Hasil untuk "Pharmaceutical industry"

E. Mansfield, Jeong-Yeon Lee

A. Straathof, S. Panke, A. Schmid

Andrea Arcuri, Alexander Poth, Olsi Rrjolli et al.

REST APIs are widely used in industry, in all different kinds of domains. An example is Volkswagen AG, a German automobile manufacturer. Established testing approaches for REST APIs are time consuming, and require expertise from professional test engineers. Due to its cost and importance, in the scientific literature several approaches have been proposed to automatically test REST APIs. The open-source, search-based fuzzer EvoMaster is one of such tools proposed in the academic literature. However, how academic prototypes can be integrated in industry and have real impact to software engineering practice requires more investigation. In this paper, we report on our experience in using EvoMaster at Volkswagen AG, as an EvoMaster user from 2023 to 2026. We share our learnt lessons, and discuss several features needed to be implemented in EvoMaster to make its use in an industrial context successful. Feedback about value in industrial setups of EvoMaster was given from Volkswagen AG about 4 APIs. Additionally, a user study was conducted involving 11 testing specialists from 4 different companies. We further identify several real-world research challenges that still need to be solved.

C. Cheok, H. Salman, R. Sulaiman

Pablo Maciel Moreira, Sabrina Miranda de Paula, Erlan Canguçu Aguiar et al.

Introduction: Hypertension is a chronic condition that requires constant monitoring and adjustment of drug therapy. Home Blood Pressure Monitoring (HBPM) has proven to be an effective tool in this process, allowing for a more accurate assessment of blood pressure outside of the clinical setting. Objective: To evaluate the contributions of the use of HBPM devices in the monitoring and evaluation of antihypertensive therapy in patients served by a public clinical pharmacy service. Methods: A longitudinal study with secondary analysis was conducted, using the IBM SPSS Statistics software, of the data aggregated to the MINOR Clinical Trial database, registered on ClinicalTrials under number NCT04861727 and approved by the Research Ethics Committee of the Federal University of Bahia (Opinion No. 4.595.144). Results: In the initial assessment with HBPM, 22.98% of participants (n=74) presented hypotension, only 15.84% (n=51) presented controlled hypertension, and 61.18% of individuals (n=166) were identified with uncontrolled hypertension. After pharmaceutical interventions, the proportion of patients with hypotension decreased to 20.81% (n=67), the proportion of controlled hypertension increased to 36.34% (n=117), while the proportion of uncontrolled hy-pertension decreased to 42.86% (n=138). Conclusion: The use of HBPM demonstrated positive contributions to the optimization of antihypertensive drug therapy and proved to be a useful tool in the clinical practice of the pharmacist, contributing to adequate blood pressure control, identification of hypotensive users and candidates for deprescribing.

Andreia Paula Lubas da Silva, Dayvid Souza Rodrigues, Anais Helena Leite Moreira Bragança et al.

Relato de experiência: O envelhecimento populacional tem elevado a incidência de câncer, tornando o paciente idoso o principal público dos serviços oncológicos.1 Esse cenário impõe desafios adicionais, sobretudo quando o tratamento envolve terapias orais, transferindo ao paciente e seus cuidadores a responsabilidade pelo uso correto dos medicamentos.2 Em idosos, a presença de comorbidades, a polifarmácia e as alterações fisiológicas do envelhecimento aumentam o risco de eventos adversos que comprometem a segurança e a efetividade da terapia.3 Nesse contexto, a assistência farmacêutica é essencial para garantir o uso seguro e racional dos medicamentos, atuando diretamente na orientação e na prevenção de problemas relacionados à medicamentos. Descrição do caso: O presente relato descreve a experiência de um serviço de assistência farmacêutica exclusivo para o público idoso, inserido na saúde suplementar em nível nacional. A equipe é composta por 8 farmacêuticos distribuídos em 7 cidades brasileiras, responsáveis por todas as etapas do ciclo da assistência farmacêutica – desde a programação e aquisição até o armazenamento e a dispensação das terapias orais oncológicas. Como diferencial, o serviço realiza orientação farmacêutica em 100% dos pacientes que iniciam o tratamento oral. A consulta farmacêutica é detalhada, direcionada ao paciente e/ou seus familiares, conduzida por farmacêuticos especializados e respaldada por fichas padronizadas para cada medicamento. São abordados o mecanismo de ação, esquema posológico, cuidados no uso, manejo de reações adversas, armazenamento, descarte e potenciais interações medicamentosas, reforçando a importância da adesão para o sucesso terapêutico. Após a consulta inicial, o paciente é acompanhado durante a retirada dos medicamentos conforme protocolo de tratamento. Nessas ocasiões, o farmacêutico reavalia o caso, reforça as orientações e monitora a evolução da terapia, incluindo a verificação de consultas de retorno e a identificação de problemas relacionados aos medicamentos. Por integrar um sistema de saúde verticalizado, o serviço favorece a comunicação entre os profissionais e alcança alta taxa de aceitação das intervenções farmacêuticas pelos médicos e demais membros da equipe multiprofissional, garantindo agilidade e efetividade no cuidado. Conclusão: Conclui-se que a assistência farmacêutica é essencial no cuidado ao paciente idoso oncológico em terapia oral, considerando a complexidade clínica desse perfil e a necessidade de medidas específicas nos serviços de saúde. Como aprimoramento da prática, estamos trabalhando na criação de um modelo de estratificação de risco durante o acompanhamento farmacoterapêutico, visando à construção de um plano de cuidado direcionado aos pacientes com maior vulnerabilidade em nosso serviço.

