Hasil untuk "Pharmaceutical industry"

Atta-ur- Rahman

B. Bruggen, M. Mänttäri, M. Nyström

Chao Ma, Yansong Peng, Hongtong Li et al.

The pharmaceutical industry has been desperately searching for efficient drug discovery methods. Organ-on-a-Chip, a cutting-edge technology that can emulate the physiological environment and functionality of human organs on a chip for disease modeling and drug testing, shows great potential for revolutionizing the drug development pipeline. However, successful translation of this novel engineering platform into routine pharmacological and medical scenarios remains to be realized. In this review, we discuss how the Organ-on-a-Chip technology can have critical roles in different preclinical stages of drug development and highlight the current challenges in translation and commercialization of this technology for the pharmacological and medical end-users. Moreover, this review sheds light on the future developmental trends and need for a next-generation Organ-on-a-Chip platform to bridge the gap between animal studies and clinical trials for the pharmaceutical industry.

Elizabeth L. Bell, W. Finnigan, Scott P. France et al.

Shih-Chun Yang, Chih-Hung Lin, C. Sung et al.

Bacteriocins are a kind of ribosomal synthesized antimicrobial peptides produced by bacteria, which can kill or inhibit bacterial strains closely-related or non-related to produced bacteria, but will not harm the bacteria themselves by specific immunity proteins. Bacteriocins become one of the weapons against microorganisms due to the specific characteristics of large diversity of structure and function, natural resource, and being stable to heat. Many recent studies have purified and identified bacteriocins for application in food technology, which aims to extend food preservation time, treat pathogen disease and cancer therapy, and maintain human health. Therefore, bacteriocins may become a potential drug candidate for replacing antibiotics in order to treat multiple drugs resistance pathogens in the future. This review article summarizes different types of bacteriocins from bacteria. The latter half of this review focuses on the potential applications in food science and pharmaceutical industry.

Yuchen Fan, M. Marioli, Kelly Zhang

Lipid nanoparticles, especially liposomes and lipid/nucleic acid complexed nanoparticles have shown great success in the pharmaceutical industry. Their success is attributed to stable drug loading, extended pharmacokinetics, reduced off-target side effects, and enhanced delivery efficiency to disease targets with formidable blood-brain or plasma membrane barriers. Therefore, they offer promising formulation options for drugs limited by low therapeutic indexes in traditional dosage forms and current "undruggable" targets. Recent development of siRNA, antisense oligonucleotide, or the CRISPR complex-loaded lipid nanoparticles and liposomal vaccines also shed light on their potential in enabling versatile formulation platforms for new pharmaceutical modalities. Analytical characterization of these nanoparticles is critical to drug design, formulation development, understanding in vivo performance, as well as quality control. The multi-lipid excipients, unique core-bilayer structure, and nanoscale size all underscore their complicated critical quality attributes, including lipid species, drug encapsulation efficiency, nanoparticle characteristics, product stability, and drug release. To address these challenges and facilitate future applications of lipid nanoparticles in drug development, we summarize available analytical approaches for physicochemical characterizations of lipid nanoparticle-based pharmaceutical modalities. Furthermore, we compare advantages and challenges of different techniques, and highlight the promise of new strategies for automated high-throughput screening and future development.

Hm Jones, K. Rowland-Yeo

The aim of this tutorial is to introduce the concept of physiologically based pharmacokinetic (PBPK) modeling to individuals in the pharmaceutical industry who may be relatively new to this area and to demonstrate application of this approach in a preclinical and clinical setting. The tutorial provides some background on PBPK models and their data requirements, introduces strategies for PBPK modeling in drug development, and includes a discussion on regulatory considerations and potential resource issues.

