Hasil untuk "Pharmaceutical industry"

G. Amidon, J. Polli, J. Woodcock et al.

T. Bodenheimer

Michele O’Dwyer, Raffaele Filieri, L. O’Malley

University–Industry Collaboration networks are increasingly significant to national economies. Previous studies have identified barriers and enablers of University–Industry Collaborations, however our understanding of the evolution of such collaborations is still limited thereby restricting our ability to nurture their development. This study explores the establishment of a successful University–Industry Collaboration and considers a range of perceived barriers and enablers through four emergent evolutionary phases: embryonic, initiation, engagement and established. The study adopted a qualitative research approach using a single site case study, focusing on the pharmaceutical industry, with 10 multinational firms and 8 academic institutions involved in a pharmaceutical collaboration. The results demonstrate that specific University–Industry Collaboration barriers and enablers emerge at different points in time, for example, strong lack of trust; strong fear of knowledge leakage, reluctance to share in the embryonic phase evolve to achieving integrity based trust and an intellectual property agreement in the engagement phase. These barriers were overcome using a range of phase appropriate mechanisms, for example, prior experience of the partners was critical in the embryonic phase, while cohesiveness and knowledge complementarity were vital in the engagement phase. The study emphasizes the significance of public funding and its distribution among members in order to support industry evolution and competitiveness. The University–Industry Collaboration continues to attract new participants and additional network-specific investments and has become a global centre of excellence for pharmaceutical research and development.

P. Roberts

N. Ayati, P. Saiyarsarai, S. Nikfar

The novel coronavirus disease 2019 (COVID-19) was characterized as a global pandemic by the WHO on March 11th, 2020. This pandemic had major effects on the health market, the pharmaceutical sector, and was associated with considerable impacts; which may appear in short and long-term time-horizon and need identification and appropriate planning to reduce their socio-economic burden. Current short communication study assessed pharmaceutical market crisis during the COVID-19 era; discussing short- and long-term impacts of the pandemic on the pharmaceutical sector. Short-term impacts of COVID-19 pandemic includes demand changes, regulation revisions, research and development process changes and the shift towards tele-communication and tele-medicine. In addition, industry growth slow-down, approval delays, moving towards self-sufficiency in pharm-production supply chain and trend changes in consumption of health-market products along with ethical dilemma could be anticipated as long-term impacts of COVID-19 pandemic on pharmaceutical sector in both global and local levels. The pandemic of COVID-19 poses considerable crisis on the health markets, including the pharmaceutical sector; and identification of these effects, may guide policy-makers towards more evidence-informed planning to overcome accompanying challenges. Graphical abstract . .

S. Caron, R. W. Dugger, S. G. Ruggeri et al.

N. Choudhry, H. Stelfox, A. Detsky

Helena Bigares Grangeia, Cláudia Silva, Sérgio Paulo Simões et al.

Quality by Design (QbD) was originated in the broad domain of Quality Management and was recently adapted and formalized in specific terms for assisting pharmaceutical companies efforts towards market and operational excellence. However, despite some impressive success stories, the pharmaceutical industry have not yet fully embraced QbD, particularly in routine commercial manufacturing [1,2]. In this review, we aim to analyse the current state of implementation of QbD methodologies and tools in the pharmaceutical industry, extracting patterns and trends and identifying gaps and opportunities that may be considered to improve QbD adoption. For this purpose, a critical analysis of 60 research papers was performed, whose contents were classified, compared and summarized at different abstraction levels. Our analysis reveals the following tools as the frequently adopted for conducting each activity: Risk Assessment (RA) - Ishikawa Diagram, Failure Mode and Effects Analysis (FMEA) and Risk Estimation Matrix (REM); Screening Design of Experiments (DoE) - 2-level Full and Fractional Factorial Designs; Optimisation DoE - Central Composite Design (CCD). Emerging trends include the growing interest in quantifying and managing the impact of raw materials' attributes variability on process and product, as well as the development of Retrospective QbD approaches (rQbD) in complement to standard QbD.

