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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]

AbstractThiazole is a sulfur and nitrogen-containing five-membered heteroaromatic ring in many FDA-approved drugs and numerous experimental leads. To facilitate access to this structure, several novel methodologies have been developed using easily accessible starting materials and more environmentally friendly protocols. This review focuses on all recently developed methods (2013–2024) that utilized homogeneous or heterogeneous catalyzed methods to synthesize 1,3-thiazole and provides thorough information on the diverse therapeutic applicability of thiazole derivatives in drug discovery and development. Furthermore, this review will ameliorate the understanding of synthetic and medicinal chemists in selecting green and ecological methodologies to synthesize thiazoles judicially. [ABSTRACT FROM AUTHOR]

The discovery of biomarkers, essential for successful drug development, is often hindered by the limited availability of tissue samples, typically obtained through core needle biopsies. Standard ‘omics platforms can consume significant amounts of tissue, forcing scientist to trade off spatial context for high-plex assays, such as genome-wide assays. While bulk gene expression approaches and standard single-cell transcriptomics have been valuable in defining various molecular and cellular mechanisms, they do not retain spatial context. As such, they have limited power in resolving tissue heterogeneity and cell–cell interactions. Current spatial transcriptomics platforms offer limited transcriptome coverage and have low throughput, restricting the number of samples that can be analyzed daily or even weekly. While the Digital Spatial Profiling (DSP) method does not provide single-cell resolution, it presents a significant advancement by enabling scalable whole transcriptome and ultrahigh-plex protein analysis from distinct tissue compartments and structures using a single tissue slide. These capabilities overcome significant constraints in biomarker analysis in solid tissue specimens. These advancements in tissue profiling play a crucial role in deepening our understanding of disease biology and in identifying potential therapeutic targets and biomarkers. To enhance the use of spatial biology tools in drug discovery and development, the DSP Scientific Consortium has created best practices guidelines. These guidelines, built on digital spatial profiling data and expertise, offer a practical framework for designing spatial studies and using current and future spatial biology platforms. The aim is to improve tissue analysis in all research areas supporting drug discovery and development. [ABSTRACT FROM AUTHOR]

Transdermal drug delivery (TDD) has gained clinical approval over several decades, with extensive research dedicated to novel drug and device development. Despite notable research progress, the market adoption of TDD devices has not met anticipated levels, with oral administration and injection remaining predominant delivery methods. To maximize the potential of TDD, we identify bottlenecks hindering its widespread clinical application and propose promising research avenues. We begin by analyzing stringent demands necessary to truly benefit patients, addressing significant challenges in biomechanics, nanomedicine, and flexible electronics. Subsequently, we delve into skin anatomy, enhancement strategies, nano-carriers, and their underlining mechanisms, highlighting the importance and framework of quantitative modeling. Based on these discussions, we highlight the core strength of TDD, such as automatic precise administration based on feedback and high delivery efficiencies, especially applicable to localized conditions (e.g., central nervous system diseases, tumors). Finally, we envision the future of intelligent TDD device and its operation scenario, aiming to steer research efforts toward faster translation of laboratory innovations into widely used products for sufferers. [ABSTRACT FROM AUTHOR]

Safety and effectiveness are the two ends of the balance in drug development that needs to be evaluated. The biotransformation of drugs within a living organism could potentiate biochemical insults in the tissue and compromise the safety of drugs. Nitrofurantoin (NFT) is a cheap clinical antibiotic with a wide array of activities against gram-positive and gram-negative organisms. The NFT scaffold has been utilized to develop other derivates or analogues in the quest to repurpose drugs against other infectious diseases. Several techniques were developed over the years to study the mechanism of NFT metabolism and toxicity, such as voltammetry, chromatographic analysis, protein precipitation, liquid-liquid extraction, etc. Due to limitations in these methods, the mechanism of NFT biotransformation in the cell is poorly understood. Metabolomics has been adopted in drug metabolism to understand the mechanism of drug toxicity and could provide a solution to overcome the limitations of current techniques to determine mechanisms of toxicity. Unfortunately, little or no information regarding the metabolomics approach in NFT metabolism and toxicity is available. Hence, this review highlights the metabolomic techniques that can be adopted in NFT metabolism and toxicological studies to encourage the research community to widely adopt and utilize metabolomics in understanding NFT's metabolism and toxicity. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effects of Tarantula cubensis alcohol extract (TCAE, Theranekron) and Sorafenib (S) treatments on carcinogenesis, apoptosis and biochemical profile of rats with experimentally induced hepatocellular carcinoma (HCC). In the presented study, 58 male rats were divided into 7 groups; Negative Control (NC, n = 6), NC + TCAE (NCT, n = 6), NC + Sorafenib (NCS, n = 6), Positive Control (PC, n = 10), Positive Control + TCAE (PCT, n = 10), Positive Control + Sorafenib (PCS, n = 10), Positive Control + TCAE + Sorafenib (PCTS, n = 10). The active ingredients Diethylnitrosamine (DEN, 120 mg/kg, single dose) and Nitrosomorpholine (NMOR, 50 ppm, 21 weeks orally) were used to induce HCC in rats. At the end of the experiment, the animals were euthanized under appropriate conditions and samples were collected for biochemical and pathological investigations. In the PC group, alanine aminotransferase (ALT), aspartate aminotransferase (AST) and gamma-glutamyl transpeptidase (GGT) levels were higher (p < 0.001) and urea levels were lower (p < 0.001) compared to all other groups. Treatment groups reorganized the relevant markers (ALT, AST, GGT, and urea). A significant increase was detected in Caspase-10, Caspase-3 and Granzyme-B (GrzB) (p < 0.001) in blood and Caspase-10 and GrzB (p < 0.05) in liver tissue in PCT, PCS and PCTS groups compared to the PC group. Histopathological examination revealed that the PC group showed cancer morphology, and the treatment groups caused a decrease in tumor incidence and size. Our current findings suggest that the mechanism of action of TCAE in HCC is through the NKs/CTLs-GrzB-Casp10-Casp3 signaling pathway and can be used in combination with chemotherapy drugs for the development of future drug designs. [ABSTRACT FROM AUTHOR]

Two series of vanillin derivatives containing 1,3,4-oxadiazole and 1,3-thiazolidin-4-one scaffolds were prepared and evaluated for their antifungal activity. The results revealed that compounds 6j (29.73 μg/ml) and 7a (38.15 μg/ml) displayed excellent inhibitory activity against the spore of Fusarium solani. The inhibitory activity of compound 7d (10.53 μg/ml) against the spore of Alternaria solani was more than 42-fold that of vanillin. Compound 7a (37.54 μg/ml) showed better antifungal activity against the spore of B. cinerea than positive controls. The cytotoxicity assay confirmed that compounds 6k, 7a, and 7d showed good selectivity and less toxicity to normal mammalian cells. [ABSTRACT FROM AUTHOR]