L. Ewart, Athanasia Apostolou, Skyler A. Briggs et al.

Conventional preclinical models often miss drug toxicities, meaning the harm these drugs pose to humans is only realized in clinical trials or when they make it to market. This has caused the pharmaceutical industry to waste considerable time and resources developing drugs destined to fail. Organ-on-a-Chip technology has the potential to improve success in drug development pipelines, as it can recapitulate organ-level pathophysiology and clinical responses; however, systematic and quantitative evaluations of Organ-Chips’ predictive value have not yet been reported. 870 Liver-Chips were analyzed to determine their ability to predict drug-induced liver injury caused by small molecules identified as benchmarks by the Innovation and Quality consortium, who has published guidelines defining criteria for qualifying preclinical models. An economic analysis was also performed to measure the value Liver-Chips could offer if they were broadly adopted in supporting toxicity-related decisions as part of preclinical development workflows. Here, we show that the Liver-Chip met the qualification guidelines across a blinded set of 27 known hepatotoxic and non-toxic drugs with a sensitivity of 87% and a specificity of 100%. We also show that this level of performance could generate over $3 billion annually for the pharmaceutical industry through increased small-molecule R&D productivity. The results of this study show how incorporating predictive Organ-Chips into drug development workflows could substantially improve drug discovery and development, allowing manufacturers to bring safer, more effective medicines to market in less time and at lower costs. Drug development is lengthy and costly, as it relies on laboratory models that fail to predict human reactions to potential drugs. Because of this, toxic drugs sometimes go on to harm humans when they reach clinical trials or once they are in the marketplace. Organ-on-a-Chip technology involves growing cells on small devices to mimic organs of the body, such as the liver. Organ-Chips could potentially help identify toxicities earlier, but there is limited research into how well they predict these effects compared to conventional models. In this study, we analyzed 870 Liver-Chips to determine how well they predict drug-induced liver injury, a common cause of drug failure, and found that Liver-Chips outperformed conventional models. These results suggest that widespread acceptance of Organ-Chips could decrease drug attrition, help minimize harm to patients, and generate billions in revenue for the pharmaceutical industry. Ewart et al. assess the performance of a human Liver-Chip for predictive toxicology. They also perform an economic analysis to demonstrate its potential financial value for the pharmaceutical industry.

Albert Isidro-Llobet, Martin N. Kenworthy, Subha Mukherjee et al.

In recent years, there has been a growing interest in therapeutic peptides within the pharmaceutical industry with more than 50 peptide drugs on the market, approximately 170 in clinical trials, and >200 in preclinical development. However, the current state of the art in peptide synthesis involves primarily legacy technologies with use of large amounts of highly hazardous reagents and solvents and little focus on green chemistry and engineering. In 2016, the ACS Green Chemistry Institute Pharmaceutical Roundtable identified development of greener processes for peptide API as a critical unmet need, and as a result, a new Roundtable team formed to address this important area. The initial focus of this new team is to highlight best practices in peptide synthesis and encourage much needed innovations. In this Perspective, we aim to summarize the current challenges of peptide synthesis and purification in terms of sustainability, highlight possible solutions, and encourage synergies between academia, the pharmaceutical industry, and contract research organizations/contract manufacturing organizations.

M. Azad, Deborah Olawuni, Georgia Kimbell et al.

Three dimensional (3D) printing as an advanced manufacturing technology is progressing to be established in the pharmaceutical industry to overcome the traditional manufacturing regime of 'one size fits for all'. Using 3D printing, it is possible to design and develop complex dosage forms that can be suitable for tuning drug release. Polymers are the key materials that are necessary for 3D printing. Among all 3D printing processes, extrusion-based (both fused deposition modeling (FDM) and pressure-assisted microsyringe (PAM)) 3D printing is well researched for pharmaceutical manufacturing. It is important to understand which polymers are suitable for extrusion-based 3D printing of pharmaceuticals and how their properties, as well as the behavior of polymer–active pharmaceutical ingredient (API) combinations, impact the printing process. Especially, understanding the rheology of the polymer and API–polymer mixtures is necessary for successful 3D printing of dosage forms or printed structures. This review has summarized a holistic materials–process perspective for polymers on extrusion-based 3D printing. The main focus herein will be both FDM and PAM 3D printing processes. It elaborates the discussion on the comparison of 3D printing with the traditional direct compression process, the necessity of rheology, and the characterization techniques required for the printed structure, drug, and excipients. The current technological challenges, regulatory aspects, and the direction toward which the technology is moving, especially for personalized pharmaceuticals and multi-drug printing, are also briefly discussed.

Shannon P. Callender, Jessica A. Mathews, K. Kobernyk et al.

Juliana Álvares-Teodoro, Lívia Silva Nassif, Ricardo Mesquita Camelo et al.