Manthana Laichapis, Rungpetch Sakulbumrungsil, Khunjira Udomaksorn et al.

Abstract BackgroundThailand’s pharmaceutical industry is prioritizing innovation and self-reliance through the development of incrementally modified drugs (IMDs), particularly sustained-release dosage forms. However, the financial feasibility of IMD development remains underexplored. ObjectiveThis study evaluates the financial feasibility of developing sustained-release IMDs in Thailand, focusing on costs, timelines, and investment requirements to inform strategic decision-making. MethodsA mixed methods approach was used, combining literature reviews, expert interviews, and financial modeling. Two scenarios were analyzed: (1) only development (phase I) and (2) full clinical trials (phase I to III). Sensitivity analysis was used to assess the impact of key variables on financial feasibility. ResultsThe research and development (R&D) process for sustained-release IMDs takes 7 years for phase I–only development, costing US $1.46‐3.09 million, and 11 years for full clinical trials, costing US $18.60‐20.23 million. Process validation batches accounted for 60% of costs in phase I–only scenarios, while clinical trials represented 70% of costs in full clinical trial scenarios. The annual income required for a 5-year payback period ranged from US $0.20‐1.80 million (phase I only) to US $3.01‐27.11 million (full trials). Shorter R&D durations and longer payback periods substantially improved feasibility. ConclusionsDeveloping sustained-release IMDs in Thailand involves substantial costs and extended timelines but offers a lower-risk alternative to new chemical entities. Strategic investments, efficient R&D processes, and supportive policies are essential to enhance feasibility and alignment with national goals of innovation and self-reliance.

Jinghui Wang, Yutian Zeng, Cong Xu et al.

Non-pharmaceutical interventions, such as contact tracing and social distancing, are critical for controlling epidemic outbreaks, yet their dynamic interactions remain underexplored. We introduce a probabilistic framework to analyze the synergy between contact tracing speed, quantified by the contact tracing period $τ$, and the average number of close contacts, $\bar{k}_+$, reflecting social distancing measures. We identify critical thresholds ($R=1$) that separate pandemic and contained phases in the $\bar{k}_{+}-τ$ plane, validated using high-resolution data from Shenzhen's 2022 Omicron outbreak (1,187 cases, 86,451 contacts). Our findings show that contact tracing alone can contain diseases with $R_0 < 2.12$ (95% CI 2.07-2.16), covering 43.33% of major infectious diseases, while combining with social distancing extends control to $R_0 < 7.82$ (95% CI 7.70-7.93), encompassing 86.67% of pathogens. These results, supported by empirical data, highlight the efficacy of rapid tracing and targeted social distancing as alternatives to mass PCR testing. Our framework offers actionable insights for optimizing NPI strategies, though challenges in scaling to regions with higher tracing miss rates or weaker infrastructure underscore the need for adaptive, data-driven policies.

Sathish Krishna Anumula, SVSV Prasad Sanaboina, Ravi Kumar Nagula et al.

The growing need to automate processes in industrial settings has led to tremendous growth in the robotic systems and especially the robotic arms. The paper assumes the design, modeling and control of a robotic arm to suit industrial purpose like assembly, welding and material handling. A six-degree-of-freedom (DOF) robotic manipulator was designed based on servo motors and a microcontroller interface with Mechanical links were also fabricated. Kinematic and dynamic analyses have been done in order to provide precise positioning and effective loads. Inverse Kinematics algorithm and Proportional-Integral-Derivative (PID) controller were also applied to improve the precision of control. The ability of the system to carry out tasks with high accuracy and repeatability is confirmed by simulation and experimental testing. The suggested robotic arm is an affordable, expandable, and dependable method of automation of numerous mundane procedures in the manufacturing industry.

