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Strategic collaborations are critical to the success of efforts aimed at discovering new drugs and therapies in the biopharmaceutical industry. These collaborations aim to leverage domain expertise, asymmetries in production costs and/or capabilities to improve efficiency. Despite increasing collaborations, the biopharmaceutical industry lacks a structured guideline for choosing contracts. We present contract models with effort-based formulations that capture the key characteristics of biopharmaceutical operations and analyse incentive mechanisms such as fixed payment, revenue-sharing, risk-sharing, and cost-sharing in biopharmaceutical collaborations. We show that traditional incentive schemes do not achieve supply chain coordination, although they are commonly used in the industry. We introduce a new contract model called fee-for-effort-and-output contract that encourages the parties to exert higher efforts by offering discounts on their operating costs, and show that this contract achieves coordination with an appropriate selection of contract parameters. We also investigate the efficiency of noncoordinating contracts with traditional incentive schemes and identify the capability and cost structures under which they achieve the highest efficiency possible, to both determine the next-best alternatives and explain their popularity in practice. [ABSTRACT FROM AUTHOR]

Although public–private collaboration abounds in addressing societal grand challenges, little is known about its performance relative to private-sector collaboration. Drawing from the innovation collaboration literature, and qualitative insights from interviews and contracts, we argue that collaboration risk impairs task performance of public–private versus private–private collaboration. We attribute this to two collaboration risk mechanisms: cooperation problems arising from misaligned social versus economic incentives, and coordination problems due to differences in organizational governance and processes. We test our hypotheses using the development history of 2,496 antimicrobial drugs from 1995–2019. After accounting for endogenous selection into collaboration, we find that public–private collaboration is less effective than private–private collaboration. However, this performance gap reduces for innovation tasks under high technological uncertainty (i.e., in the discovery stage and for developing new drug action mechanisms). To probe the distinctive cooperation and coordination mechanisms, we also examine innovation task efficiency. Findings reveal a wider gap in task effectiveness but not efficiency between public–private and private–private collaboration, suggesting more significant cooperation than coordination problems. Our theoretical and practical insights pertain to whether, when, and how public–private and private–private collaboration offer viable pathways for socially beneficial innovation tasks. [ABSTRACT FROM AUTHOR]

Specialty drugs treat complex, severe diseases and offer significant therapeutic advances. Despite their potential to transform patient care, little is known about the drivers of their diffusion. In this study, the authors develop a framework for the diffusion of specialty drugs that is motivated by the drugs' novelty, complexity, and importance, with a focus on the role of scientific evidence production. They propose that the effects of scientific evidence on specialty drug diffusion are multifaceted and generated through the three stages of the scientific evidence production process: unpublished clinical studies, publications in medical journals not cited in clinical guidelines, and clinical guidelines. The findings from the empirical analysis of two specialty drugs validate the framework, supporting the idea of multistage scientific evidence effects. In contrast, marketing activities do not have a significant effect. Although this could be attributed to specialty drug prescribers discounting information from commercial sources, it may also be due to limited marketing support. An additional analysis on a nonspecialty drug further validates the proposed framework. Calculations of scientific evidence contributions to trial prescriptions indicate that scientific evidence production can generate returns beyond the publication stage, which should provide specialty drug manufacturers with strong incentives to commit to quality and innovation. [ABSTRACT FROM AUTHOR]

OBJECTIVE: This study aims to evaluate published clinical trials of ramucirumab to assess the risk/benefit profile and burden over time for patients. BACKGROUND: The burden of oncologic drug development on patients paired with increasing clinical trial failure rates emphasizes the need for reform of drug development. Identifying and addressing patterns of excess burden can guide policy, ensure evidence-based protections for trial participants, and improve medical decision-making. METHODS: On May 25, 2023 a literature search was performed on Pubmed/MEDLINE, Embase, Cochrane CENTRAL, and ClinicalTrials.gov for clinical trials using ramucirumab as monotherapy or in combination with other interventions for cancer treatment. Authors screened titles and abstracts for potential inclusion in a masked, duplicate fashion. Following data screening, data was extracted in a masked, duplicate fashion. Trials were classified as positive when meeting their primary endpoint and safety, negative or indeterminate. RESULTS: Ramucirumab was initially approved for gastric cancer but has since been tested in 20 cancers outside of its FDA approved indications. In our analysis of ramucirumab trials, there were a total of 10,936 participants and 10,303 adverse events reported. Gains in overall survival and progression-free survival for patients were 1.5 and 1.2 months, respectively. FDA-approved indications have reported more positive outcomes in comparison to off-label indications. CONCLUSION: We found that FDA-approved indications for ramucirumab had better efficacy outcomes than non-approved indications. However, a concerning number of adverse events were observed across all trials assessed. Participants in ramucirumab randomized controlled trials saw meager gains in overall survival when evaluated against a comparison group. Clinicians should carefully weigh the risks associated with ramucirumab therapy given its toxicity burden and poor survival gains.

Cardiovascular organ-on-a-chip (OoC) devices are composed of engineered or native functional tissues that are cultured under controlled microenvironments inside microchips. These systems employ microfabrication and tissue engineering techniques to recapitulate human physiology. This review focuses on human OoC systems to model cardiovascular diseases, to perform drug screening, and to advance personalized medicine. We also address the challenges in the generation of organ chips that can revolutionize the large-scale application of these systems for drug development and personalized therapy.

Recent advancements in AI-driven technologies, particularly in protein structure prediction, are significantly reshaping the landscape of drug discovery and development. This review focuses on the question of how these technological breakthroughs, exemplified by AlphaFold2, are revolutionizing our understanding of protein structure and function changes underlying cancer and improve our approaches to counter them. By enhancing the precision and speed at which drug targets are identified and drug candidates can be designed and optimized, these technologies are streamlining the entire drug development process. We explore the use of AlphaFold2 in cancer drug development, scrutinizing its efficacy, limitations, and potential challenges. We also compare AlphaFold2 with other algorithms like ESMFold, explaining the diverse methodologies employed in this field and the practical effects of these differences for the application of specific algorithms. Additionally, we discuss the broader applications of these technologies, including the prediction of protein complex structures and the generative AI-driven design of novel proteins.

In theory, financial markets promote innovation by selectively allocating capital to high-quality projects. In this article, I show that equity markets can also inhibit innovation. In public firms, I find that short-term equity market declines cause pharmaceutical companies to abandon early-stage drug developments, irrespective of drug quality or changes in a firm's stock price. I show that financing constraints drive this behavior, highlighting that even short-term market fluctuations can have long-term effects on pharmaceutical innovation and prevent potentially life-saving drugs from progressing to the market. [ABSTRACT FROM AUTHOR]

Many machine learning applications in bioinformatics currently rely on matching gene identities when analyzing input gene signatures and fail to take advantage of preexisting knowledge about gene functions. To further enable comparative analysis of OMICS datasets, including target deconvolution and mechanism of action studies, we develop an approach that represents gene signatures projected onto their biological functions, instead of their identities, similar to how the word2vec technique works in natural language processing. We develop the Functional Representation of Gene Signatures (FRoGS) approach by training a deep learning model and demonstrate that its application to the Broad Institutes L1000 datasets results in more effective compound-target predictions than models based on gene identities alone. By integrating additional pharmacological activity data sources, FRoGS significantly increases the number of high-quality compound-target predictions relative to existing approaches, many of which are supported by in silico and/or experimental evidence. These results underscore the general utility of FRoGS in machine learning-based bioinformatics applications. Prediction networks pre-equipped with the knowledge of gene functions may help uncover new relationships among gene signatures acquired by large-scale OMICs studies on compounds, cell types, disease models, and patient cohorts.