Introdução: A hemofilia A (HA) resulta de mutações no gene F8, levando à deficiência do fator VIII (FVIII) e, consequentemente, a sangramentos espontâneos. As opções de tratamento incluem profilaxia de sangramentos com FVIII e, mais recentemente, o emicizumabe (EMI), um anticorpo bioespecífico mimético do FVIII. Em 2019, o EMI foi incorporado ao Sistema Único de Saúde (SUS) para pessoas com hemofilia A e inibidores (PwHAi) que não obtiveram sucesso na imunotolerância. Em 2023, a indicação foi ampliada para abranger todos os PwHAi, independentemente da falha ou não do tratamento de imunotolerância. Objetivo: Este estudo comparou os custos do EMI com métodos profiláticos utilizados anteriormente e avaliou seu impacto orçamentário em relação às projeções governamentais. Métodos: O Registro Nacional de Pessoas com HA em Uso de Emicizumabe no Brasil (EMCase) é um estudo observacional de mundo real iniciado em 2020, conduzido em 16 centros de tratamento de hemofilia no país. A análise incluiu o consumo de FVIII, agentes de bypass e EMI. Os custos de tratamento para o período pré-EMI e para o primeiro ano de uso do EMI foram calculados utilizando-se os preços pagos pelo Ministério da Saúde, conforme registrados no Banco de Preços em Saúde. Os custos médios anuais de tratamento por quilograma de peso corporal foram comparados com as projeções orçamentárias governamentais de 2023. Resultados: Foram incluídos 46 indivíduos com HA moderada a grave e presença de inibidores. Antes do tratamento com EMI, o custo real do tratamento foi de R$ 36.324,30 /kg.ano. Durante o primeiro ano de profilaxia com EMI, o custo real foi de R$ 21.853,30 /kg.ano, representando uma redução aproximada de 39,8% em relação ao período anterior. Adicionalmente, o custo projetado pelo governo para 2023, foi estimado em BRL 19.119,60 /kg.ano para o primeiro ano de uso do EMI, resultando em um aumento de 14,3% no impacto orçamentário projetado. Conclusões: Embora o custo real durante o primeiro ano de profilaxia com EMI tenha sido superior ao custo projetado pelo governo, observou-se redução de custos em comparação ao período pré-EMI. Essa diferença pode ser explicada, em parte, pela não consideração de fatores como o desperdício do produto nas projeções governamentais, o que pode influenciar nos custos reais. O estudo evidenciou a importância de análises econômicas baseadas em dados do mundo real na avaliação de tecnologias em saúde, complementando as projeções governamentais para subsidiar a tomada de decisão.

Monica Marconi Sciarroni, Emanuele Storti

Industrial IoT ecosystems bring together sensors, machines and smart devices operating collaboratively across industrial environments. These systems generate large volumes of heterogeneous, high-velocity data streams that require interoperable, secure and contextually aware management. Most of the current stream management architectures, however, still rely on syntactic integration mechanisms, which result in limited flexibility, maintainability and interpretability in complex Industry 5.0 scenarios. This work proposes a context-aware semantic platform for data stream management that unifies heterogeneous IoT/IoE data sources through a Knowledge Graph enabling formal representation of devices, streams, agents, transformation pipelines, roles and rights. The model supports flexible data gathering, composable stream processing pipelines, and dynamic role-based data access based on agents' contexts, relying on Apache Kafka and Apache Flink for real-time processing, while SPARQL and SWRL-based reasoning provide context-dependent stream discovery. Experimental evaluations demonstrate the effectiveness of combining semantic models, context-aware reasoning and distributed stream processing to enable interoperable data workflows for Industry 5.0 environments.

Christophe Ponsard, Abiola Paterne Chokki, Jean-François Daune

Cyber-Physical Systems (CPS) play a critical role in modern industrial domains, including manufacturing, energy, transportation, and healthcare, where they enable automation, optimization, and real-time decision-making. Ensuring the robustness of these systems is paramount, as failures can have significant economic, operational, and safety consequences. This paper present findings from an industrial survey conducted in Wallonia, covering a wide range of sectors, to assess the current state of practice in CPS robustness. It investigates robustness from how it is understood and applied in relationship with requirements engineering, system design, test execution, failure modes, and available tools. It identifies key challenges and gaps between industry practices and state-of-the-art methodologies. Additionally, it compares our findings with similar industrial surveys from the literature.