Introduction: Idiopathic pulmonary fibrosis (IPF) is a progressive-fibrosing lung disease with a median survival of less than 5 years. Currently, two agents, pirfenidone and nintedanib are approved for this disease, and both have been shown to reduce the rate of decline in lung function in patients with IPF. However, both have significant adverse effects and neither completely arrest the decline in lung function. Areas covered: Thirty experimental agents with unique mechanisms of action that are being evaluated for the treatment of IPF are discussed. These agents work through various mechanisms of action, these include inhibition of transcription nuclear factor k-B on fibroblasts, reduced expression of metalloproteinase 7, the generation of more lysophosphatidic acids, blocking the effects of transforming growth factor ß, and reducing reactive oxygen species as examples of some unique mechanisms of action of these agents. Expert opinion: New drug development has the potential to expand the treatment options available in the treatment of IPF patients. It is expected that the adverse drug effect profiles will be more favorable than current agents. It is further anticipated that these new agents or combinations of agents will arrest the fibrosis, not just slow the fibrotic process. [ABSTRACT FROM AUTHOR]

Dose optimization is a critical challenge in drug development. Historically, dose determination in oncology has followed a divergent path from other non-oncology therapeutic areas due to the unique characteristics and requirements in Oncology. However, with the emergence of new drug modalities and mechanisms of drugs in oncology, such as immune therapies, radiopharmaceuticals, targeted therapies, cytostatic agents, and others, the dose-response relationship for efficacy and toxicity could be vastly varied compared to the cytotoxic chemotherapies. The doses below the MTD may demonstrate similar efficacy to the MTD with an improved tolerability profile, resembling what is commonly observed in non-oncology treatments. Hence, alternate strategies for dose optimization are required for new modalities in oncology drug development. This paper delves into the historical evolution of dose finding methods from non-oncology to oncology, highlighting examples and summarizing the underlying drivers of change. Subsequently, a practical framework and guidance are provided to illustrate how dose optimization can be incorporated into various stages of the development program. We provide the following general recommendations: 1) The objective for phase I is to identify a dose range rather than a single MTD dose for subsequent development to better characterize the safety and tolerability profile within the dose range. 2) At least two doses separable by PK are recommended for dose optimization in phase II. 3) Ideally, dose optimization should be performed before launching the confirmatory study. Nevertheless, innovative designs such as seamless II/III design can be implemented for dose selection and may accelerate the drug development program. [ABSTRACT FROM AUTHOR]

Abstract\nHIGHLIGHTSCardiovascular diseases (CVDs) cause 30% of deaths each year, and in 2030, around 23.6 million people will die due to CVDs. The major challenge is to obtain molecules with minimal adverse reactions that can prevent and dissolve blood clots. In this context, fibrinolytic enzymes from diverse microorganism sources have been extensively investigated due to their potential to act directly and specifically on the fibrin clot, preventing side effects and performing potential thrombolytic effects. However, most researches focus on the purification and characterization of proteases, with little emphasis on the mechanism of action and pharmacological characteristics, including toxicity assays which are essential to assess safety and side effects. Therefore, this work aims to emphasize the importance of evaluations indicating the toxicological profile of fibrinolytic proteases through in vitro and in vivo tests. Both types of assays contribute as preclinical stage in drug development and are crucial for clinical applications. This scarcity creates arbitrary barriers to further studies. This work should further encourage the development of studies to ensure the safety and effectivity of fibrinolytic proteases.Suggested pre-clinical trials aim to validate more specific methods for fibrinolytic enzymes;Current toxicity standards can be adapted to better assess the profile of fibrinolytic enzymes;The class of fibrinolytic enzymes must be carefully evaluated according to the method of application.Suggested pre-clinical trials aim to validate more specific methods for fibrinolytic enzymes;Current toxicity standards can be adapted to better assess the profile of fibrinolytic enzymes;The class of fibrinolytic enzymes must be carefully evaluated according to the method of application. [ABSTRACT FROM AUTHOR]

The phage display technology is based on the presentation of peptide sequences on the surface of virions of bacteriophages. Its development led to creation of sophisticated systems based on the possibility of the presentation of a huge variability of peptides, attached to one of proteins of bacteriophage capsids. The use of such systems allowed for achieving enormous advantages in the processes of selection of bioactive molecules. In fact, the phage display technology has been employed in numerous fields of biotechnology, as diverse as immunological and biomedical applications (in both diagnostics and therapy), the formation of novel materials, and many others. In this paper, contrary to many other review articles which were focussed on either specific display systems or the use of phage display in selected fields, we present a comprehensive overview of various possibilities of applications of this technology. We discuss an usefulness of the phage display technology in various fields of science, medicine and the broad sense of biotechnology. This overview indicates the spread and importance of applications of microbial systems (exemplified by the phage display technology), pointing to the possibility of developing such sophisticated tools when advanced molecular methods are used in microbiological studies, accompanied with understanding of details of structures and functions of microbial entities (bacteriophages in this case). [ABSTRACT FROM AUTHOR]

There are good reasons to perform a randomized controlled trial (RCT) even in early phases of clinical development. However, the low sample sizes in those settings lead to high variability of the treatment effect estimate. The variability could be reduced by adding external control data if available. For the common setting of suitable subject-level control group data only available from one external (clinical trial or real-world) data source, we evaluate different analysis options for estimating the treatment effect via hazard ratios. The impact of the external control data is usually guided by the level of similarity with the current RCT data. Such level of similarity can be determined via outcome and/or baseline covariate data comparisons. We provide an overview over existing methods, propose a novel option for a combined assessment of outcome and baseline data, and compare a selected set of approaches in a simulation study under varying assumptions regarding observable and unobservable confounder distributions using a time-to-event model. Our various simulation scenarios also reflect the differences between external clinical trial and real-world data. Data combinations via simple outcome-based borrowing or simple propensity score weighting with baseline covariate data are not recommended. Analysis options which conflate outcome and baseline covariate data perform best in our simulation study. [ABSTRACT FROM AUTHOR]