BackgroundAccording to the new AASLD Practice Guidance, all patients with primary sclerosing cholangitis (PSC) should be considered for participation in clinical trials. However, PSC's rarity has posed challenges to characterizing patient interest in trial participation and identifying predictors of patient willingness to participate in drug trials.MethodsPSC Partners Seeking a Cure developed the "Our Voices" survey to inform the development of the Externally-Led Patient-Focused Drug Development Forum, an FDA initiative to capture patient experiences and perspectives on drug development.ResultsOf 797 survey respondents from over 30 countries, 536 (67%) identified slowing disease progression as the most important outcome. Eighty-nine percent identified their hepatologist/gastroenterologist as someone they would approach for advice about trials. Although 61% reported being willing to participate in drug trials, only 26% had ever been asked to participate. Notable barriers to trial involvement included unknown long-term risks (71%), long travel times to the study center (32%), and a liver biopsy requirement (27%). On multivariable logistic regression, pruritus (OR 1.62, 95% CI: 1.09-2.40, p = 0.017) was positively associated with willingness to participate in disease-modifying therapy trials, while jaundice (OR 0.34, 95% CI: 0.19-0.61, p < 0.001) and inflammatory bowel disease (OR 0.64, 95% CI: 0.42-0.98, p = 0.038) were negatively associated. Pruritus (OR 2.25, 95% CI: 1.50-3.39, p < 0.001) was also independently associated with willingness to participate in symptom treatment trials.ConclusionsMost patients with PSC report interest in participating in clinical trials, but few have been asked to participate. Referral of patients with PSC by their hepatologist/gastroenterologist to clinical trials and patient education on trial participation are vital to closing the gap between trial interest and participation. Pruritus may serve as a key indicator of patient interest in trial participation.

Atherosclerotic coronary artery disease (CAD) is the causal pathological process driving most major adverse cardiovascular events (MACE) worldwide. The complex development of atherosclerosis manifests as intimal plaque which occurs in the presence or absence of traditional risk factors. There are numerous effective medications for modifying CAD but new pharmacologic therapies require increasingly large and expensive cardiovascular outcome trials to assess their potential impact on MACE and to obtain regulatory approval. For many disease areas, nearly a half of drugs are approved by the U.S. Food & Drug Administration based on beneficial effects on surrogate endpoints. For cardiovascular disease, only low-density lipoprotein cholesterol and blood pressure are approved as surrogates for cardiovascular disease. Valid surrogates of CAD are urgently needed to facilitate robust evaluation of novel, beneficial treatments and inspire investment. Fortunately, advances in non-invasive imaging offer new opportunity for accelerating CAD drug development. Coronary computed tomography angiography (CCTA) is the most advanced candidate, with the ability to measure accurately and reproducibly characterize the underlying causal disease itself. Indeed, favourable changes in plaque burden have been shown to be associated with improved outcomes, and CCTA may have a unique role as an effective surrogate endpoint for therapies that are designed to improve CAD outcomes. CCTA also has the potential to de-risk clinical endpoint-based trials both financially and by enrichment of participants at higher likelihood of MACE. Furthermore, total non-calcified, and high-risk plaque volume, and their change over time, provide a causally linked measure of coronary artery disease which is inextricably linked to MACE, and represents a robust surrogate imaging biomarker with potential to be endorsed by regulatory authorities. Global consensus on specific imaging endpoints and protocols for optimal clinical trial design is essential as we work towards a rigorous, sustainable and staged pathway for new CAD therapies.

Autophagy is a form of programmed cell degradation that enables the maintenance of homeostasis in response to extracellular stress stimuli. Autophagy is primarily activated by starvation and mediates the degradation, removal, or recycling of cell cytoplasm, organelles, and intracellular components in eukaryotic cells. Autophagy is also involved in the pathogenesis of human diseases, including several cancers. Human uveal melanoma (UM) is the primary intraocular malignancy in adults and has an extremely poor prognosis; at present there are no effective therapies. Several studies have suggested that autophagy is important in UM. By understanding the mechanisms of activation of autophagy in UM it may be possible to develop biomarkers to provide more definitive disease prognoses and to identify potential drug targets for the development of new therapeutic strategies. This article reviews the current information regarding autophagy in UM that could facilitate biomarker and drug development.

A new high-throughput optical sensor for captopril (CAP) is proposed. The sensor is based on the inhibitory effect of the analyte on the specific reaction of desferal with Fe(III) in an acidic medium. The whole analytical scheme was developed in micro-plates format combined with instrumental-free detection through an overhead book scanner. Dissolution testing was selected as an interesting application due to the generation of large amounts of samples during drug development. The method allowed the quantification of CAP up to 500 μM, with a lower limit of quantification LLOQ of 25 μM. 96 samples/standards could be processed simultaneously, obtaining a complete dissolution profile within 1 h (n = 12). Following validation, the obtained results were in accordance with the HPLC method recommended by the US Pharmacopeia. Finally, the greenness of the procedure was assessed by well-established tools such as the Green Analytical Procedure and Blue Applicability Grade indexes (77.5% score). [ABSTRACT FROM AUTHOR]

[Display omitted] Due to the complexity of regulatory networks of disease-related biomarkers, developing simple, sensitive, and accurate methods has remained challenging for precise diagnosis. Herein, an "AND" logic gates DNA molecular machine (LGDM) was constructed, which was powered by the catalytic hairpin assembly (CHA). It was coupled with dual-emission CdTe quantum dots (QDs)-based cation exchange reaction (CER) for label-free, sensitive, and ratiometric fluorescence detection of APE1 and miRNA biomarkers. Benefiting from synergistic signal amplification strategies and a ratiometric fluorometric output mode, this LGDM enables accurate logic computing with robust and significant output signals from weak inputs. It offers improved sensitivity and selectivity even in cell extracts. Using dual-emission spectra CdTe QDs, with a ratiometric signal output mode, ensured good stability and effectively prevented false-positive signals from intrinsic biological interferences compared to the approach relying on a single signal output mode, which enabled the LGDM to achieve rapid, efficient, and accurate natural drug screening against APE1 inhibitors in vitro and cells. The developed method provides impetus to streamline research related to miRNA and APE1, offering significant promise for widespread application in drug development and clinical analysis. [ABSTRACT FROM AUTHOR]

The efficient identification and validation of drug targets are paramount in drug discovery and development. Excessive costs, intricate procedures, and laborious sample handling frequently encumber contemporary methodologies. In this study, we introduce an innovative approach for the expeditious screening of drug targets utilizing solid-state nanopores. These nanopores provide a label-free, ultra-sensitive, and high-resolution platform for the real-time detection of biomolecular interactions. By observing the changes in relative ion currents over time after mixing different peptides with small molecule drugs, and supplementing this with noise analysis, we can pinpoint specific regions of drug action, thereby enhancing both the speed and cost-efficiency of drug development. This research offers novel insights into drug discovery, expands current perspectives, and lays the groundwork for formulating effective therapeutic strategies across a spectrum of diseases. [ABSTRACT FROM AUTHOR]