Ruicheng Li, Jingxu Wu

Emergency pharmaceutical logistics during rapid-onset disasters must balance timeliness, legal compliance, and environmental uncertainty. We present a hybrid framework that co-designs quantum-inspired decision dynamics, embedded legal constraints, and blockchain-verified environmental feedback. Candidate routes are modeled as a superposed state whose collapse is governed by entropy modulation-delaying commitment under ambiguity and accelerating resolution when coherent signals emerge. Legal statutes act as real-time projection operators shaping feasible choices, while environmental decoherence cues adjust confidence and path viability. The core engine is situated within a multilevel governance and mechanism design architecture, establishing clear roles, accountability channels, and audit trails. Large-scale simulations in wildfire scenarios demonstrate substantial gains over conventional baselines in latency, compliance, and robustness, while preserving interpretability and fairness adaptation. The resulting system offers a deployable, governance-aware infrastructure where law and physical risk jointly inform emergency routing decisions.

S. A. Zolotov, A. V. Panov

Introduction. The use of the solid disperse systems method to increase the solubility of lipophilic active pharmaceutical ingredients is industrially applicable using different technologies, but the influence of particle size on the dissolution of these systems, depending on the method, is not sufficiently reflected in the literature.Aim. To study the influence of the particle size of amorphous solid disperse systems "darunavir-water-soluble polymer" obtained by solvent removal and hot melt extrusion on the dissolution of Darunavir in the biological pH range of 1.2; 4.5 and 6.8.Materials and methods. Amorphous solid disperse systems were obtained in two ways: solvent removal and hot melt extrusion. Amorphism was determined by X-ray powder diffraction and electron microscopy. The efficiency of disperse systems was compared based on the results of the "Dissolution" test of powders mechanically ground to the same particle size in the biological pH range. The concentration of Darunavir in solution was determined using high-performance liquid chromatography with diode array detection.Results and discussion. The best result was shown by a solid dispersion system based on the Eudragit® E PO polymer with a particle size D90 of less than 10 μm. The increase in the concentration of Darunavir relative to the crystalline form corresponding to Darunavir ethanolate was 324, 2485, and 740%, respectively, in dissolution media with pH 1.2; 4.5, and 6.8.Conclusions. Methods for obtaining solid dispersion systems, such as solvent removal and hot melt extrusion with the same particle size, do not affect the concentration of the Darunavir API in solution in the biological pH range during the Dissolution test.

D. Constable, C. Jiménez-González, R. K. Henderson

Ananya Shah, Manan Shah

Abstract The waste that Pharmaceutical industries produce has hazardous implications on the environment and public health if disposed without being treated. Pharmaceutical Industry wastewater (PIWW) is the product of the drug and formulation development process. And its safe disposal upon treatment is essential. There have been very few studies that reflect on nature of effluents from the Pharmaceutical industries. To select successful and efficacious process of treatment, it is critical to know the characteristics and components of the influent water. Hence, this review aims at comprehensively analysing the characteristics of the pharmaceutical wastewater to provide a better insight on the preferable choices of treatment. Several studies have been carried out on various treatment methods. This paper compares these methods, namely- Physicochemical, Advanced Oxidation and Bioremediation, in which bioremediation emerges as the most sustainable and economically viable option. Additionally, the scope of this paper extends to discuss the various types of bioremediation, their applications and drawbacks in context of industrial wastewater treatment aimed at decreasing the ecotoxicological effects of pharmaceutical wastewater.

Bruno Santos, Rogério Luís C. Costa, Leonel Santos

Unlocking the potential of Industry 5.0 hinges on robust cybersecurity measures. This new Industrial Revolution prioritises human-centric values while addressing pressing societal issues such as resource conservation, climate change, and social stability. Recognising the heightened risk of cyberattacks due to the new enabling technologies in Industry 5.0, this paper analyses potential threats and corresponding countermeasures. Furthermore, it evaluates the existing industrial implementation frameworks, which reveals their inadequacy in ensuring a secure transition from Industry 4.0 to Industry 5.0. Consequently, the paper underscores the necessity of developing a new framework centred on cybersecurity to facilitate organisations' secure adoption of Industry 5.0 principles. The creation of such a framework is emphasised as a necessity for organisations.