Introduction: The treatment landscape of polycythemia vera (PV) has seen major advancements within the last decade including approval of ruxolitinib in the second line setting after hydroxyurea, ropegylated interferon-α2b, and advanced clinical development of a novel class of agents called hepcidin mimetics. Areas covered: We provide a comprehensive review of the evidence discussing the risk stratification, treatment indications, role and limitations of phlebotomy only approach and pivotal trials covering nuances related to the use of interferon-α (IFN-α), ruxolitinib, hepcidin mimetics, and upcoming investigational agents including HDAC and LSD1 inhibitors. Expert opinion: The research paradigm in PV is slowly shifting from the sole focus on hematocrit control and moving toward disease modification. The discovery of hepcidin mimetics has come as a breakthrough in restoring iron homeostasis, achieving phlebotomy-independence and may lead to improved thrombosis-free survival with stricter hematocrit control. On the other hand, emerging data with IFN- α and ruxolitinib as well as combination of the two agents suggests the potential for achieving molecular remission in a subset of PV patients and long-term follow-up is awaited to validate the correlation of molecular responses with clinically relevant outcomes of progression-free and thrombosis-free survival. [ABSTRACT FROM AUTHOR]

AbstractEnzyme-mediated pharmacokinetic drug-drug interactions can be caused by altered activity of drug metabolizing enzymes in the presence of a perpetrator drug, mostly via inhibition or induction. We identified a gap in the literature for a state-of-the art detailed overview assessing this type of DDI risk in the context of drug development. This manuscript discusses in vitro and in vivo methodologies employed during the drug discovery and development process to predict clinical enzyme-mediated DDIs, including the determination of clearance pathways, metabolic enzyme contribution, and the mechanisms and kinetics of enzyme inhibition and induction. We discuss regulatory guidance and highlight the utility of in silico physiologically-based pharmacokinetic modeling, an approach that continues to gain application and traction in support of regulatory filings. Looking to the future, we consider DDI risk assessment for targeted protein degraders, an emerging small molecule modality, which does not have recommended guidelines for DDI evaluation. Our goal in writing this report was to provide early-career researchers with a comprehensive view of the enzyme-mediated pharmacokinetic DDI landscape to aid their drug development efforts. [ABSTRACT FROM AUTHOR]

AbstractAberrant metabolism of purines and pyrimidines led to development of drugs for treatment of various diseases, such as inflammatory, neurological, cardiovascular, viral infections and cancer. Purine and Pyrimidine Symposia are characterized by close interactions, leading to extensive cross-fertilization on methodology and translating not only from bench-to-bedside, but also between various disciplines such as medicinal chemistry, pharmacology, oncology, virology, rheumatology, biochemistry, pediatrics, cardiology, surgery and immunology. This background was fundamental in our studies on how to optimize application of existing drugs (5-fluorouracil [5FU], thiopurines, antifolates such as methotrexate) but also to support development of novel drugs such as gemcitabine, novel antifolates, S-1, TAS-102 and fluorocyclopentenylcytosine. Knowledge of their metabolism helped to design rational combinations such as of gemcitabine with cisplatin, one of the most widely used drug combinations for various cancers. The combination of 5FU with uridine, led to the development of triacetyluridine registered for emergency treatment of patients with lethal 5FU toxicity. Mechanisms of action were studied by careful analysis of their metabolism, using classical enzyme assays with radioactive precursors and HPLC analysis. Drug metabolism moved from manually operated HPLC systems with UV-detection for peak identification and paper rolls for quantification, to computer-operated HPLC with automatic multi-wavelength and fluorometric peak detection and more recently to ultrasensitive, highly specific mass-spectrometry-based systems. Some aspects, however, never changed; careful analysis of the results and being prepared for the unexpected. The latter actually led to the most interesting results. Investigation of (nucleoside/nucleotide) metabolism remains an exciting field of research. [ABSTRACT FROM AUTHOR]

Dose selection and optimization in early phase of oncology drug development serves as the foundation for the success of late phases drug development. Bivariate Bayesian logistic regression model (BLRM) is a widely utilized model-based algorithm that has been shown to improve the accuracy for identifying recommended phase 2 dose (RP2D) based on dose-limiting-toxicity (DLT) over traditional method such as 3 + 3. However, it remains a challenge to optimize dose selection that strikes a proper balance between safety and efficacy in escalation and expansion phase of phase I trials. In this paper, we first use a phase I clinical trial to demonstrate how the variability of drug exposure related to pharmacokinetic (PK) parameters among trial participants may add to the difficulties of identifying optimal dose. We use simulation to show that concurrently or retrospectively fitting BLRM model for dose/toxicity data from escalation phase with dose-independent PK parameters as covariate lead to improved accuracy of identifying dose level at which DLT rate is within a prespecified toxicity interval. Furthermore, we proposed both model- and rule-based methods to modify dose at patient level in expansion cohorts based on their PK/exposure parameters. Simulation studies show this approach leads to higher likelihood for a dose level with a manageable toxicity and desirable efficacy margin to be advanced to late phase pipeline after being screened at expansion phase of phase I trial. [ABSTRACT FROM AUTHOR]

AbstractClinical trials are an essential component of the drug development process, providing crucial data on the efficacy and safety of new treatments. However, traditional clinical trial designs can be inefficient and ineffective, leading to increased costs and a higher risk of failure. The FDA Oncology Center of Excellence (OCE) has recently initiated Project Optimus to reform the dose selection paradigm for oncology treatments. We propose the adaptive seamless phase II/III clinical trial designs (ASD) with the sequential estimation-adjusted urn (SEU) model for randomization to achieve efficient and ethical objectives. However, the combination of ASD and SEU poses a challenge in controlling the type I error rate: ASD exerts a dual influence of multiplicity and selection; all the responses and treatment assignments are not independent due to SEU. In this paper, we investigated how to overcome these difficulties, utilize the two adaptive approaches’ advantages, and control the type I error rate. We provide a theoretical foundation for this procedure, and numerical studies demonstrate that our methods can assign more people to better treatments, leading to fewer failures while still controlling the type I error rate and preserving power. [ABSTRACT FROM AUTHOR]

AbstractRecombinant human acidic fibroblast growth factor (rh-aFGF) is a widely used biological product, but it is unstable and its biological activity is easy to decrease. In order to maintain the long-term stability and biological activity of rh-aFGF, based on the response surface method, the freeze-drying characterization and cell proliferation rate of rh-aFGF freeze-dried powder were evaluated by scoring and Methylthiazolyldiphenyl-tetrazolium bromide (MTT) assay in this study. The optimal concentrations of trehalose, glycine and BSA were optimized, and the optimal formulation was verified by regression experiment. The results showed that trehalose, glycine and BSA had significant effects on the characterization of lyophilized rh-aFGF and cell proliferation. The optimal formulation of 5.7% trehalose, 2.04% glycine and 1.98%BSA combined with rh-aFGF could achieve the optimal freeze-dried characterization and biological activity. Using the best formulation to verify, the freeze-dried formability index of the freeze-dried powder was 23.35, and the rate of cell proliferation was 43.59%, which was close to the expected 23 and 41.69%. This study determined a freeze-dried formulation of rh-aFGF that meets the requirements of freeze-dried formalization integrity and maintains biological activity, providing reliable support for the subsequent development of related drugs. [ABSTRACT FROM AUTHOR]