Predicting drug-target interactions (DTI) is a crucial stage in drug discovery and development. Understanding the interaction between drugs and targets is essential for pinpointing the specific relationship between drug molecules and targets, akin to solving a link prediction problem using information technology. While knowledge graph (KG) and knowledge graph embedding (KGE) methods have been rapid advancements and demonstrated impressive performance in drug discovery, they often lack authenticity and accuracy in identifying DTI. This leads to increased misjudgment rates and reduced efficiency in drug development. To address these challenges, our focus lies in refining the accuracy of DTI prediction models through KGE, with a specific emphasis on causal intervention confidence measures (CI). These measures aim to assess triplet scores, enhancing the precision of the predictions. Comparative experiments conducted on three datasets and utilizing 9 KGE models reveal that our proposed confidence measure approach via causal intervention, significantly improves the accuracy of DTI link prediction compared to traditional approaches. Furthermore, our experimental analysis delves deeper into the embedding of intervention values, offering valuable insights for guiding the design and development of subsequent drug development experiments. As a result, our predicted outcomes serve as valuable guidance in the pursuit of more efficient drug development processes. • The confidence method based on causal intervention is applied to drug target link prediction. • Three data sets and nine KGE models were used to verify the robustness of the proposed method. • The robustness of the results was evaluated by the optimal score and the dimension of the intervention input vector. • A comprehensive introduction to the algorithm and extensive experiments are conducted. [ABSTRACT FROM AUTHOR]

Accurately predicting drug-target affinity is crucial in expediting the discovery and development of new drugs, which is a complex and risky process. Identifying these interactions not only aids in screening potential compounds but also guides further optimization. To address this, we propose a multi-perspective feature fusion model, MFF-DTA, which integrates chemical structure, biological sequence, and other data to comprehensively capture drug-target affinity features. The MFF-DTA model incorporates multiple feature learning components, each of which is capable of extracting drug molecular features and protein target information, respectively. These components are able to obtain key information from both global and local perspectives. Then, these features from different perspectives are efficiently combined using specific splicing strategies to create a comprehensive representation. Finally, the model uses the fused features to predict drug-target affinity. Comparative experiments show that MFF-DTA performs optimally on the Davis and KIBA data sets. Ablation experiments demonstrate that removing specific components results in the loss of unique information, thus confirming the effectiveness of the MFF-DTA design. Improvements in DTA prediction methods will decrease costs and time in drug development, enhancing industry efficiency and ultimately benefiting patients. • The MFF-DTA model is proposed to accurately predict the affinity relationship between drugs and target proteins. • The model includes multiple feature extractors to capture global and local key features. • We create a comprehensive and information-rich representation. • The model has demonstrated strong performance on public datasets. [ABSTRACT FROM AUTHOR]

Valbenazine is a highly potent and selective inhibitor of synaptic vesicular monoamine transporter 2. The current therapeutic doses of valbenazine for tardive dyskinesia (TD) are 40, 60, or 80 mg capsules, given orally, once daily (QD). While 40 and 80 mg were investigated in phase 3 KINECT® 3 trial and initially approved, the approval of valbenazine 60 mg was based on the analysis utilizing the Model‐informed drug development (MIDD) approach, facilitated through the US Food and Drug Administration's MIDD Pilot Program. This study aimed to demonstrate the efficacy of 60 mg QD dose through model simulations using an established exposure‐response (E‐R) relationship between valbenazine active metabolite [+]‐α‐dihydrotetrabenazine exposure and the change from baseline in Abnormal Involuntary Movement Scale total score (AIMS‐CFB). A longitudinal E–R model was constructed based on the 40 and 80 mg data from the KINECT 3 trial. The final Emax model adequately predicted dose‐dependent improvement in the primary endpoint and was used to interpolate AIMS‐CFB for 60 mg at week 6. The efficacy of the unstudied 60 mg dose regimen is expected to be within the range of doses studied clinically with predicted mean AIMS‐CFB (95% confidence interval) of −2.69 (−3.30, −2.13) between observed mean AIMS‐CFB for 40 mg of −1.92 and 80 mg of −3.39. Results from this analysis provided the key evidence to establish efficacy of 60 mg QD without the need for an additional clinical trial. The availability of valbenazine 60 mg dose fills an existing medical need for patients with TD who could benefit from this third effective dose. [ABSTRACT FROM AUTHOR]

Advances in precision oncology led to approval of tumour-agnostic molecularly guided treatment options (MGTOs). The minimum requirements for claiming tumour-agnostic potential remain elusive. The European Society for Medical Oncology (ESMO) Precision Medicine Working Group (PMWG) coordinated a project to optimise tumour-agnostic drug development. International experts examined and summarised the publicly available data used for regulatory assessment of the tumour-agnostic indications approved by the US Food and Drug Administration and/or the European Medicines Agency as of December 2023. Different scenarios of minimum objective response rate (ORR), number of tumour types investigated, and number of evaluable patients per tumour type were assessed for developing a screening tool for tumour-agnostic potential. This tool was tested using the tumour-agnostic indications approved during the first half of 2024. A taxonomy for MGTOs and a framework for tumour-agnostic drug development were conceptualised. Each tumour-agnostic indication had data establishing objective response in at least one out of five patients (ORR ≥ 20%) in two-thirds (≥4) of the investigated tumour types, with at least five evaluable patients in each tumour type. These minimum requirements were met by tested indications and may serve as a screening tool for tumour-agnostic potential, requiring further validation. We propose a conceptual taxonomy classifying MGTOs based on the therapeutic effect obtained by targeting a driver molecular aberration across tumours and its modulation by tumour-specific biology: tumour-agnostic, tumour-modulated, or tumour-restricted. The presence of biology-informed mechanistic rationale, early regulatory advice, and adequate trial design demonstrating signs of biology-driven tumour-agnostic activity, followed by confirmatory evidence, should be the principles for tumour-agnostic drug development. The ESMO Tumour-Agnostic Classifier (ETAC) focuses on the interplay of targeted driver molecular aberration and tumour-specific biology modulating the therapeutic effect of MGTOs. We propose minimum requirements to screen for tumour-agnostic potential (ETAC-S) as part of tumour-agnostic drug development. Definition of ETAC cut-offs is warranted. • Advances in precision oncology led to the approval of tumour-agnostic therapies, challenging conventional drug development. • There is a need to establish a minimum set of requirements for a therapy to be eligible for tumour-agnostic potential. • Approved tumour-agnostic therapies had ORR ≥ 20% in 2/3 of tumour types (≥4) with ≥5 evaluable patients per tumour type. • Tumour-agnostic effect results from targeted driver molecular aberration interplay with tumour-specific modulating biology. • The ESMO PMWG proposes a framework to foster and accelerate tumour-agnostic drug development for patients with cancer. [ABSTRACT FROM AUTHOR]

