Drug Discovery Today最新文献

This study conducted policy and regulation analyses and user acceptance surveys in three East Asian countries with developed telecommunication infrastructure (China, South Korea, and Japan) to determine the most effective way to implement mobile health (mHealth). Regional differences in users’ emphasis on the purpose of mHealth, including medical information referral or health management, appear to be influenced by regional regulation, thus making regulation analysis important when considering mHealth penetration strategies. Potential mHealth users have high expectations for medical information and correspondence, which is crucial for the pharmaceutical industry in terms of providing information and retaining patients. Furthermore, potential users are willing to use the system medically, which is beneficial to the pharmaceutical industry when introducing mHealth and prescriptions in combination.

This article addresses the research and development (R&D) productivity challenge of the pharmaceutical industry, focusing on United States Food and Drug Administration (FDA)-related new drug approvals of the top 20 pharmaceutical companies (2014–2023). We evaluated the degree of innovation in new drugs to determine the innovativeness of these leading companies. A key finding of our analysis is the decline in the number of new drugs approved by the FDA for these leading companies over the investigated time period. This trend suggests that some of the leading companies are losing ground in R&D innovation, raising concerns about their ability to sustain competitive advantage, ensure long-term market success, and maintain viable business models.

Eculizumab is an orphan drug with indications for extremely rare autoimmune disorders. It is primarily prescribed for use in patients with paroxysmal nocturnal hemoglobinuria and atypical hemolytic uremic syndrome; but is also highly effective in the treatment of myasthenia gravis, among others. By binding to the C5 protein in the complement system, eculizumab effectively inhibits cellular hemolysis and autoimmune reactions. Despite this effective treatment, some patients reported no improvement in symptoms. Genetic sequencing revealed three distinct C5 mutations in the non-responders and these polymorphisms appeared to be most prevalent among Japanese, Korean and African populations. Here, we present an overview of the current and potential future applications of eculizumab, as well as the disadvantages of eculizumab treatment in patients with C5 polymorphisms.

Oxygen-generating biomaterials are emerging as a groundbreaking solution for transforming cardiovascular engineering. These biomaterials generate and release oxygen within various biomedical applications, marking a new frontier in healthcare. Most cardiovascular treatments face a significant challenge, ensuring a consistent oxygen supply to nurture engineered tissues or even implanted devices. Traditional methods relying on passive oxygen diffusion often fall short, hindering functional cardiovascular tissue development. Oxygen-generating biomaterials, incorporating agents like calcium peroxide, provide a controlled oxygen source to the surrounding cells. This innovation potentially enhances cell viability, stimulates growth and boosts metabolic activity crucial for tissue health. Applications include repairing cardiac and vascular tissues, disease modeling, drug testing and personalized medicine, promising tailored treatments. Challenges like material toxicity and oxygen release control need consideration. As research progresses, the use of these innovative biomaterials in clinical translation could reshape cardiovascular healthcare, revolutionizing patient outcomes in heart disease treatment.

Prostate cancer (PCa) is one of the leading cancers in men and the lack of suitable biomarkers or their modulators results in poor prognosis. Membrane proteins (MPs) have a crucial role in the development and progression of PCa and can be attractive therapeutic targets. However, experimental limitations in targeting MPs hinder effective biomarker and inhibitor discovery. To overcome this barrier, computational methods can yield structural insights and screen large libraries of compounds, accelerating lead identification and optimization. In this review, we examine current breakthroughs in computer-aided drug design (CADD), with emphasis on structure-based approaches targeting the most relevant membrane-bound PCa biomarkers.

Deep generative models (GMs) have transformed the exploration of drug-like chemical space (CS) by generating novel molecules through complex, nontransparent processes, bypassing direct structural similarity. This review examines five key architectures for CS exploration: recurrent neural networks (RNNs), variational autoencoders (VAEs), generative adversarial networks (GANs), normalizing flows (NF), and Transformers. It discusses molecular representation choices, training strategies for focused CS exploration, evaluation criteria for CS coverage, and related challenges. Future directions include refining models, exploring new notations, improving benchmarks, and enhancing interpretability to better understand biologically relevant molecular properties.

Cardiac glycosides (CGs), which are traditionally used for heart disease, show promise for cancer therapy. However, there is a lack of a comprehensive review of clinical studies in this area, and so far, CGs have not been widely integrated into clinical cancer treatment. This review covers clinical studies from the past five years, highlighting the potential of CGs to reduce cancer risk, enhance chemotherapy effectiveness, mitigate chemotherapy-induced side effects and improve quality of life. Future clinical trials should personalize the dosage of CGs, integrate molecular testing and investigate immunogenic cell death induction and the potential of CGs for treating bone cancer and metastasis. Optimizing the repurposing of CGs for anticancer treatment requires consideration of specific CGs, cancer types and concurrent medications.

Drug development has historically relied on phase I–III clinical trials including participants sharing the same disease. However, drug development has evolved as the discovery of mechanistic drivers of disease demonstrated that the same therapeutic target may provide benefits across different diseases. A basket trial condenses evaluation of one therapy among multiple related diseases into a single trial and presents an opportunity to borrow information across them rather than viewing each in isolation. Borrowing is a statistical tool but requires a foundation of clinical and therapeutic mechanistic justification. We review the Bayesian borrowing approach, including its assumptions, and provide a framework for how this approach can be evaluated for successful use in a basket trial for drug development.

Coronavirus disease 2019 (COVID-19) was declared a global pandemic in March 2020, which precipitated urgent public health responses. The causative agent, SARS-CoV-2, spreads primarily via respiratory droplets, necessitating precautions to mitigate transmission risks. Biopharmaceutical industries and academic institutions worldwide swiftly redirected their research endeavors towards developing therapeutic interventions, focusing on monoclonal antibodies, antiviral agents, and immunomodulatory therapies. The evolving body of evidence surrounding these treatments has prompted successive updates and revisions from the FDA, delineating the evolving landscape of COVID-19 therapeutics. This review comprehensively examines each treatment modality within the context of their developmental trajectories and regulatory approvals throughout the pandemic. Furthermore, it elucidates their mechanisms of action and presents clinical data underpinning their utility in combating the COVID-19 crisis.

Influenza still poses a significant challenge due to its high mutation rates and the low effectiveness of traditional vaccines. At present, antibodies that neutralize the highly variable hemagglutinin antigen are a major driver of the observed variable protection. To decipher how influenza vaccines can be improved, an analysis of licensed vaccine platforms was conducted, contrasting the strengths and limitations of their different mechanisms of protection. Through this review, it is evident that these vaccines do not elicit the robust cellular immune response critical for protecting high-risk groups. Emerging platforms, such as RNA vaccines, that induce robust cellular responses that may be additive to the recognized mechanism of protection through hemagglutinin inhibition may overcome these constraints to provide broader, protective immunity. By combining both humoral and cellular responses, such platforms could help guide the future influenza vaccine development.