By describing the absorption, distribution, metabolism, and excretion of drugs, pharmacokinetics helps to find optimal therapies for patients and speed up drug development. In pharmacokinetics, dynamic uncertainties, such as fluctuations in hormone levels and external environment factors, are ubiquitous. Due to sparse clinical data and patient disease specificity, these uncertainties are mainly epistemic uncertainties rather than aleatory uncertainties, which cannot be handled well by probability theory based methods. Therefore, several pharmacokinetics based on uncertain differential equations under the framework of uncertainty theory were investigated, which all considered one compartment models. Noting that many drugs follow two compartment kinetics, this article proposes a two compartment pharmacokinetic model based on uncertain differential equations. Based on the proposed model, several essential pharmacokinetic parameters are investigated, which are important information required by regulatory bodies to approve drugs for public use. Estimation for unknown parameters in the model are given. Finally, a real data analysis using lidocaine drug concentration illustrates our methodology in details. [ABSTRACT FROM AUTHOR]

AbstractThis review, part of a special issue on drug-drug interactions (DDIs) spearheaded by the International Society for the Study of Xenobiotics (ISSX) New Investigators, explores the critical role of drug transporters in absorption, disposition, and clearance in the context of DDIs. Over the past two decades, significant advances have been made in understanding the clinical relevance of these transporters. Current knowledge on key uptake and efflux transporters that affect drug disposition and development is summarized. Regulatory guidelines from the FDA, EMA, and PMDA that inform the evaluation of potential transporter-mediated DDIs are discussed in detail. Methodologies for preclinical and clinical testing to assess potential DDIs are reviewed, with an emphasis on the utility of physiologically based pharmacokinetic (PBPK) modeling. This includes the application of relative abundance and expression factors to predict human pharmacokinetics (PK) using preclinical data, integrating the latest regulatory guidelines. Considerations for assessing transporter-mediated DDIs in special populations, including pediatric, hepatic, and renal impairment groups, are provided. Additionally, the impact of transporters at the blood-brain barrier (BBB) on the disposition of CNS-related drugs is explored. Enhancing the understanding of drug transporters and their role in drug disposition and toxicity can improve efficacy and reduce adverse effects. Continued research is essential to bridge remaining gaps in knowledge, particularly in comparison with cytochrome P450 (CYP) enzymes. [ABSTRACT FROM AUTHOR]

As part of the drug development process, interim analysis is frequently used to design efficient phase II clinical trials. A stochastic curtailment framework is often deployed wherein a decision to continue or curtail the trial is taken at each interim look based on the likelihood of observing a positive or negative treatment effect if the trial were to continue to its anticipated end. Thus, curtailment can take place due to evidence of early efficacy or futility. Traditionally, in the case of time-to-event endpoints, interim monitoring is conducted in a two-arm clinical trial using the log-rank test, often with the assumption of proportional hazards. However, when this is violated, the log-rank test may not be appropriate, resulting in loss of power and subsequently inaccurate sample sizes. In this paper, we propose stochastic curtailment methods for two-arm phase II trial with the flexibility to allow non-proportional hazards. The proposed methods are built utilizing the concept of relative time assuming that the survival times in the two treatment arms follow two different Weibull distributions. Three methods – conditional power, predictive power and Bayesian predictive probability – are discussed along with corresponding sample size calculations. The monitoring strategy is discussed with a real-life example. [ABSTRACT FROM AUTHOR]

AbstractAdvances in the field of bioactivation have significantly contributed to our understanding and prediction of drug-induced liver injury (DILI). It has been established that many adverse drug reactions, including DILI, are associated with the formation and reactivity of metabolites. Modern methods allow us to detect and characterize these reactive metabolites in earlier stages of drug development, which helps anticipate and circumvent the potential for DILI. Improved in silico models and experimental techniques that better reflect in vivo environments are enhancing predictive capabilities for DILI risk. Further, studies on the mechanisms of bioactivation, including enzyme interactions and the role of individual genetic differences, have provided valuable insights for drug optimizations. Cumulatively, this progress is continually refining our approaches to drug safety evaluation and personalized medicine. [ABSTRACT FROM AUTHOR]

The selection of appropriate starting dose and suitable method to predict an efficacious dose for novel oncology drug in the early clinical development stage poses significant challenges. The traditional methods of using body surface area transformation from toxicology studies to predict the first-in human (FIH) starting dose, or simply selecting the maximum tolerated dose (MTD) or maximum administered dose (MAD) as efficacious dose or recommended phase 2 dose (RP2D), are usually inadequate and risky for novel oncology drugs. Due to the regulatory efforts aimed at improving dose optimisation in oncology drug development, clinical dose selection is now shifting away from these traditional methods towards a comprehensive benefit/risk assessment-based approach. Quantitative pharmacology analysis (QPA) plays a crucial role in this new paradigm. This mini-review summarises the use of QPA in selecting the starting dose for oncology FIH studies and potential efficacious doses for expansion or phase 2 trials. QPA allows for a more rational and scientifically based approach to dose selection by integrating information across studies and development phases. In conclusion, the application of QPA in oncology drug development has the potential to significantly enhance the success rates of clinical trials and ultimately support clinical decision-making, particularly in dose selection. [ABSTRACT FROM AUTHOR]

The intranasal (IN) route of administration is important for topical drugs and drugs intended to act systemically. More recently, direct nose-to-brain input was considered to bypass the blood-brain barrier. Processes related to IN absorption and nose-to-brain distribution are complex and depend, sometimes in contrasting ways, on chemico-physical and structural parameters of the compounds, and on formulation options. Due to the intricacies of these processes and despite the large number of articles published on many different IN compounds, it appears that absorption after IN dosing is not yet fully understood. In particular, at variance of the understanding and modelling approaches that are available for predicting the pharmacokinetics (PK) following oral administration of xenobiotics, it appears that there is not a similar understanding of the chemico-physical and structural determinants influencing drug absorption and disposition of compounds after IN administration, which represents a missed opportunity for this research field. This is even more true regarding the understanding of the direct nose-to-brain input. Due to this, IN administrations may represent an interesting and open research field for scientists aiming to develop PK property predictions tools, mechanistic PK models describing rate and extent of IN absorption, and translational tools to anticipate the clinical PK following IN dosing based on in vitro and in vivo non clinical experiments. This review intends to provide: i) some basic knowledge related to the physiology of PK after IN dosing, ii) a non-exhaustive list of preclinical and clinical examples related to compounds explored for the potential nose-to-blood and nose-to-brain passage, and iii) the identification of some areas requiring improvements, the understanding of which may facilitate the development of IN drug candidates. [ABSTRACT FROM AUTHOR]