The spread of carbapenemase-producing gram-negative pathogens, especially those producing metallo-β-lactamases (MBLs), has become a major health concern. MBLs are molecularly the most diverse carbapenemases, produced by a wide spectrum of gram-negative organisms, including the Enterobacterales, Pseudomonas spp., Acinetobacter baumannii, and Stenotrophomonas maltophilia, and can hydrolyze most β-lactams using metal ion cofactors in their active sites. Over the years, the prevalence of MBL-carrying isolates has increased globally, particularly in Asia. MBL infections are associated with adverse clinical outcomes including longer length of hospital stay, ICU admission, and increased mortality across the globe. The optimal treatment for MBL infections not only depends on the pathogen but also on the underlying resistance mechanisms. Currently, there are only few drugs or drug combinations that can efficiently offset MBL-mediated resistance, which makes the treatment of MBL infections challenging. The rising concern of MBLs along with the limited treatment options has led to the need and development of drugs that are specifically targeted towards MBLs. This review discusses the prevalence of MBLs, their clinical impact, and the current treatment options for MBL infections and their limitations. Furthermore, this review will discuss agents currently in the pipeline for treatment of MBL infections. [ABSTRACT FROM AUTHOR]

For public health protection, informed decision-making relies on having a robust foundation of evidence concerning risks and their prevention. Application of an evidence-based framework depends on the availability of pertinent, scientifically sound data generated by well-directed and valid research endeavors. In this essay, we address the current state of research in humans and the evidential base concerning high-concentration delta-9-tetrahydrocannabinol (delta-9-THC) products, which are readily available in the United States. Furthermore, we explore the intricate challenges faced in carrying out research on these products, which reflect the full range of study design issues: measurement of exposure and outcomes, confounding, selection bias, and the generalizability of findings. We offer recommendations to guide future research toward providing more informative evidence. By following these recommendations, researchers and funders on this emerging topic could move toward generating the valid and comprehensive evidence needed to effectively inform public health initiatives and guide policy decisions regarding high-concentration delta-9-THC products and their use. The urgency of generating such evidence cannot be overstated, given the widespread legalization and increasing availability and use of these products. (Am J Public Health. 2024;114(S8):S639–S644. https://doi.org/10.2105/AJPH.2024.307724) [ABSTRACT FROM AUTHOR]

“Somehow scientists still pursue the same questions, if now on higher levels of theoretical abstraction rooted in deeper layers of empirical evidence… To paraphrase an old philosophy joke, science is more like it is today than it has ever been. In other words, science remains as challenging as ever to human inquiry. And the need to communicate its progress… remains as essential now as then.” — Tom Siegfried, Science News 2021 In fact, essential questions about pain have not changed since IASP’s creation in Issaquah: what causes it and how can we treat it? Are we any closer to answering these questions, or have we just widened the gap between bench and bedside? The technology used to answer questions about pain mechanisms has certainly changed, whether the focus is on sensory neurons, spinal cord circuitry, descending controls or cortical pain processing. In this paper, we will describe how transgenics, transcriptomics, optogenetics, calcium imaging, fMRI, neuroimmunology and in silico drug development have transformed the way we examine the complexity of pain processing. But does it all, as our founders hoped, help people with pain? Are voltage-gated Na channels the new holy grail for analgesic development, is there a pain biomarker, can we completely replace opioids, will proteomic analyses identify novel targets, is there a “pain matrix,” and can it be targeted? Do the answers lie in our tangible discoveries, or in the seemingly intangible? Our founders could barely imagine what we know now, yet their questions remain. [ABSTRACT FROM AUTHOR]

The failure rate of drugs being developed for neuropsychiatric indications remains high. Optimizing drug discovery and development requires not only a better neurobiological understanding of disease aetiology and development, but also the means by which we can measure relevant biological and clinical processes related to disease progression, drug target engagement, and sensitivity to treatment. Here we address the role and key considerations for the selection of biomarkers in clinical drug development for neuropsychiatric disorders. We do not provide an exhaustive list of biomarkers; rather we lay out a pragmatic, well-defined biomarker selection strategy that addresses the main goals for each of the phases in the drug development cycle. We discuss the key questions and issues that concern biomarker selection and implementation in each phase of development. For the better development of biomarkers, we emphasize the need to focus on discrete biological dysfunction and/or symptom domains rather than diagnoses. We also advocate the use of biomarker-based patient stratification in phase 2 and 3 to increase sensitivity and power and reduce costs. Our aim is to enhance precision and chances of success for these complex and heterogeneous brain disorders with a high unmet medical need. [ABSTRACT FROM AUTHOR]

The serotonin 2A (5-HT2A) receptor is an important target for drug development and the main receptor through which classical psychedelics elucidate their hallucinogenic effects. The 5-HT2A receptor antagonist ketanserin has frequently been used as a tool to block the receptor. Here, we establish the dose-occupancy relation of ketanserin and the cerebral 5-HT2A receptor in healthy participants by conducting a positron emission tomography (PET) study. 120-min PET scans using the 5-HT2A receptor agonist radiotracer [11C]Cimbi-36 were conducted at baseline and after oral doses of either 10, 20, or 40 mg of ketanserin; each participant underwent one or two scans after ketanserin administration. Occupancy was defined as the percent change in neocortex binding potential (BP ND), estimated using the simplified reference tissue model (SRTM) with the cerebellum as reference region. Peroral ketanserin intake resulted in a plasma concentration-related increase in cerebral 5-HT2A receptor occupancy with the highest plasma ketanserin concentrations measured after ∼2 h. The relation between mean plasma ketanserin concentrations and 5-HT2A receptor occupancy conformed to a single-site binding model with an estimated EC 50 (95 % CI) of 2.52 (0.75; 8.1) ng/mL, which corresponds to a peroral dose of ketanserin of approximately 10 mg. These data elucidate for the first time in humans the cerebral pharmacodynamics of ketanserin, both benefitting its use as a pharmacological tool for probing brain function and adding to its potential for therapeutic use in rescuing a bad psychedelic experience. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is a complex multi-organ autoimmune disease marked by the production of autoantibodies against nuclear structures, formation of immune complexes, and chronic inflammation triggered by their tissular deposition. SLE is characterized by alternating periods of relapse and remission and each flare has the potential to cause new organ damage related to either the disease process or the medication toxicity. Despite remarkable progress across its multiple domains, SLE is still an area with many unmet needs, calling for innovative and practical solutions. The efforts of the drug development programme in lupus have led to considerable growth in the last decade, owing to the approval of belimumab, anifrolumab, and voclosporin. The increasing understanding of the pathogenesis of the disease has enabled the exploration of novel therapeutic strategies. New discoveries in the intricate cytokine kaleidoscope of lupus have made the concept of targeted therapy an attractive and promising research focus. JAK inhibitors are oral targeted therapies approved for a wide variety of diseases across the Rheumatology, Gastroenterology, Dermatology, and Haematology fields. Multiple JAKis are currently being investigated in SLE. This paper aims to summarize existing data coming from both clinical trials and case reports regarding the use of JAK inhibitors in SLE. [ABSTRACT FROM AUTHOR]