Moritz Mock, Thomas Forrer, Barbara Russo

Deep learning solutions for vulnerability detection proposed in academic research are not always accessible to developers, and their applicability in industrial settings is rarely addressed. Transferring such technologies from academia to industry presents challenges related to trustworthiness, legacy systems, limited digital literacy, and the gap between academic and industrial expertise. For deep learning in particular, performance and integration into existing workflows are additional concerns. In this work, we first evaluate the performance of CodeBERT for detecting vulnerable functions in industrial and open-source software. We analyse its cross-domain generalisation when fine-tuned on open-source data and tested on industrial data, and vice versa, also exploring strategies for handling class imbalance. Based on these results, we develop AI-DO(Automating vulnerability detection Integration for Developers' Operations), a Continuous Integration-Continuous Deployment (CI/CD)-integrated recommender system that uses fine-tuned CodeBERT to detect and localise vulnerabilities during code review without disrupting workflows. Finally, we assess the tool's perceived usefulness through a survey with the company's IT professionals. Our results show that models trained on industrial data detect vulnerabilities accurately within the same domain but lose performance on open-source code, while a deep learner fine-tuned on open data, with appropriate undersampling techniques, improves the detection of vulnerabilities.

Yuhao Wang, Kailai Wang, Songhua Hu et al.

The rapid evolution of the transportation cybersecurity ecosystem, encompassing cybersecurity, automotive, and transportation and logistics sectors, will lead to the formation of distinct spatial clusters and visitor flow patterns across the US. This study examines the spatiotemporal dynamics of visitor flows, analyzing how socioeconomic factors shape industry clustering and workforce distribution within these evolving sectors. To model and predict visitor flow patterns, we develop a BiTransGCN framework, integrating an attention-based Transformer architecture with a Graph Convolutional Network backbone. By integrating AI-enabled forecasting techniques with spatial analysis, this study improves our ability to track, interpret, and anticipate changes in industry clustering and mobility trends, thereby supporting strategic planning for a secure and resilient transportation network. It offers a data-driven foundation for economic planning, workforce development, and targeted investments in the transportation cybersecurity ecosystem.

Roxana Gheorghita, Liliana Anchidin-Norocel, Roxana Filip et al.

Research regarding the use of biopolymers has been of great interest to scientists, the medical community, and the industry especially in recent years. Initially used for food applications, the special properties extended their use to the pharmaceutical and medical industries. The practical applications of natural drug encapsulation materials have emerged as a result of the benefits of the use of biopolymers as edible coatings and films in the food industry. This review highlights the use of polysaccharides in the pharmaceutical industries and as encapsulation materials for controlled drug delivery systems including probiotics, focusing on their development, various applications, and benefits. The paper provides evidence in support of research studying the use of biopolymers in the development of new drug delivery systems, explores the challenges and limitations in integrating polymer-derived materials with product delivery optimization, and examines the host biological/metabolic parameters that can be used in the development of new applications.

D. Kingston

R. Campos-Vega, K. H. Nieto-Figueroa, B. Dave Oomah

Abstract Background Cocoa Pod Husk (CPH) is the main by-product from the coca industry constituting 67–76% of the cocoa fruit weight. This waste represents an important, and challenging, economic, environmental renewable opportunity, since ten tons of wet CPH are generated for each ton of dry cocoa beans. Scope and approach This review highlights the value that can be added to this industrial co-product to generate new pharmaceutical, medical, nutraceuticals or functional food products. Key findings and conclusions The quality and functionality of cocoa pod husk (CPH) has being improving through processing (fermentation, enzymatic hydrolysis, and combustion, among others), guiding to their use as source of volatile fragrance compounds, lipase extraction, skin whitening, skin hydration and sun screening, ruminants’ food, vegetable gum, organic potash, antibacterial and nanoparticles synthesis with antioxidant and larvicidal activities. However, their exploration to produce high-value-added products, specially for the food industry, is limited as well as their potential health benefits. Cocoa pod husk, the main by-product from cacao industry (up to 76%), is an abundant, inexpensive, and renewable source of bioactive compounds like dietary fiber, pectin, antioxidant compounds, minerals and theobromine, justifying their valorization. This review highlights the value addition that can be achieved with this valuable industrial co-product to generate new pharmaceutical, medical, nutraceuticals or functional food products.