Suguru Otani

I investigate how explicit cartels, known as ``shipping conferences", in a global container shipping market facilitated the formation of one of the largest globally integrated markets through entry, exit, and shipbuilding investment of shipping firms. Using a novel data, I develop and construct a structural model and find that the cartels shifted shipping prices by 20-50\% and encouraged firms' entry and investment. In the counterfactual, I find that cartels would increase producer surplus while slightly decreasing consumer surplus, then may increase social welfare by encouraging firms' entry and shipbuilding investment. This would validate industry policies controlling prices and quantities in the early stage of the new industry, which may not be always harmful. Investigating hypothetical allocation rules supporting large or small firms, I find that the actual rule based on tonnage shares is the best to maximize social welfare.

David Wichner, Jeffrey Wishart, Jason Sergent et al.

Safety Management Systems (SMSs) have been used in many safety-critical industries and are now being developed and deployed in the automated driving system (ADS)-equipped vehicle (AV) sector. Industries with decades of SMS deployment have established frameworks tailored to their specific context. Several frameworks for an AV industry SMS have been proposed or are currently under development. These frameworks borrow heavily from the aviation industry although the AV and aviation industries differ in many significant ways. In this context, there is a need to review the approach to develop an SMS that is tailored to the AV industry, building on generalized lessons learned from other safety-sensitive industries. A harmonized AV-industry SMS framework would establish a single set of SMS practices to address management of broad safety risks in an integrated manner and advance the establishment of a more mature regulatory framework. This paper outlines a proposed SMS framework for the AV industry based on robust taxonomy development and validation criteria and provides rationale for such an approach. Keywords: Safety Management System (SMS), Automated Driving System (ADS), ADS-Equipped Vehicle, Autonomous Vehicles (AV)

А. R. Shaikhislamova, N. А. Gasratova

Background. The analysis of the exports of medicines of the Russian Federation (RF) by group 30 (pharmaceutical products) of the commodity nomenclature of foreign economic activity of the Eurasian Economic Union (equal to Harmonized System Code 30, HS 30) is an important task for determining the economic potential of the country in the pharmaceutical industry.Objective: building an export regression model. Development of an alternative mathematical model of pharmaceutical products’ export, suitable for making the forecast.Material and methods. Statistical data on HS 30 exports from 2010 to 2021 were taken from an open source: The International Trade Center (Trade Map). Data for 2022 and later for the Russian Federation are not available in open sources. Registration on the website is not required to collect statistics on export and import volumes based on annual data. The well-known statistical methods and methods of mathematical modeling were used. An alternative approach to regression analysis was developed. Technical data analysis was performed using MAPLE (Watcom Products Inc., Canada) and R (Bell Laboratories, USA) software.Results. Two models were constructed: Model I – a differential model based on cumulative data by year, and Model II – a model of standard regression analysis, the input parameters of which were quarterly export data, and the influencing parameters were a certain group of factors. Model I allowed considering the dynamics of changes in pharmaceutical exports over time (dynamic factors and nonlinear interactions). Model II, in turn, made it possible to determine the dependence of the volume of pharmaceutical exports on various economic indicators, such as gross domestic product, the volume of government procurement, and measures of protectionism. The relative error of Model I does not exceed 10%, which makes it suitable for forecasting.Conclusion. The construction and analysis of specified models help to provide main information about the trends in pharmaceutical product exports in the RF and assess its potential in the global market. The obtained results can be useful for developing strategies of the pharmaceutical industry development, making management decisions and forecasting future exports.

Grona Chen, Yihua Xu, P. Kwok et al.

Abstract Although 3D printing (3DP) has long been an integral part of industries such as aviation and automotive, its use in healthcare, especially the pharmaceutical industry, is relatively new and currently receiving close attention. At the beginning of 2018, we reviewed the applications of 3DP for drug delivery and drug testing [1]. Due to the rapid development of this field, it is necessary to summarize the latest development in this field after 2 years. In this article, we reviewed the three major areas in pharmaceutical applications. First, drug delivery system is the most studied subject, including controlled release, polypills, gastrofloating, orodispersibles and microneedles. Second, 3DP also helped the development of pharmaceutical devices, including pharmacy dispensing aids and drug eluting devices. Lastly, we reviewed the pharmaceutical models for drug testing, covering acellular and cellular models. We also summarized the materials used in the mentioned articles and their regulatory status for pharmaceutical applications to provide references for future research.