During recent decades, the metabolic dysfunction-associated steatohepatitis (MASH) field has witnessed several paradigm shifts, including the recognition of liver fibrosis as the main predictor of major adverse liver outcomes. Throughout this evolution, liver histology has been recognised as one of the main hurdles in MASH drug development due to its invasive nature, associated cost, and high inter- and intra-reader variability. Collective experience demonstrates the importance of consistency in the central reading process, where consensus methods have emerged as appropriate ways to mitigate against well-known challenges. Using crystalized knowledge in the field, stakeholders should collectively work towards the next paradigm shift, where non-invasive biomarkers will be considered surrogate endpoints for accelerated approval. In this review, we provide an overview of the evolution of the regulatory histology endpoints and the liver biopsy reading process, within the MASH trial landscape, over recent decades; we then review the biggest challenges associated with liver biopsy endpoints. Finally, we discuss and provide recommendations on the best practices for liver biopsy evaluation in MASH drug development. [ABSTRACT FROM AUTHOR]

The monoclonal IgE antibody SPE‐7 was originally raised against a 2,4‐dinitrophenyl (DNP) target. Through its ability to adopt multiple conformations, the antibody is capable of binding to a diverse range of small haptens and large proteins. The present study examines a dataset of experimentally determined crystal structures of the SPE‐7 antibody to gain insight into the mechanisms that contribute to its multispecificity. With the emergence of more and more therapeutic antibodies against a huge repertoire of different targets, our research could be of great interest for future drug development. We are able to discriminate between the different paratope‐binding states in the conformational ensembles obtained by enhanced sampling molecular dynamics simulations, and to calculate their transition timescales and state probabilities. Furthermore, we describe the key residues responsible for discriminating between the different binding capacities and identify a tryptophan in a central position of the CDR L3 loop as the residue of greatest interest. The overall dynamics of the paratope appear to be mainly influenced by the CDR L3 and CDR L1 loops. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to develop and evaluate a population PK model of mycophenolic acid (MPA) in pediatric kidney transplant patients to aid MPA dose optimization. Methods: Data were collected from pediatric kidney transplant recipients from a Dutch academic hospital (Radboudumc, the Netherlands). Pharmacokinetic model-building and model-validation analyses were performed using NONMEM. Subsequently, we externally evaluated the final model using data from another academic hospital. The final model was used to develop an optimized dosing regimen. Results: Thirty pediatric patients were included of whom 266 measured MPA plasma concentrations, including 20 full pharmacokinetic (PK) curves and 24 limited sampling curves, were available. A two-compartment model with a transition compartment for Erlang-type absorption best described the data. The final population PK parameter estimates were Ktr (1.48 h−1; 95% CI, 1.15–1.84), CL/F (16.0 L h−1; 95% CI, 10.3–20.4), Vc/F (24.9 L; 95% CI, 93.0–6.71E25), Vp/F (1590 L; 95% CI, 651–2994), and Q/F (36.2 L h−1; 95% CI, 9.63–74.7). The performance of the PK model in the external population was adequate. An optimized initial dose scheme based on bodyweight was developed. With the licensed initial dose, 35% of patients were predicted to achieve the target AUC, compared to 42% using the optimized scheme. Conclusion: We have successfully developed a pharmacokinetic model for MPA in pediatric renal transplant patients. The optimized dosing regimen is expected to result in better target attainment early in treatment. It can be used in combination with model-informed follow-up dosing to further individualize the dose when PK samples become available. [ABSTRACT FROM AUTHOR]

Aim: To assess the effects of a small‐molecule nicotinamide N‐methyltransferase (NNMT) inhibitor, 5A1MQ, on body composition, metabolic variables, fatty liver pathologies, and circulating biomarkers in diet‐induced obese (DIO) mice, and characterize its plasma pharmacokinetics (PK) and tissue distribution in vivo. Materials and Methods: DIO mice were administered vehicle or 5A1MQ once daily for 28 days. Longitudinal measures of body composition, blood glucose and plasma insulin levels, and terminal measures of liver histopathology and serum markers, were evaluated. Plasma and tissue PK were established in age‐ and strain‐matched mice after intravenous, oral, and subcutaneous dosing of 5A1MQ. Results: 5A1MQ treatment dose‐dependently limited body weight and fat mass gains, improved oral glucose tolerance and insulin sensitivity, and suppressed hyperinsulinaemia in DIO mice. Liver histology from 5A1MQ‐treated DIO mice showed attenuated hepatic steatosis and macrophage infiltration, and correspondingly reduced liver weight, size, and triglyceride levels. 5A1MQ treatment normalized circulating levels of alanine transaminase, aspartate transaminase, and ketone bodies, supporting an overall improvement in liver and metabolic functions. The pharmacodynamic effects of 5A1MQ were further corroborated by its high systemic exposure and effective distribution to metabolically active tissues, including adipose, muscle and liver, following subcutaneous dosing of mice. Conclusions: This work validates NNMT inhibition as a viable pharmacological approach to ameliorate metabolic imbalances and improve liver pathologies that develop with obesity. [ABSTRACT FROM AUTHOR]

The translation of in vitro potency of a candidate drug, as determined by traditional pharmacology metrics (such as EC50/IC50 and KD/Ki values), to in vivo efficacy and safety is challenging. Residence time, which represents the duration of drug‐target interaction, can be part of a more comprehensive understanding of the dynamic nature of drug‐target interactions in vivo, thereby enabling better prediction of drug efficacy and safety. As a consequence, a prolonged residence time may help in achieving sustained pharmacological activity, while transient interactions with shorter residence times may be favourable for targets associated with side effects. Therefore, integration of residence time into the early stages of drug discovery and development has yielded a number of clinical candidates with promising in vivo efficacy and safety profiles. Insights from residence time research thus contribute to the translation of in vitro potency to in vivo efficacy and safety. Further research and advances in measuring and optimizing residence time will bring a much‐needed addition to the drug discovery process and the development of safer and more effective drugs. In this review, we summarize recent research progress on residence time, highlighting its importance from a translational perspective. [ABSTRACT FROM AUTHOR]

Epimedium is a Chinese herb known as "yin and yang fire," first mentioned in the Compendium of Materia Medica. Many of the proprietary Chinese medicines used in clinical practice contain Epimedium as an ingredient, and its main active constituents include icariin, icaritin, and icariside II, among others. In addition to its traditional use in treating fatigue and sexual problems, modern research has confirmed that the main bioactive compounds in Epimedium have pharmacological effects such as antidepressant, antibacterial, antiviral, antioxidant, and anti-inflammatory properties, as well as inhibiting bone destruction, promoting bone growth, improving immune regulation and protecting the cardio-cerebral vascular system. With the continuous development of extraction and purification techniques, the development and use of bioactive compounds in Epimedium have significantly progressed, and the anticancer effect has received widespread attention. Since natural herbs have few side effects on the human body and do not easily develop drug resistance, they have long been the direction of research in cancer treatment. This review summarizes the latest research on the anticancer effects of Epimedium and its extracts, describes the bioactive compounds, pharmacological efficacy, and antitumor mechanism of Epimedium, and gives a new view on the administration and development of Epimedium. [ABSTRACT FROM AUTHOR]