Drug-induced liver injury (DILI) is a major cause of drug development discontinuation and drug withdrawal from the market, but there are no golden standard methods for DILI risk evaluation. Since we had found the association between DILI and CYP1A1 or CYP1B1 inhibition, we further evaluated the utility of cytochrome P450 (P450) inhibition assay data for DILI risk evaluation using decision tree analysis. The inhibitory activity of drugs with DILI concern (DILI drugs) and no DILI concern (no-DILI drugs) against 10 human P450s was assessed using recombinant enzymes and luminescent substrates. The drugs were also subjected to cytotoxicity assays and high-content analysis using HepG2 cells. Molecular descriptors were calculated by alvaDesc. Decision tree analysis was performed with the data obtained as variables with or without P450-inhibitory activity to discriminate between DILI drugs and no-DILI drugs. The accuracy was significantly higher when P450-inhibitory activity was included. After the decision tree discrimination, the drugs were further discriminated with the P450-inhibitory activity. The results demonstrated that many false-positive and false-negative drugs were correctly discriminated by using the P450 inhibition data. These results suggest that P450 inhibition assay data are useful for DILI risk evaluation. [ABSTRACT FROM AUTHOR]

The analysis of pharmacokinetic data has been in a constant state of evolution since the introduction of the term pharmacokinetics. Early work focused on mechanistic understanding of the absorption, distribution, metabolism and excretion of drug products. The introduction of non-linear mixed effects models to perform population pharmacokinetic analysis initiated a paradigm shift. The application of these models represented a major shift in evaluating variability in pharmacokinetic parameters across a population of subjects. While technological advancements in computing power have fueled the growth of population pharmacokinetics in drug development efforts, there remain many challenges in reducing the time required to incorporate these learnings into a model-informed development process. These challenges exist because of expanding datasets, increased number of diagnostics, and more complex mathematical models. New machine learning tools may be potential solutions for these challenges. These new methodologies include genetic algorithms for model selection, machine learning algorithms for covariate selection, and deep learning models for pharmacokinetic and pharmacodynamic data. These new methods promise the potential for less bias, faster analysis times, and the ability to integrate more data. While questions remain regarding the ability of these models to extrapolate accurately, continued research in this area is expected to address these questions. [ABSTRACT FROM AUTHOR]

Biological macromolecules, encompassing proteins, nucleic acids, lipids, and carbohydrates, have garnered increasing attention as tethering excipients within the realms of pharmaceuticals and biotechnology. This concise appraisal offers a comprehensive overview of their multifaceted role, highlighting the latest advancements in their applications. Biological macromolecules, long regarded as fundamental components of life, have transitioned into pivotal agents that contribute significantly to drug development, drug formulation stability and the optimization of pharmacokinetic profiles. This review delineates how these macromolecules serve as integral players in the enhancement of drug delivery systems, enabling controlled release, targeted delivery, and improved bioavailability. Furthermore, they play a critical role in the stabilization of sensitive compounds, preserving their efficacy and extending their shelf life. Additionally, the interactions between macromolecules and therapeutic agents are pivotal in mitigating issues of solubility and bioavailability, further propelling their utility as excipients. Despite these promising attributes, challenges such as immunogenicity, scalability, and regulatory compliance persist. Navigating these hurdles necessitates a concerted effort from researchers, engineers, and regulatory bodies alike. In conclusion, biological macromolecules stand as formidable contenders in the field of tethering excipients. Their versatile applications in drug delivery, formulation stability, and pharmacokinetic enhancement hold the promise of revolutionizing the pharmaceutical and biotechnological landscapes. To realize this potential fully, the scientific community must continue to probe their intricacies, address challenges proactively, and foster collaborative efforts to ensure their seamless integration into the future of healthcare and therapeutics. Ultimately, the enduring impact of biological macromolecules on patient care is poised to be transformative and far-reaching. [ABSTRACT FROM AUTHOR]

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]

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]

Natural products have provided abundant sources of lead compounds for new drug discovery and development over the past centuries. Curcumin is a lipophilic polyphenol isolated from turmeric, a plant used in traditional Asian medicine for centuries. Despite the low oral bioavailability, curcumin exhibits profound medicinal value in various diseases, especially liver and gut diseases, bringing an interest in the paradox of its low bioavailability but high bioactivity. Several latest studies suggest that curcumin's health benefits may rely on its positive gastrointestinal effects rather than its poor bioavailability solely. Microbial antigens, metabolites, and bile acids regulate metabolism and immune responses in the intestine and liver, suggesting the possibility that the liver-gut axis bidirectional crosstalk controls gastrointestinal health and diseases. Accordingly, these pieces of evidence have evoked great interest in the curcumin-mediated crosstalk among liver-gut system diseases. The present study discussed the beneficial effects of curcumin against common liver and gut diseases and explored the underlying molecular targets, as well as collected evidence from human clinical studies. Moreover, this study summarized the roles of curcumin in complex metabolic interactions in liver and intestine diseases supporting the application of curcumin in the liver-gut system as a potential therapeutic option, which opens an avenue for clinical use in the future. [ABSTRACT FROM AUTHOR]

AbstractA multiregional clinical trial is a clinical trial conducted simultaneously in multiple regions under a single protocol. It is a new drug development strategy that has advantages in many ways. A significant part of these advantages comes from the hierarchical data structure of the multiregional clinical trials. Based on the recent work of Kim and Kang (2020) concerning hierarchical linear models to better reflect the structure, we address the problem of controlling the Frequentist type I error rate when the number of regions is small using a Bayesian method. More precisely, we present a strategy for controlling the type I error rate by setting a prespecified Bayesian credible level. Simulation results show that our proposed method controls the type I error rate reliably and well. Through sensitivity analysis, we also investigate the effect on the results when accurate information on between-region variability is given and when several different types of prior distributions are used. [ABSTRACT FROM AUTHOR]