Marlene C. Ndoun, Samuel A. Darko

In this paper, we report herein, the conversion of waste prescription and non-prescription pharmaceuticals into carbonaceous materials. The hydrothermal carbonization (HTC) of the pharmaceuticals was carried out at temperatures of 180, 230 and 275 0C in closed reactors for 6, 12 and 24 hours, respectively. The main products from the carbonization process were in the solids, liquids and gas phases. The resulting hydrochars were shown to be very functionalized with a high degree of aromaticity and high carbon content (between 55% to 65%). The adsorptive capacity of the hydrochars to remove Pb2+ ions from an aqueous system was evaluated and compared to that of analytical reagent activated carbon (AR-AC) through batch adsorptive tests. The effect of contact time on batch adsorption experiments with an initial Pb2+ concentration of 50 mg/L was also evaluated. The results indicated that PH24_230 has a better adsorption capacity when compared to AR-AC; achieving over 97% removal of Pb2+ after 60 minutes. The batch adsorption studies were best described by the pseudo-second order kinetic model with coefficient of regression (R2) values above 0.99. Also, slow pyrolysis experiments were carried out to evaluate the difference in solid yields, char heating value and surface area. Pyrochar yields were slightly higher, while heating values were one order of magnitude lower when compared to hydrochars. The pyrolysis conducted at 700°C led to the pyrochar with the highest value of the surface area (63.15 m2/g). The study shows that valuable products can be generated successfully from the hydrothermal carbonization of waste pharmaceuticals. KEYWORDS: waste pharmaceuticals; hydrothermal carbonization; hydrochars, batch adsorption, adsorption capacity

Razin Farhan Hussain, Mohsen Amini Salehi

Industry 4.0 operates based on IoT devices, sensors, and actuators, transforming the use of computing resources and software solutions in diverse sectors. Various Industry 4.0 latency-sensitive applications function based on machine learning to process sensor data for automation and other industrial activities. Sending sensor data to cloud systems is time consuming and detrimental to the latency constraints of the applications, thus, fog computing is often deployed. Executing these applications across heterogeneous fog systems demonstrates stochastic execution time behavior that affects the task completion time. We investigate and model various Industry 4.0 ML-based applications' stochastic executions and analyze them. Industries like oil and gas are prone to disasters requiring coordination of various latency-sensitive activities. Hence, fog computing resources can get oversubscribed due to the surge in the computing demands during a disaster. We propose federating nearby fog computing systems and forming a fog federation to make remote Industry 4.0 sites resilient against the surge in computing demands. We propose a statistical resource allocation method across fog federation for latency-sensitive tasks. Many of the modern Industry 4.0 applications operate based on a workflow of micro-services that are used alone within an industrial site. As such, industry 4.0 solutions need to be aware of applications' architecture, particularly monolithic vs. micro-service. Therefore, we propose a probability-based resource allocation method that can partition micro-service workflows across fog federation to meet their latency constraints. Another concern in Industry 4.0 is the data privacy of the federated fog. As such, we propose a solution based on federated learning to train industrial ML applications across federated fog systems without compromising the data confidentiality.

Patrícia Véras Marrone, Fabio Rampazzo Mathias, Wanderley Marques Bernardo et al.

(1) Background: Any disturbance in the pharmaceutical supply chain (PSC) can disrupt the supply of medicines and affect the efficiency of health systems. Due to shortages in the global pharma supply chain over the past few years and the complex nature of free trade and its limitations when confronted by a major global health and humanitarian crisis, many countries have taken steps to mitigate the risks of disruption, including, for example, recommending the adoption of a plus one diversification approach, increasing safety stock, and nationalizing the medical supply chains. (2) Objective: To scope findings in the academic literature related to decision criteria to guide national policy decisions for the “Partial Nationalization of Pharmaceutical Supply Chain” (PNPSC) from the viewpoints of the three main stakeholders: industry, payers (government and health insurance), and patients. (3) Methods: These consist of a scoping review of the peer-reviewed literature. (4) Results: A total of 115 studies were included. For local manufacturing decisions, five criteria and 15 sub-criteria were identified. Weighting, decision-making, risk assessment, and forecasting were the main data analysis tools applied; (5) Conclusions: The findings could serve as a baseline for constructing PNPSC frameworks after careful adaptation to the local context.