Hasil untuk "Pharmaceutical industry"

P. Bierly, A. Chakrabarti

D. Acemoglu, Joshua Linn

Laura B. Cardinal

C. Jiménez-González, C. Ponder, Q. Broxterman et al.

Lady Laura Del Rio Osorio, E. Flórez-López, C. Grande-Tovar

The food sector includes several large industries such as canned food, pasta, flour, frozen products, and beverages. Those industries transform agricultural raw materials into added-value products. The fruit and vegetable industry is the largest and fastest-growing segment of the world agricultural production market, which commercialize various products such as juices, jams, and dehydrated products, followed by the cereal industry products such as chocolate, beer, and vegetable oils are produced. Similarly, the root and tuber industry produces flours and starches essential for the daily diet due to their high carbohydrate content. However, the processing of these foods generates a large amount of waste several times improperly disposed of in landfills. Due to the increase in the world’s population, the indiscriminate use of natural resources generates waste and food supply limitations due to the scarcity of resources, increasing hunger worldwide. The circular economy offers various tools for raising awareness for the recovery of waste, one of the best alternatives to mitigate the excessive consumption of raw materials and reduce waste. The loss and waste of food as a raw material offers bioactive compounds, enzymes, and nutrients that add value to the food cosmetic and pharmaceutical industries. This paper systematically reviewed literature with different food loss and waste by-products as animal feed, cosmetic, and pharmaceutical products that strongly contribute to the paradigm shift to a circular economy. Additionally, this review compiles studies related to the integral recovery of by-products from the processing of fruits, vegetables, tubers, cereals, and legumes from the food industry, with the potential in SARS-CoV-2 disease and bacterial diseases treatment.

Lanting Qian, S. Durairaj, S. Prins et al.

The surging growth of the pharmaceutical industry is a result of the rapidly increasing human population, which has inevitably led to new biomedical and environmental issues. Aside from the quality control of pharmaceutical production and drug delivery, there is an urgent need for precise, sensitive, portable, and cost-effective technologies to track patient overdosing and to monitor ambient water sources and wastewater for pharmaceutical pollutants. The development of advanced nanomaterial-based electrochemical sensors and biosensors for the detection of pharmaceutical compounds has garnered immense attention due to their advantages, such as high sensitivity and selectivity, real-time monitoring, and ease of use. This review article surveys state-of-the-art nanomaterials-based electrochemical sensors and biosensors for the detection and quantification of six classes of significant pharmaceutical compounds, including anti-inflammatory, anti-depressant, anti-bacterial, anti-viral, anti-fungal, and anti-cancer drugs. Important factors such as sensor/analyte interactions, design rationale, fabrication, characterization, sensitivity, and selectivity are discussed. Strategies for the development of high-performance electrochemical sensors and biosensors tailored toward specific pharmaceuticals are highlighted to provide readers and scientists with an extensive toolbox for the detection of a wide range of pharmaceuticals. Our aims are two-fold: (i) to inspire readers by further elucidating the properties and functionalities of existing nanomaterials for the detection of pharmaceuticals; and (ii) to provide examples of the potential opportunities that these devices have for the advanced sensing of pharmaceutical compounds toward safeguarding human health and ecosystems on a global scale.

S. Omer, László Forgách, R. Zelkó et al.

Recently, the electrospinning (ES) process has been extensively studied due to its potential applications in various fields, particularly pharmaceutical and biomedical purposes. The production rate using typical ES technology is usually around 0.01–1 g/h, which is lower than pharmaceutical industry production requirements. Therefore, different companies have worked to develop electrospinning equipment, technological solutions, and electrospun materials into large-scale production. Different approaches have been explored to scale-up the production mainly by increasing the nanofiber jet through multiple needles, free-surface technologies, and hybrid methods that use an additional energy source. Among them, needleless and centrifugal methods have gained the most attention and applications. Besides, the production rate reached (450 g/h in some cases) makes these methods feasible in the pharmaceutical industry. The present study overviews and compares the most recent ES approaches successfully developed for nanofibers’ large-scale production and accompanying challenges with some examples of applied approaches in drug delivery systems. Besides, various types of commercial products and devices released to the markets have been mentioned.

Siyuan Yang, Xihan Bian, Jiayin Tang

The increasing frequency and complexity of regulatory updates present a significant burden for multinational pharmaceutical companies. Compliance teams must interpret evolving rules across jurisdictions, formats, and agencies, often manually, at high cost and risk of error. We introduce RegGuard, an industrial-scale AI assistant designed to automate the interpretation of heterogeneous regulatory texts and align them with internal corporate policies. The system ingests heterogeneous document sources through a secure pipeline and enhances retrieval and generation quality with two novel components: HiSACC (Hierarchical Semantic Aggregation for Contextual Chunking) semantically segments long documents into coherent units while maintaining consistency across non-contiguous sections. ReLACE (Regulatory Listwise Adaptive Cross-Encoder for Reranking), a domain-adapted cross-encoder built on an open-source model, jointly models user queries and retrieved candidates to improve ranking relevance. Evaluations in enterprise settings demonstrate that RegGuard improves answer quality specifically in terms of relevance, groundedness, and contextual focus, while significantly mitigating hallucination risk. The system architecture is built for auditability and traceability, featuring provenance tracking, access control, and incremental indexing, making it highly responsive to evolving document sources and relevant for any domain with stringent compliance demands.

Suyash Mishra, Srikanth Patil, Satyanarayan Pati et al.