AbstractIt is well-known that the hepatotoxicity of drugs can significantly influence their clinical use. Despite their effective therapeutic efficacy, many drugs are severely limited in clinical applications due to significant hepatotoxicity. In response, researchers have created several machine learning-based hepatotoxicity prediction models for use in drug discovery and development. Researchers aim to predict the potential hepatotoxicity of drugs to enhance their utility. However, current hepatotoxicity prediction models often suffer from being unverified, and they fail to capture the detailed toxicological structures of predicted hepatotoxic compounds. Using the 56 chemical constituents of Gardenia jasminoides as examples, we validated the trained hepatotoxicity prediction model through literature reviews, principal component analysis (PCA), and structural comparison methods. Ultimately, we successfully developed a model with strong predictive performance and conducted visual validation. Interestingly, we discovered that the predicted hepatotoxic chemical constituents of Gardenia possess both toxic and therapeutic effects, which are likely dose-dependent. This discovery greatly contributes to our understanding of the dual nature of drug-induced hepatotoxicity. [ABSTRACT FROM AUTHOR]

AbstractClinical trials are an essential aspect of the drug development process. Clinical endpoints and surrogate endpoints are two terms used in clinical trials to measure the effectiveness of a treatment. While clinical endpoints typically require higher costs and longer durations of observation to show direct clinical benefits, surrogate endpoints have been introduced as a cheaper and faster method that may be used to predict clinical effects. When there is a linear relationship between the surrogate and the clinical endpoint, the surrogate may still need to rule out a threshold that corresponds to no clinical benefit. The determination of such a threshold uses the knowledge of numerous parameters in the bivariate statistical distribution of the clinical response and the surrogate. In our work, we present a concept of “working” threshold to incorporate statistical uncertainties in determination of such a threshold. [ABSTRACT FROM AUTHOR]

There is an urgent, persistent, need for better biomarkers in clinical drug development. More informative biomarkers can increase the likelihood of drug advancement or approval, and implementing biomarkers increases the success rate in drug development. Biomarkers may guide decisions and allow resources to be directed to the projects most likely to succeed. However, biomarkers that are validated to high standards are needed, reflecting biological and pathological processes accurately. Such biomarkers are needed to develop treatments faster, and to improve and guide clinical trial design by selecting and de-selecting patients. In this review based on the authors' previous published experience and interaction with pharmaceutical- and biomarker stakeholders, we highlight the use and value of biomarkers in clinical development according to the BEST guidelines. We highlight the value of 3 types of biomarkers that may provide optimal value to stakeholders: diagnostic, prognostic and pharmacodynamic biomarkers. A more appropriate clinical trial design, increasing the ratio between benefits and side effects, may come from a more tailored biomarker-approach identifying suitable molecular endotypes of patients to treat. Biomarkers may guide drug developers in selecting the optimal projects to progress, when designing clinical studies and development paths. Biomarkers may aid in the diagnosis and prognostic assessment of patients and assist in matching the molecular endotype to the selected treatment, which improves the success rate of clinical development progression. The aim of this paper is to provide a comprehensive ideation framework for how to utilize biomarkers in clinical development, with a focus on utility for patients, payers and drug developers. [ABSTRACT FROM AUTHOR]

The prevalence of various kidney diseases has become a significant threat to global public health and one of the leading causes of severe morbidity and high mortality. Multiple extrinsic or intrinsic factors, including drug or chemotoxicity, aging biomarkers, and various aging-related disorders, may exacerbate multiple kidney diseases and subsequently lead to end-stage renal disease (ESRD). In addition, the complications of kidney pathologies further pose challenges to current clinical practices. However, amid the development of various novel therapeutic approaches against kidney diseases, the interest in natural products or nutraceutical-based treatments has been growing and active in research on renal disorders. Amongst these, luteolin-a flavone, has been shown to be potent in combatting kidney disorders by effectively preventing and ameliorating the progression of various kidney biomarkers and associated pathologies. Therefore, this systemic review assimilates the evidence of numerous in-vitro and in-vivo studies along with the progress in luteolin-based drug development to enlighten its pharmacological potency in treating kidney disorders. The existing reports strongly support the promising therapeutic benefits of luteolin and thus, the review suggests conducting clinical studies to establish it as a potent therapeutic agent against kidney diseases. [ABSTRACT FROM AUTHOR]

The MCS initiative was first introduced in 2013. Since then, two MCS papers have been published: the first proposing a structured approach to consider the impact of drug substance physical properties on manufacturability and the second outlining real world examples of MCS principles. By 2023, both publications had been extensively cited by over 240 publications. This article firstly reviews this citing work and considers how the MCS concepts have been received and are being applied. Secondly, we will extend the MCS framework to continuous manufacture. The review structure follows the flow of drug product development focussing first on optimisation of API properties. The exploitation of links between API particle properties and manufacturability using large datasets seems particularly promising. Subsequently, applications of the MCS for formulation design include a detailed look at the impact of percolation threshold, the role of excipients and how other classification systems can be of assistance. The final review section focusses on manufacturing process development, covering the impact of strain rate sensitivity and modelling applications. The second part of the paper focuses on continuous processing proposing a parallel MCS framework alongside the existing batch manufacturing guidance. Specifically, we propose that continuous direct compression can accommodate a wider range of API properties compared to its batch equivalent. [ABSTRACT FROM AUTHOR]

Snakebites envenoming are a global public health problem that largely affects economically vulnerable populations. The primary recognized treatment involves hyperimmune serum, consisting of sterile and heterologous immunoglobulin solutions targeting specific antigens. One established production method in Vital Brazil Institute involves antibody digestion by pepsin, fractionation with ammonium sulfate salt, and thermocoagulation, yielding 30-40% and requiring a 5-day duration. This study aims to assess a novel production method centered on recovering the (Fab')2 fraction using caprylic acid, intending to implement a more efficient technological process. A new methodology was developed, defining digestion conditions (37 °C, pH 3.2; 2.5 g L-1 of pepsin over 120 minutes at 150 rpm) and fractionation parameters (37 °C, pH 5.8; 2% caprylic acid over 60 minutes at 250 rpm). These conditions were established through the application of Quality by Design, supported by a critical risk analysis. This method reduced the usage of raw materials, process time, and labor cost per hour while maintaining yield with greater purity. These modifications were promising, resulting in higher purity and lower manufacturing costs, thereby expanding the prospect of achieving a more robust production process with a safer, optimized product. This allows meeting production goals and exploring new opportunities in foreign markets. [ABSTRACT FROM AUTHOR]