Introduction: The European Medicines Agency Innovation Task Force (ITF) acts as early point of contact for medicine and technology developers to enable innovation during early drug development stages through ITF briefing meetings. Aim: To reflect on the current pace of innovation and to assess the potential of ITF stakeholder interactions, a comprehensive analysis of the ITF briefing meetings held between 2021 and 2022 was conducted with a focus on individual questions raised by the developers and the related feedback provided by the European regulators. Methods: Questions raised during ITF briefing meetings were extracted and categorised into main and sub-categories, revealing different themes across the whole medicine development process such as manufacturing technologies, pre-clinical developments, and clinically relevant questions. Results: There was positive feedback from regulators who gave initial guidance in 85% of the answers, provided concrete examples in 20% of the answers and recommended to continue discussions through additional regulatory procedures in 22% of the answers. Conclusion: This analysis frames the content and the type of topics discussed during ITF briefing meetings. Moreover, it describes the type of regulatory feedback provided to medicine developers and identified potential for improvement of these early interactions. Therefore, this analysis emphasises the role of ITF briefing meetings in fostering innovation in medicine. [ABSTRACT FROM AUTHOR]

Purpose: The transformative impact of Artificial intelligence (AI) on clinical trials is explored. To identify the potential benefits of AI in enhancing both the efficiency and effectiveness of clinical research, while also examining the challenges associated with its implementation. Methods: Through an analysis of research literature, case studies, and relevant regulatory frameworks, which highlights the potential of AI in clinical research. This includes improvements in patient recruitment, streamlined data analysis, and optimized clinical trial design. Case studies are presented to showcase the effectiveness of AI in achieving better trial outcomes. Results: Challenges that come with implementing AI such as issues regarding accountability and transparency due to increased reliance on AI-driven insights. Additionally, regulatory uncertainties around approving and overseeing AI-powered clinical trials, and ethical considerations concerning data privacy and potential biases within AI algorithms, are identified. Despite these challenges, the research emphasizes AI's potential to transform drug development by making clinical trials more efficient and insightful. Conclusion: The paper concludes by suggesting future research directions that explore the ethical, legal, and regulatory implications of AI in clinical trials, while further investigating its potential benefits for medical advancements. [ABSTRACT FROM AUTHOR]

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The ASCPT Journal Family provides a platform for research in clinical pharmacology and translational science, along with career development and networking opportunities. Members can renew their membership, submit abstracts for the Annual Meeting, and apply for editorial positions. The organization recognizes excellence in the field through awards and supports initiatives to advance clinical pharmacology and translational science. The text features the experiences of members like Erick Velasquez, Dr. Seeprarani Rath, Hyunseo Park, and Dr. Syed Saoud Zaidi, highlighting the importance of diversity and inclusion in the scientific community. New members from diverse backgrounds and institutions worldwide are welcomed, showcasing the global reach and inclusivity of ASCPT. [Extracted from the article]

Targeted covalent inhibitors (TCIs) are an emerging class of anticancer therapeutics. TCIs are designed to selectively engage their targeted proteins via covalent warheads. From the drug development standpoint, the covalent inhibition mechanism is anticipated to elicit the following theoretical benefits: (i) an extended duration of therapeutic action that is determined by the target protein turnover rate and not necessarily by drug half‐life, (ii) a lower therapeutic dose owing to greater pharmacological potency, (iii) lower risk of off‐target binding and associated adverse events, and (iv) reduced drug–drug interaction (DDI) liability due to high selectivity and low dose. Elucidating the clinical relevance of these expected benefits requires an integrated assessment of pharmacokinetics (PK), efficacy, safety, and DDI data. In this review, we compared the clinical pharmacology attributes of FDA‐approved oncology TCIs within the last 10 years against their reversible inhibitor (RI) counterparts. Our findings indicated that (i) PK half‐lives of TCIs were typically shorter and (ii) at their respective recommended clinical doses per drug label, the molar unbound steady state areas under the concentration‐time curve (AUCss) of TCIs were lower than those of RIs, but with longer clinically observed durations of response. However, (iii) there was no conclusive evidence supporting improved clinical safety profiles for TCIs, and (iv) DDI perpetrator profiles appeared to be similar between TCIs and RIs. The overall clinical pharmacology comparison of TCI vs. RI surveyed in this paper suggested that at least two of the four forecasted clinical benefits were achieved by TCIs. [ABSTRACT FROM AUTHOR]

Oxidative DNA damage‐related diseases, such as incurable inflammation, malignant tumors, and age‐related disorders, present significant challenges in modern medicine due to their complex molecular mechanisms and limitations in identifying effective treatment targets. Recently, 8‐oxoguanine DNA glycosylase 1 (OGG1) has emerged as a promising multifunctional therapeutic target for the treatment of these challenging diseases. In this review, we systematically summarize the multiple functions and mechanisms of OGG1, including pro‐inflammatory, tumorigenic, and aging regulatory mechanisms. We also highlight the potential of OGG1 inhibitors and activators as potent therapeutic agents for the aforementioned life‐limiting diseases. We conclude that OGG1 serves as a multifunctional hub; the inhibition of OGG1 may provide a novel approach for preventing and treating inflammation and cancer, and the activation of OGG1 could be a strategy for preventing age‐related disorders. Furthermore, we provide an extensive overview of successful applications of OGG1 regulation in treating inflammatory, cancerous, and aging‐related diseases. Finally, we discuss the current challenges and future directions of OGG1 as an emerging multifunctional therapeutic marker for the aforementioned challenging diseases. The aim of this review is to provide a robust reference for scientific researchers and clinical drug developers in the development of novel clinical targeted drugs for life‐limiting diseases, especially for incurable inflammation, malignant tumors, and age‐related disorders. SIGNIFICANCE STATEMENT: 8‐oxoguanine DNA glycosylase 1 (OGG1) has emerged as a promising multifunctional therapeutic target for the treatment of oxidative DNA damage‐related life‐limiting diseases, particularly incurable inflammations, malignant tumors, and age‐related disorders, due to its crucial multifunctional role in regulating oxidative DNA damage. As a potential therapeutic target, inhibiting OGG1 may provide a novel approach to prevent and treat inflammation and cancer, while activating OGG1 could be a strategy to prevent age‐related disorders. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease and is a major health threat globally. Its prevalence is forecasted to exponentially increase during the next 30 years due to the global aging population. Currently, approved drugs are merely symptomatic, being ineffective in delaying or blocking the relentless disease advance. Intensive AD research describes this disease as a highly complex multifactorial disease. Disclosure of novel pathological pathways and their interconnections has had a major impact on medicinal chemistry drug development for AD over the last two decades. The complex network of pathological events involved in the onset of the disease has prompted the development of multitarget drugs. These chemical entities combine pharmacological activities toward two or more drug targets of interest. These multitarget‐directed ligands are proposed to modify different nodes in the pathological network aiming to delay or even stop disease progression. Here, we review the multitarget drug development strategy for AD during the last decade. [ABSTRACT FROM AUTHOR]

