or improving the treatment response. In this review, we summarize recent advances in our understanding of adipokines and their role in the most prevalent musculoskeletal immune and inflammatory disorders.

During a cytokine storm, dysregulated proinflammatory cytokines are produced in excess. Cytokine storms occur in multiple infectious diseases, including Coronavirus 2019 (COVID-19). Thus, eliminating cytokine storms to enhance patient outcomes is crucial. Given the numerous cytokines involved, individual therapies might have little effect. Traditional cytokines might be less effective than medicines that target malfunctioning macrophages. Nanomedicine-based therapeutics reduce cytokine production in animal models of proinflammatory illnesses. The unique physicochemical features and controlled nano-bio interactions of nanotechnology show promise in healthcare and could be used to treat several stages of this virus-induced sickness, including cytokine storm mortality. Macrophage-oriented nanomedicines can minimize cytokine storms and associated harmful effects, enhancing patient outcomes. Here, we also discuss engineering possibilities for enhancing macrophage efficacy with nanodrug carriers.

In many countries, β-thalassemia (β-THAL) is not uncommon; however, it qualifies as a rare disease in the US and in European Union (EU), where thalassemia drugs are eligible for Orphan Drug Designation (ODD). In this paper, we evaluate all 28 ODDs for β-THAL granted since 2001 in the US and the EU: of these, ten have since been discontinued, twelve are pending, and six have become licensed drugs available for clinical use. The prime mover for these advances has been the increasing depth of understanding of the pathophysiology of β-THAL; at the same time, and even though only one-fifth of β-THAL ODDs have become licensed drugs, the ODD legislation has clearly contributed substantially to the development of improved treatments for β-THAL.