Alina Sorescu, Rajesh Chandy, Jaideep Prabhu

Feng Yang, Yao Zhang, Hong Liang

Human serum albumin (HSA) is an abundant plasma protein, which attracts great interest in the pharmaceutical industry since it can bind a remarkable variety of drugs impacting their delivery and efficacy and ultimately altering the drug’s pharmacokinetic and pharmacodynamic properties. Additionally, HSA is widely used in clinical settings as a drug delivery system due to its potential for improving targeting while decreasing the side effects of drugs. It is thus of great importance from the viewpoint of pharmaceutical sciences to clarify the structure, function, and properties of HSA–drug complexes. This review will succinctly outline the properties of binding site of drugs in IIA subdomain within the structure of HSA. We will also give an overview on the binding characterization of interactive association of drugs to human serum albumin that may potentially lead to significant clinical applications.

Archana Ahlawat, Amy Winecoff, Jonathan Mayer

Across the technology industry, many companies have expressed their commitments to AI ethics and created dedicated roles responsible for translating high-level ethics principles into product. Yet it is unclear how effective this has been in leading to meaningful product changes. Through semi-structured interviews with 26 professionals working on AI ethics in industry, we uncover challenges and strategies of institutionalizing ethics work along with translation into product impact. We ultimately find that AI ethics professionals are highly agile and opportunistic, as they attempt to create standardized and reusable processes and tools in a corporate environment in which they have little traditional power. In negotiations with product teams, they face challenges rooted in their lack of authority and ownership over product, but can push forward ethics work by leveraging narratives of regulatory response and ethics as product quality assurance. However, this strategy leaves us with a minimum viable ethics, a narrowly scoped industry AI ethics that is limited in its capacity to address normative issues separate from compliance or product quality. Potential future regulation may help bridge this gap.

Francisco de Arriba-Pérez, Silvia García-Méndez, Javier Otero-Mosquera et al.

New technologies such as Machine Learning (ML) gave great potential for evaluating industry workflows and automatically generating key performance indicators (KPIs). However, despite established standards for measuring the efficiency of industrial machinery, there is no precise equivalent for workers' productivity, which would be highly desirable given the lack of a skilled workforce for the next generation of industry workflows. Therefore, an ML solution combining data from manufacturing processes and workers' performance for that goal is required. Additionally, in recent times intense effort has been devoted to explainable ML approaches that can automatically explain their decisions to a human operator, thus increasing their trustworthiness. We propose to apply explainable ML solutions to differentiate between expert and inexpert workers in industrial workflows, which we validate at a quality assessment industrial workstation. Regarding the methodology used, input data are captured by a manufacturing machine and stored in a NoSQL database. Data are processed to engineer features used in automatic classification and to compute workers' KPIs to predict their level of expertise (with all classification metrics exceeding 90 %). These KPIs, and the relevant features in the decisions are textually explained by natural language expansion on an explainability dashboard. These automatic explanations made it possible to infer knowledge from expert workers for inexpert workers. The latter illustrates the interest of research in self-explainable ML for automatically generating insights to improve productivity in industrial workflows.

Mehrnoosh Askarpour, Sahar Kokaly, Ramesh S

Agile methodologies have gained significant traction in the software development industry, promising increased flexibility and responsiveness to changing requirements. However, their applicability to safety-critical systems, particularly in the automotive sector, remains a topic of debate. This paper examines the benefits and challenges of implementing agile methods in the automotive industry through a comprehensive review of relevant literature and case studies. Our findings highlight the potential advantages of agile approaches, such as improved collaboration and faster time-to-market, as well as the inherent challenges, including safety compliance and cultural resistance. By synthesizing existing research and practical insights, this paper aims to provide an understanding of the role of agile methods in shaping the future of automotive software development.

A. George, P. A. Shah, P. Shrivastav

Abstract Guar gum a non-ionic polysaccharide obtained from the seeds of Cyamopsis tetragonolobus of the Leguminosae family is found abundantly in nature. It finds extensive use in a variety of fields such as food industry, textile industry, paper industry, cosmetic industry, pharmaceutical industry among many others. Guar gum being a natural polymer with several interesting properties like biodegradability, biosafety, biocompatibility and sustainability presents a potential case for use in pharmaceutical formulations and drug release studies. Although guar gum in its native form finds limited use as delivery carriers owing to its high swelling characteristics in aqueous medium, this property can be significantly altered through derivatization of functional groups, cross-linking and grafting for application in a wide spectrum of biomedical fields. This review article provides a comprehensive overview of different modifications made on guar gum through derivatization in the quest to make them more versatile for drug delivery applications. The drug entrapment efficacy and in vitro drug release from different micro- and nano-formulations using guar gum for controlled release are also assessed.