Bone defects resulting from trauma, disease, or congenital abnormalities represent a significant clinical challenge, necessitating advanced regenerative therapies. This study presents the development and formulation of a drug-loaded hydrogel as a novel approach for bone regeneration. The hydrogel matrix is engineered to provide structural support and controlled release of therapeutic agents to enhance bone healing. Various biocompatible polymers and crosslinking strategies are investigated to optimize the hydrogel's mechanical properties, degradation kinetics, and drug release profiles. Furthermore, the study explores the efficacy of different drugs, growth factors, and osteoinductive molecules in promoting osteogenesis and bone tissue regeneration within the hydrogel scaffold. The developed drug-loaded hydrogel holds promise as a versatile platform for addressing diverse bone defects and advancing the field of regenerative orthopedics. [ABSTRACT FROM AUTHOR]

Rationale: This study focuses on the advantage of using the novel electron‐activated dissociation (EAD) technology on the QTOF system for structural elucidation of conjugation metabolites. In drug metabolite identification, conceptual "boxes" are generally used to represent potential sites of modifications, which are proposed based on MS/MS data. Electron‐activated dissociation (EAD) provides unique fragmentation patterns, potentially allowing for more precise localization of the metabolic modification sites compared to CID, particularly for conjugations. Method: Known compounds were incubated with rat liver microsomes in the presence of nicotinamide adenine dinucleotide phosphate (NADPH), uridine dihosphate‐glucuronic acid (UDPGA), and glutathione. Conjugation metabolites were analyzed using the QTOF system. High‐resolution MS/MS spectra were collected using EAD and CID fragmentations along with TOF MS full scan for tested drugs and metabolites. Fragmentation patterns were compared to evaluate their efficiency in structural elucidation. Results: Metabolite profiling identified conjugation metabolites (glucuronides and GSH adducts), using characteristic mass shifts. A comparison of EAD and CID fragmentation revealed EAD‐specific fragments for most conjugates. EAD was able to break the relatively stable bonds on parent drug motifs while keeping relatively weak conjugation bonds intact, despite the generally low intensity of EAD. EAD effectively narrowed the conceptual "box" representing modification sites, providing more definitive information on conjugation sites and facilitating the structural elucidation of conjugated metabolites. Conclusion: EAD is a powerful tool for metabolite profiling in drug development, particularly for identifying conjugation sites. EAD‐enabled MS/MS spectra offer a greater variety of signature fragments compared to CID, resulting in more comprehensive and unique structural information for metabolic modification analysis. Overall, EAD, complementary to CID, has the potential to narrow down potential modification sites, significantly enhancing the precision of conjugation metabolite structure elucidation. [ABSTRACT FROM AUTHOR]

Dengue viral infection is caused by the Dengue virus, which spreads to humans through the bite of infected mosquitos. Dengue affects over half of the global population, with an estimated 500 million infections per year. Despite this, no effective treatment is currently available, however, several promising candidates are undergoing pre-clinical/clinical testing. The existence of four major serotypes is an important challenge in the development of drugs and vaccines to combat Dengue virus infection. Hence, the drug/vaccine thereby developed should neutralize all the four serotypes equally. However, there is no pan-serotype specific treatment for Dengue virus, thereby emphasizing the need for the identification of novel drug-like compounds that can target all serotypes of the Dengue virus equally. To this end, we employed virtual screening methodologies to find drug-like compounds that target the domain III of glycoprotein E. Most importantly, domain III of E protein is involved in viral fusion with the host membrane and is also targeted by neutralizing antibodies. Our study found two small molecule drug-like compounds (out of the 3 million compounds screened) having similar binding affinity with all four serotypes. The compounds thereby identified exhibit favourable drug like properties and can be developed as a treatment for Dengue virus. [ABSTRACT FROM AUTHOR]

Background : Altered metabolism plays a role in the pathophysiology of cardiac diseases, such as atrial fibrillation (AF) and heart failure (HF). We aimed to identify novel plasma metabolites and proteins associating with cardiac disease. Methods: Mendelian randomisation (MR) was used to assess the association of 174 metabolites measured in up to 86,507 participants with AF, HF, dilated cardiomyopathy (DCM), and non-ischemic cardiomyopathy (NICM). Subsequently, we sourced data on 1567 plasma proteins and performed cis MR to identify proteins affecting the identified metabolites as well as the cardiac diseases. Proteins were prioritised on cardiac expression and druggability, and mapped to biological pathways. Results: We identified 35 metabolites associating with cardiac disease. AF was affected by seventeen metabolites, HF by nineteen, DCM by four, and NCIM by taurine. HF was particularly enriched for phosphatidylcholines (p = 0.029) and DCM for acylcarnitines (p = 0.001). Metabolite involvement with AF was more uniform, spanning for example phosphatidylcholines, amino acids, and acylcarnitines. We identified 38 druggable proteins expressed in cardiac tissue, with a directionally concordant effect on metabolites and cardiac disease. We recapitulated known associations, for example between the drug target of digoxin (AT1B2), taurine and NICM risk. Additionally, we identified numerous novel findings, such as higher RET values associating with phosphatidylcholines and decreasing AF and HF. RET is targeted by drugs such as regorafenib which has known cardiotoxic side-effects. Pathway analysis implicated involvement of GDF15 signalling through RET, and ghrelin regulation of energy homeostasis in cardiac pathogenesis. Conclusions: This study identified 35 plasma metabolites involved with cardiac diseases and linked these to 38 druggable proteins, providing actionable leads for drug development. [ABSTRACT FROM AUTHOR]

Natural products are a treasure trove for drug discovery, especially in the areas of infection, inflammation and cancer, due to their diverse bioactivities and complex, and varied structures. Chronic inflammation is closely related to many diseases, including complex diseases such as cancer and neurodegeneration. Improving target identification for natural products contributes to elucidating their mechanism of action and clinical progress. It also facilitates the discovery of novel druggable targets and the elimination of undesirable ones, thereby significantly enhancing the productivity of drug discovery and development. Moreover, the rise of polypharmacological strategies, considered promising for the treatment of complex diseases, will further increase the demand for target deconvolution. This review underscores strategies for identifying natural product targets (NPs) in the context of chronic inflammation over the past 5 years. These strategies encompass computational methodologies for early target discovery and the anticipation of compound binding sites, proteomics‐driven approaches for target delineation and experimental biology techniques for target validation and comprehensive mechanistic exploration. [ABSTRACT FROM AUTHOR]