Selecting a safe and clinically beneficial dose can be difficult in drug development. Dose justification often relies on dose-response modeling where parametric assumptions are made in advance which may not adequately fit the data. This is especially problematic in longitudinal dose-response models, where additional parametric assumptions must be made. This paper proposes a class of longitudinal dose-response models to be used in the Bayesian model averaging paradigm which improve trial operating characteristics while maintaining flexibility a priori. A new longitudinal model for non-monotonic longitudinal profiles is proposed. The benefits and trade-offs of the proposed approach are demonstrated through a case study and simulation. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a complex, neurodegenerative disorder in which alterations in structural, physiological, and metabolic parameters act synergistically. Over the last decade there has been a considerable focus on developing drugs to slow the progression of the disease. Despite this, only four disease-modifying therapies are approved in North America. Although additional research is required for a thorough understanding of ALS, we have accumulated a large amount of knowledge that could be better integrated into future clinical trials to accelerate drug development and provide patients with improved treatment options. It is likely that future, successful ALS treatments will take a multi-pronged therapeutic approach, targeting different pathways, akin to personalized medicine in oncology. In this review, we discuss the link between ALS pathophysiology and treatments, looking at the therapeutic failures as learning opportunities that can help us refine and optimize drug development. [ABSTRACT FROM AUTHOR]

Arthrospira/Limnospira is a popular botanical dietary supplement throughout the world and has been consumed as a food product for hundreds of years. Ongoing efforts from our research group are focused on evaluating the utility of a Limnospira-derived oral supplement (Immulina) in promoting resilience against influenza viral infection. Like other botanical extracts, Immulina is inherently a complex matrix with variation in the levels of its chemical constituents. Therefore, to ensure therapeutic consistency for future scientific research and clinical studies, we are developing standardization technology using a bioassay and chemical markers. Braun-type lipoproteins, a class of macromolecules that activate the Toll-like receptor (TLR)2/TLR1 signaling pathway, have been identified as a major active component within Immulina. Based on the mechanism of action of the Braun-type lipoproteins, an in vitro bioassay was established using the HEK-Blue hTLR2/TLR1 cell line to quantitate the immune-enhancing potency of Immulina. The objective of the current research was to validate that bioassay for Immulina activity quantification using the U.S. FDA guidance document for botanical drug development and U.S. Pharmacopeia recommendations. System suitability, reference standards and defining potency units were established. Validation of performance parameters included precision, specificity, accuracy, linearity, and range. Validating this bioassay for Immulina activity provides a tool for ensuring product consistency and quantifying the potency of this botanical for use in future research as well as material in the consumer market. [ABSTRACT FROM AUTHOR]

Morinda officinalis is a traditional Chinese tonic herb, and have been used in the treatment of multiple diseases. Here, three iridoid glycosides isolated from M. officinalis were evaluated for their roles in the autophagy-lysosomal pathway. All three iridoid glycosides could induce TFEB/TFE3-mediated lysosomal biogenesis and trigger autophagy. Interestingly, they promoted the nuclear import of TFEB/TFE3 without affecting their nuclear export, suggesting their role in the maintenance of lysosomal homeostasis. The results from this study shed light on the identification of autophagy activators from M. officinalis and provide a basis for developing them in the treatment of oxidative stress-involved diseases. [ABSTRACT FROM AUTHOR]

Pruritus, particularly in its chronic form, often imposes significant suffering and reductions in patients' quality of life. The pathophysiology of itch is varied depending on disease context, creating opportunities for unique drug development and multimodal therapy. The purpose of this article is to provide an update of the literature regarding current and emerging therapeutics in itch. We review the multitudes of drug targets available and corresponding drugs that have shown efficacy in clinical trials, with a particular emphasis on phase 2 and 3 trials and beyond. Broadly, these targets include therapies directed against type 2 inflammation (i.e. Th2 cytokines, JAK/STAT, lipid mediators, T-cell mediators, and other enzymes and receptors) and neural receptors and targets (i.e. PARs, TRP channels, opioid receptors, MRGPRs, GABA receptors, and cannabinoid receptors). Therapeutics for itch are emerging at a remarkable pace, and we are entering an era with more and more specialized therapies. Increasingly, these treatments are able to relieve itch beyond their effect on inflammation by directly targeting the neurosensory system. [ABSTRACT FROM AUTHOR]

Young adulthood is characterized by a sense of invincibility while the college leisure environment offers a playground for risk taking and experimentation with self-identity. The purpose of this study was to clarify the essence of drug consumption in/as leisure experience and its links to existential authenticity and self-transformation. Data collection involved 16 in-depth individual interviews with U.S. college students. Transcendental phenomenology was implemented, proceeding through the stages of epoché, phenomenological reduction, imaginative variation, and synthesis. Students experienced intrapersonal authenticity through drugs in/as leisure in the form of altered bodily feelings (e.g., self-display and sensibility) and self-making (e.g., self-expression and reaching self-reappraisals). Students also described interpersonal authenticity through drugs in/as leisure, including transformation of family ties and experiencing communitas. Understanding links between drugs in/as leisure, identity, and authenticity offers insights for the intersections between biomedical and psycho-socio-cultural discourses on drugs and contributes to the development of relevant drug education programs. [ABSTRACT FROM AUTHOR]

Due to highly unmet medical needs in rare disease areas, there is great desire to speed up the drug development process. A two-stage adaptive design option for a placebo-controlled registration study is being evaluated. Stage 1 consists of participants in an ongoing phase 2 study with 1-year double blinded (DB) treatment and Stage 2 includes newly enrolled participants with 2-year DB treatment period. The primary endpoint is the annualized rate of change (slope) for a continuous longitudinal measurement, which will be evaluated through a random coefficient linear mixed model. An unblinded interim analysis will be performed using Stage 1 data to re-estimate the sample size for Stage 2, followed by another interim analysis for potential early efficacy stopping when all participants completed the 1-year DB treatment. To control the overall Type 1 error rate, rather than using a conservative approach, the actual correlation between the interim and final test statistics will be taken into account to determine the final significance level given the pre-specified significance level for the interim efficacy analysis. Multiplicity adjustments for secondary endpoints including considerations for order switching between interim and final analysis in this specific case study will also be discussed. [ABSTRACT FROM AUTHOR]

Getting professional help in early-mid adolescence can reduce or eliminate harm related to substance use and risky situations. Research was conducted over eighty years ago that increased our understanding of cognitive development in the adolescent period (the concrete stage of development) of life. However, there is a need for a greater understanding of the Fundamental Attribution Error for substance use problems and risky behaviors. The current study identifies developmental and cultural factors that would facilitate or prevent adolescents from seeking support for problems. Eighty (80) eleven to thirteen-year-olds were recruited from a middle school in Washington State. A qualitative interpretative design using interpretative phenomenological analysis (IPA) was used incorporating semi-structured, computer-generated interviews. Several overlapping themes that reflected barriers or enablers to seeking help were identified: approachability, confidentiality and trustworthiness, and perceived expertise. Help-seeking was facilitated when adolescents believed that the help source would be honest, would keep the information confidential; interpret the information accurately; were viewed as trustworthy; and possessed expertise in the field of substance use and risky behaviors. These findings highlight perceptions that may influence help-seeking for substance use problems and risky behaviors. Mothers were reported to be the most significant supports in life, followed by fathers, then friends and siblings. These supports need further investigation. Further research is needed to determine if help-seeking can be facilitated by improving parent and peer knowledge of risky behaviors and promoting the expertise of health professionals. Additional research is needed into the impact of Adverse Childhood Experiences (ACEs) and the Fundamental Attribution Error. [ABSTRACT FROM AUTHOR]