Gabriel de Oliveira Moura, Mariana Costa Milan, Marina Lima da Silveira et al.

Introdução: O leite é um dos produtos agropecuários mais importantes do mundo sendo consumido diariamente por bilhões de pessoas em suas variadas formas. No Espírito Santo, a produção leiteira representa um setor economicamente relevante.1 No entanto, a garantia da qualidade do leite ainda constitui um desafio, uma vez que uma matéria prima de alta qualidade não apenas reduz perdas no processamento de laticínios e agrega valor aos produtos, mas também contribui para a redução da ocorrência de doenças de transmissão alimentar (DTAs) associadas a presença de microrganismos patógenos.2 Objetivos: Este estudo teve por objetivo avaliar a qualidade do leite in natura comercializado em Alegre- ES por meio da quantificação de cocos Gram-positivos (CGP) e da identificação de bactérias coagulase positivas nas amostras avaliadas. Material e Método: Para isso foram coletadas dez amostras de leite, no período de abril a dezembro de 2024. Após a coleta, as amostras foram mantidas a 8oC e imediatamente enviadas ao laboratório. Para a contagem, foram realizadas diluições seriadas das amostras (10-2 a 10-5) e estas foram plaqueadas por espalhamento em meio seletivo de ágar manitol salgado e incubadas por 48h a 35 +/- 2oC. Após o período de incubação, foram selecionadas até 10 colônias com características sugestivas de estafilococos (crescimento com coloração amarela e formação de halo de fermentação de manitol). As colônias selecionadas foram submetidas à coloração, totalizando 100 colônias analisadas. Posteriormente, as colônias foram submetidas ao teste de coagulase para a identificação de Staphylococcus coagulase positiva (SCP). As SPC foram preservadas em meio de conservação apropriado para análises posteriores. Resultados e Discussão: As contagens de CGP nas amostras de leite variaram de 5,6 × 104 UFC/m L a 7,25 × 106 UFC/mL. Embora a legislação não estabeleça limite específico3, valores acima de 105 UFC/mL indicam contaminação por Staphylococcus sp., o que compromete a qualidade e representa risco à saúde pública.4 Seis amostras ultrapassaram esse limite, apontando falhas no manejo sanitário, ordenha, higienização e armazenamento do leite, além de possíveis problemas relacionados à mastite subclínica e uso de equipamentos contaminados. Das colônias isoladas e submetidas ao teste de coagulase, 65,52% (57 colônias) apresentaram resultado positivo, indicando a presença de SCP, como Staphylococcus aureus. Essa elevada frequência é preocupante, pois SCP são reconhecidas pela capacidade de produzir enterotoxinas termoestáveis que podem resistir ao processamento térmico e causar toxinfecção alimentar em humanos.5 Conclusões: Diante dos resultados, é essencial adotar boas práticas de ordenha, melhorar a higienização e o controle sanitário, além de monitorar continuamente a saúde do rebanho para garantir a qualidade e segurança do leite produzido.

Yaan Zhang, Tingyu Zhou, Zhuxin She et al.

Multivalent lectin-glycan interactions play a significant role in biology. Developing novel methods to investigate glycosyl-receptor interactions quantitatively and elucidate binding modes is crucial for advancing biomedical detection techniques and innovative therapeutic approaches. Herein, a mannobiose-chalcone disulfide ligand (2S-DiMan) was designed and synthesized. Through click chemistry and surface ligand exchange, 2S-DiMan-functionalized gold nanoprobes (2S-DiMan-AuNPs) were prepared and characterized. Density functional theory (DFT) calculations and molecular docking revealed that the oxygen atoms of the mannobiose moiety in 2S-DiMan have the highest negative charge, enabling specific recognition of the carbohydrate recognition domain (CRD) of concanavalin A (Con A) by effectively occupying its sugar-binding site and forming hydrogen bonds. Thus, the 2S-DiMan ligand exhibits strong binding affinity for Con A. The effect of fluorescence quenching on the recognition of Con A was further investigated. Obvious quenching was observed upon 2S-DiMan-AuNPs addition. The probes showed a dissociation constant (Kd) of 0.76 μM for Con A (affinity enhancement factor β = 315-fold vs. monovalent mannose) and achieved a limit of detection as low as 5.02 nM. This work provides a novel structure and method for analysing lectins with sugar-binding sites, investigating protein-glycan multivalent binding affinity, and assaying disease-associated glycans, with promising potential for medical research and biotechnological applications.