Background: Patient and public co-creation and involvement in health initiatives have been witnessing great expansion in recent years. From healthcare to research settings, collaborative approaches are becoming increasingly prevalent and diverse, especially in the field of rare diseases which faces complex challenges. Conference development and implementation, however, have been primarily guided by passive, information-sharing models. There is a need for conferences to evolve towards more inclusive, interactive, collaborative, and problem-solving platforms. Here, we aimed to report on a pioneer model, emphasizing a community partnership approach to conference co-creation that takes the World Conference on Congenital Glycosylation Disorders (CDG) as an exemplary case. Methods: To answer the need to overcome the lack of access to high-quality information which limits CDG diagnosis, research and treatment options, the World CDG Organization has been refining a community-centric model for conference co-creation. Focusing on the 5th edition of the conference, data on stakeholders' preferences was collected using an online survey and a poll to define the conference agenda, guide its development and select optimal dates for an all-stakeholder inclusive, relevant and participatory event. Results: We describe the complexities of the community-centric conference co-creation model, detailing its refined methodology and the outcomes achieved. The model is grounded on a participative approach to promote people-centered research and care for CDG patients. The involvement of the public in the conference co-creation and in participatory methods allowed the generation of knowledge on community needs and preferences. Conclusion: This paper describes a reliable, highly adaptable conference co-creation model that fosters community-building, disseminates understandable information, and serves as a borderless platform to incentivize multiple stakeholder collaborations towards CDG research and drug development. We argue this is a reproducible model that can be endorsed and more widely adopted by other disease communities and events. Plain English summary: In recent years, there has been a growing trend towards involving patients and the public in healthcare and research, transforming traditional conferences that follow a one-way information-sharing approach into inclusive and interactive platforms. This study presents a unique conference co-creation model established by the World Congenital Disorders of Glycosylation (CDG) Organization that emphasizes partnership with the community in its design and implementation. Besides involving the community in the planning phase, the model also uses other participatory methods. The 5th World Conference on CDG, held in 2021, serves as a prime example of this approach. The resulting community partnership model is shown to produce outcomes tailored to community needs, promoting people-centered research and care. This model is reproducible and easily adaptable by other disease communities and events to promote collaboration and problem-solving. [ABSTRACT FROM AUTHOR]

Cryptosporidiosis is a diarrheal disease caused by infection with Cryptosporidium spp. parasites and is a leading cause of death in malnourished children worldwide. The only approved treatment, nitazoxanide, has limited efficacy in this at-risk patient population. Additional safe therapeutics are urgently required to tackle this unmet medical need. However, the development of anti-cryptosporidial drugs is hindered by a lack of understanding of the optimal compound properties required to treat this gastrointestinal infection. To address this knowledge gap, a diverse set of potent lysyl-tRNA synthetase inhibitors was profiled to identify optimal physicochemical and pharmacokinetic properties required for efficacy in a chronic mouse model of infection. The results from this comprehensive study illustrated the importance of balancing solubility and permeability to achieve efficacy in vivo. Our results establish in vitro criteria for solubility and permeability that are predictive of compound efficacy in vivo to guide the optimization of anti-cryptosporidial drugs. Two compounds from chemically distinct series (DDD489 and DDD508) were identified as demonstrating superior efficacy and prioritized for further evaluation. Both compounds achieved marked parasite reduction in immunocompromised mouse models and a disease-relevant calf model of infection. On the basis of these promising data, these compounds have been selected for progression to preclinical safety studies, expanding the portfolio of potential treatments for this neglected infectious disease. Editor's summary: Cryptosporidium spp. parasites are a major cause of potentially fatal, severe diarrhea in malnourished children, with no vaccine available and no reliably effective treatment for this at-risk population. Caldwell et al. studied the physiochemical properties required for lysyl-tRNA synthetase targeting anti-cryptosporidial compounds to be effective given the unique intracellular but extracytoplasmic location of infecting protozoa in the small intestine. Testing of two chemically distinct lead compounds in immunocompromised mouse and neonatal calf models showed improvement in infection, suggesting that these leads should be prioritized for further efficacy and safety studies. —Catherine Charneski [ABSTRACT FROM AUTHOR]

Effective prevention and treatment options for bone cancer-related pain (BCP) are lacking. In recent years, numerous studies have investigated the association between m6A epigenetic modifications and pain, revealing their significant role in pain initiation and maintenance. This study aimed to provide theoretical support for the treatment of BCP and to identify target drugs for future development. Specifically, we investigated the involvement of fat mass and obesity-related protein (FTO) in rat models of BCP by administering varying doses (1/5/10 mg/kg) of the FTO inhibitor meclofenamic acid (MA) and assessing changes in mechanical sensitivity through domain analysis, gait analysis, and open-field experiments. After successfully establishing the BCP model, we verified it by performing mechanical sensitivity assessments. We observed significantly increased expression levels of the demethylase FTO within the spinal dorsal horn accompanied by decreased m6A methylation levels in the model. Compared with untreated BCP rats, remarkably improved behavioral responses indicative of reduced pain were observed in the model rats after administration of 10 mg/kg MA, concomitant with decreased expression levels of FTO and increased m6A methylation levels. Compared with untreated BCP rats, the expression levels of p-ERK and pro-inflammatory cytokines were also significantly decreased after MA administration. Taken together, FTO can downregulate m6A methylation level and activate ERK/inflammatory cytokines signaling pathway to maintain BCP in rats. [ABSTRACT FROM AUTHOR]

Malaria is preventable, but the burden of disease remains high with over 249 million cases and 608,000 deaths reported in 2022. Historically, the most important protective interventions have been vector control and chemopreventive medicines with over 50 million children receiving seasonal malaria chemoprevention in the year 2023. Two vaccines are approved and starting to be deployed, bringing additional protection for children up to 36 months. However, the impact of these currently available tools is somewhat limited on various fronts. Vaccines exhibit partial efficacy, are relatively costly, and not accessible in all settings. The challenges encountered with chemoprevention are barriers to acceptability and feasibility, including frequency of dosing, and the lack of options in the first trimester of pregnancy and for women living with HIV. Also, the emergence of resistance against chemopreventive medicines is concerning. To address these limitations, a target product profile (TPP) is proposed as a road map to guide innovation and to boost the quest for novel chemopreventive alternatives. This TPP describes the ideal product attributes, while acknowledging potential trade-offs that may be needed. Critically, it considers the target populations most at risk; primarily infants, children, and pregnant women. Malaria control and elimination requires appropriate chemoprevention, not only in areas of high endemicity and transmission, but also in lower transmission areas where immunity is declining, as well as for travellers from areas where malaria has been eliminated. New medicines should show acceptable safety and tolerability, with high and long protective efficacy. Formulations and costs need to support operational adherence, access, and effectiveness. Next generation long-acting oral and injectable drugs are likely to constitute the backbone of malaria prevention. Therefore, the perspectives of front-line experts in malaria prevention, researchers, and those involved in drug development are captured in the TPP. This inclusive approach aims at concentrating efforts and aligning responses across the community to develop new and transformative medicines. [ABSTRACT FROM AUTHOR]

Vascularized lymph node transfer (VLNT) is an advanced surgical approach for secondary lymphedema (SLE) treatment, but tissue fibrosis around the lymph node flap (VLNF) inhibiting lymphangiogenesis is the biggest challenge undermining its therapeutic efficacy. This study explored the effects of periodic hyaluronidase (HLD) injection in reducing fibrosis and promoting lymphangiogenesis in 52 Sprague–Dawley rats with a VLNF over 13 weeks. The results demonstrated that HLD administration significantly enhanced swelling reduction, lymphatic drainage efficiency, and lymphatic vessel regeneration, with up to a 26% decrease in tissue fibrosis around the VLNF. These findings suggest that combining VLNT with periodic injections of HLD could substantially improve SLE treatment outcomes in clinical settings. It offers a promising direction for future therapeutic strategies and drug development aimed at increasing the efficacy of surgical treatment for SLE patients. [ABSTRACT FROM AUTHOR]