In contemporary exploratory phase of oncology drug development, there has been an increasing interest in evaluating investigational drug or drug combination in multiple tumor indications in a single basket trial to expedite drug development. There has been extensive research on more efficiently borrowing information across tumor indications in early phase drug development including Bayesian hierarchical modeling and the pruning-and-pooling methods. Despite the fact that the Go/No-Go decision for subsequent Phase 2 or Phase 3 trial initiation is almost always a multi-facet consideration, the statistical literature of basket trial design and analysis has largely been limited to a single binary endpoint. In this paper we explore the application of considering clinical priorities of multiple endpoints based on matched win ratio to the basket trial design and analysis. The control arm data will be simulated for each tumor indication based on the corresponding null assumptions that could be heterogeneous across tumor indications. The matched win ratio matching on the tumor indication can be performed for individual tumor indication, pooled data, or the pooled data after pruning depending on whether an individual evaluation or a simple pooling or a pruning-and-pooling method is used. We conduct the simulation studies to evaluate the performance of proposed win ratio-based framework and the results suggest the proposed framework could provide desirable operating characteristics. [ABSTRACT FROM AUTHOR]

Research and development (R&D) in the pharmaceutical sector traditionally operated with in closed, siloed institutional settings, driven by intellectual property rights concerns that viewed data sharing as a threat. However, the evolving scientific landscape demands a more collaborative approach involving external engagement and dynamic partnerships. To address this, a hybrid contractual framework combining smart contracts, non-fungible tokens (NFTs), and traditional licensing schemes is introduced. This framework was developed through an experimental pilot platform that adhered to FAIR data principles, allowing participants to store, find, and reuse data related to drug discovery. The platform utilizes blockchain technology to document real-world assets in an immutable digital ledger. Smart contracts and NFTs offer an open and global collaborative platform for advancing drug research assets, overcoming hurdles related to standardization, interoperability, and disclosure. This framework aims to reconcile the conflict between the demand for greater data sharing and the protection of rightsholder interests in pharmaceutical R&D. By providing mechanisms for resolving practical challenges, it facilitates further cooperation and innovation in the field. [ABSTRACT FROM AUTHOR]

Systemic Lupus Erythematosus (SLE) is an autoimmune disease characterized by inflammation in multiple organs. A few treatments for SLE currently exist, including antimalarials, glucocorticoids, immunosuppressants, and two recently approved antibody agents; however, an unmet medical need remains for SLE. In addition, developing new drugs targeting SLE is a challenge since no specific biomarkers exist for the prediction of disease progression or drug response. A new drug candidate, E6742, is a specific antagonist of the toll-like receptors 7/8. To address the challenges for drug development in SLE, the process of developing E6742 utilizes a unique system of the Japan Agency for Medical Research and Development (AMED), the Cyclic Innovation for Clinical Empowerment (CiCLE) program. In the CiCLE program, a Phase 1 study in healthy adults was completed (NCT04683185) and a Phase 1/2 study in patients with SLE is on-going (NCT05278663). One of the potential benefits of this program is to conduct academia-led clinical research to identify specific biomarkers for E6742 in parallel with clinical studies (UMIN000042037). The aim of this review is to present current progress within the strategic collaboration of the AMED CiCLE program that optimize clinical development for patients with SLE. [ABSTRACT FROM AUTHOR]

This study exposes the influence of sodium electrolytes and temperature on the interaction forces between tetradecyltrimethylammonium bromide (TTAB) and antibiotic cefixime trihydrate (CMT). The results highlight the significance of considering temperature (from 300.55 to 320.55 K) and electrolytes (NaBr, Na2SO4, Na3PO4, and CH3COONa (NaOAc)) effects when designing drug formulations. Conductometric method was utilised to compute and understand physicochemical parameters occurring during drug-surfactant micellization. The addition of sodium electrolytes favours the micellization of the TTAB and CMT system in aq. salts solution (a decrease of CMC was acquired) except at higher NaOAc concentrations. In all the solvents used herein, the CMC values were detected to be increased with the escalation of working temperature. The $ \Delta H_m^o $ Δ H m o and $ \Delta S_m^o $ Δ S m o expose the survival of hydrophobic interaction involving TTAB and CMT drug in aq. medium whereas both electrostatic and hydrophobic interaction are in function in aq. salts medium. As an extension of the thermodynamic assessment, the molar heat capacity $ ({\Delta C_m^0}) $ (Δ C m 0) were estimated and discussed. The thermodynamics of transfer ( $ \Delta G_{m,tr}^0 $ Δ G m , tr 0 , $ \Delta H_{m,tr}^0 $ Δ H m , tr 0 , and $ \Delta S_{m,tr}^0 $ Δ S m , tr 0 ) and enthalpy-entropy compensation parameters for TTAB + CMT micelles were also analysed. This comprehension of drug-surfactant interaction holds utmost significance in the development of efficient drug formulations and the optimisation of drug delivery techniques. [ABSTRACT FROM AUTHOR]

A digital microfluidic biochip (DMFB) with cyber-physical adaptation implements complex bio-protocols with high precision and high throughput dealing with safety-critical applications including point-of-care diagnosis, personalized medicine, and drug development. Having integrated sensors with network connectivity, a cyber-physical DMFB is undeniably susceptible to attacks. A number of leading research works are carried out to assess various attacks and their impacts. Several defense mechanisms are developed by arranging on-chip monitoring systems through deployment of checkpoints. As checkpoints are external resources imposing a cost-overhead to the system, a cost-effective detection mechanism is of utmost importance. Moreover, after detecting an attack, an efficient recovery process is imperative to execute the associated bioassay in a vulnerable environment. Here, an attack-tolerant synthesis is proposed with two-way security through integrating attack-detection and attack-recovery from various Denial of Service attacks. Moreover, a selective re-synthesis approach has been introduced to allow multiple recovery steps to be executed simultaneously on the biochip. The recovery strategy is closely coupled with the detection process which makes the system adaptive towards attack-tolerance. Experimental results on several benchmarks demonstrate the efficacy of the proposed two-way attack-tolerance strategy. [ABSTRACT FROM AUTHOR]