Davide Privitera, Alessandro Mecocci, Sandro Bartolini

Abstract We publish a comprehensive dataset of peristaltic pump dosing outputs in pharmaceutical manufacturing, where accuracy is crucial for drug quality and patient safety, consisting of 149,847 measurements spanning volumes from 0.1 to 2.0 ml. An industrial filling system was used to acquire data under controlled conditions, using calibrated weighing equipment. To the best of our knowledge, this is the first dataset documenting pump behavior across such a wide range of volumes. The dataset aims to constitute a solid tool that enables investigation from short-term precision to long-term stability standpoints, providing detailed insights into peristaltic pump behavior under various operating conditions. Additionally, the dataset incorporates compensation outcomes across multiple volumes, documenting both statistical and AI-based compensation strategies, thus exemplifying how the statistical behavior of the dosing can change in response to some compensation strategies aimed to improve dosing accuracy. This resource directly addresses pharmaceutical industry needs by supporting optimization of quality control systems and validation of novel compensation strategies.

Ashley Hourigan, Ridewaan Hanslo

The demand for rapid software delivery in the Information Technology (IT) industry has significantly intensified, emphasising the need for faster software products and service releases with enhanced features to meet customer expectations. Agile methodologies are replacing traditional approaches such as Waterfall, where flexibility, iterative development and adaptation to change are favoured over rigid planning and execution. DevOps, a subsequent evolution from Agile, emphasises collaborative efforts in development and operations teams, focusing on continuous integration and deployment to deliver resilient and high-quality software products and services. This study aims to critically assess both Agile and DevOps practices in the IT industry to identify the feasibility and applicability of Agile methods in DevOps practices. Eleven semi-structured interviews were conducted with Agile and DevOps practitioners in varying capacities across several sectors within the IT industry. Through thematic analysis, 51 unique codes were extracted and synthesised into 19 themes that reported on each phase of the DevOps lifecycle, specifically regarding the integration and implementation of Agile methods into DevOps practices. Based on the findings, a new understanding detailing the interrelationship of Agile methods in DevOps practices was discussed that met the research objectives.

Seonwu Kim, Yohan Na, Kihun Kim et al.

The emergence of open-source large language models (LLMs) has expanded opportunities for enterprise applications; however, many organizations still lack the infrastructure to deploy and maintain large-scale models. As a result, small LLMs (sLLMs) have become a practical alternative despite inherent performance limitations. While Domain Adaptive Continual Pretraining (DACP) has been explored for domain adaptation, its utility in commercial settings remains under-examined. In this study, we validate the effectiveness of a DACP-based recipe across diverse foundation models and service domains, producing DACP-applied sLLMs (ixi-GEN). Through extensive experiments and real-world evaluations, we demonstrate that ixi-GEN models achieve substantial gains in target-domain performance while preserving general capabilities, offering a cost-efficient and scalable solution for enterprise-level deployment.

Ruiyang Ma, Tianhao Wei, Jiaxi Zhang et al.

As hardware design complexity increases, hardware fuzzing emerges as a promising tool for automating the verification process. However, a significant gap still exists before it can be applied in industry. This paper aims to summarize the current progress of hardware fuzzing from an industry-use perspective and propose solutions to bridge the gap between hardware fuzzing and industrial verification. First, we review recent hardware fuzzing methods and analyze their compatibilities with industrial verification. We establish criteria to assess whether a hardware fuzzing approach is compatible. Second, we examine whether current verification tools can efficiently support hardware fuzzing. We identify the bottlenecks in hardware fuzzing performance caused by insufficient support from the industrial environment. To overcome the bottlenecks, we propose a prototype, HwFuzzEnv, providing the necessary support for hardware fuzzing. With this prototype, the previous hardware fuzzing method can achieve a several hundred times speedup in industrial settings. Our work could serve as a reference for EDA companies, encouraging them to enhance their tools to support hardware fuzzing efficiently in industrial verification.