AI is transforming pharmaceutical search, where traditional systems struggle with multimodal content and manual curation. Finder is a scalable AI-powered framework that unifies retrieval across text, images, audio, and video using hybrid vector search, combining sparse lexical and dense semantic models. Its modular pipeline ingests diverse formats, enriches metadata, and stores content in a vector-native backend. Finder supports reasoning-aware natural language search, improving precision and contextual relevance. The system has processed over 291,400 documents, 31,070 videos, and 1,192 audio files in 98 languages. Techniques like hybrid fusion, chunking, and metadata-aware routing enable intelligent access across regulatory, research, and commercial domains.

Abhijeet Ghadge, M. Bourlakis, Sachin S. Kamble et al.

Research on Blockchain implementation in the Pharmaceutical Supply Chains (PSC) is lacking despite its strong potential to overcome conventional supply chain challenges. Thus, this study aims to provide critical insight into the nexus between Blockchain and PSC and further build a conceptual framework for implementation within the pharmaceutical industry. Following a systematic literature review and text mining approach, 65 interdisciplinary articles published between 2010 and 2021 were studied to capture the decade long developments. Descriptive and thematic analysis showcases nascent developments of Blockchain in PSC. The drivers and barriers to adoption, implementation stages, and applications identified through the thematic analysis guide in setting the agenda for future research, primarily focussing on the use of Blockchain for drug counterfeiting, recall issues, along with other sector-specific challenges such as patient privacy, regulations and clinical trials. Research on Blockchain for PSC has been slow compared to other sectors, but has accelerated since the Covid-19 pandemic. Identified influential factors, implementation process and apparent applications are expected to influence researchers and practitioners in developing a roadmap for adopting Blockchain in the pharmaceutical industry. The proposed conceptual framework is novel and provides valuable directions to producers, regulators and governments to implement Blockchain in the pharmaceutical industry.

Francesco Destro, M. Barolo

Recently, the pharmaceutical industry has been facing several challenges associated to the use of outdated development and manufacturing technologies. The return on investment on research and development has been shrinking, and, at the same time, an alarming number of shortages and recalls for quality concerns has been registered. The pharmaceutical industry has been responding to these issues through a technological modernization of development and manufacturing, under the support of initiatives and activities such as quality-by-design (QbD), process analytical technology, and pharmaceutical emerging technology. In this review, we analyze this modernization trend, with emphasis on the role that mathematical modeling plays within it. We begin by outlining the main socio-economic trends of the pharmaceutical industry, and by highlighting the life-cycle stages of a pharmaceutical product in which technological modernization can help both achieve consistently high product quality and increase return on investment. Then, we review the historical evolution of the pharmaceutical regulatory framework, and we discuss the current state of implementation and future trends of QbD. The pharmaceutical emerging technology is reviewed afterwards, and a discussion on the evolution of QbD into the more effective quality-by-control (QbC) paradigm is presented. Further, we illustrate how mathematical modeling can support the implementation of QbD and QbC across all stages of the pharmaceutical life-cycle. In this respect, we review academic and industrial applications demonstrating the impact of mathematical modeling on three key activities within pharmaceutical development and manufacturing, namely design space description, process monitoring, and active process control. Finally, we discuss some future research opportunities on the use of mathematical modeling in industrial pharmaceutical environments.

Bo Qu, Zhurong Wang, Daisuke Yagi et al.

This paper presents a novel approach to e-commerce payment fraud detection by integrating reinforcement learning (RL) with Large Language Models (LLMs). By framing transaction risk as a multi-step Markov Decision Process (MDP), RL optimizes risk detection across multiple payment stages. Crafting effective reward functions, essential for RL model success, typically requires significant human expertise due to the complexity and variability in design. LLMs, with their advanced reasoning and coding capabilities, are well-suited to refine these functions, offering improvements over traditional methods. Our approach leverages LLMs to iteratively enhance reward functions, achieving better fraud detection accuracy and demonstrating zero-shot capability. Experiments with real-world data confirm the effectiveness, robustness, and resilience of our LLM-enhanced RL framework through long-term evaluations, underscoring the potential of LLMs in advancing industrial RL applications.

Tingwei Xie, Tianyi Zhou, Yonghong Song

We present PharmaShip, a real-world Chinese dataset of scanned pharmaceutical shipping documents designed to stress-test pre-trained text-layout models under noisy OCR and heterogeneous templates. PharmaShip covers three complementary tasks-sequence entity recognition (SER), relation extraction (RE), and reading order prediction (ROP)-and adopts an entity-centric evaluation protocol to minimize confounds across architectures. We benchmark five representative baselines spanning pixel-aware and geometry-aware families (LiLT, LayoutLMv3-base, GeoLayoutLM and their available RORE-enhanced variants), and standardize preprocessing, splits, and optimization. Experiments show that pixels and explicit geometry provide complementary inductive biases, yet neither alone is sufficient: injecting reading-order-oriented regularization consistently improves SER and EL and yields the most robust configuration, while longer positional coverage stabilizes late-page predictions and reduces truncation artifacts. ROP is accurate at the word level but challenging at the segment level, reflecting boundary ambiguity and long-range crossings. PharmaShip thus establishes a controlled, reproducible benchmark for safety-critical document understanding in the pharmaceutical domain and highlights sequence-aware constraints as a transferable bias for structure modeling. We release the dataset at https://github.com/KevinYuLei/PharmaShip.

Yash Mundhra, Max Valk, Maliheh Izadi

Large language models have shown impressive performance in various domains, including code generation across diverse open-source domains. However, their applicability in proprietary industrial settings, where domain-specific constraints and code interdependencies are prevalent, remains largely unexplored. We present a case study conducted in collaboration with the leveling department at ASML to investigate the performance of LLMs in generating functional, maintainable code within a closed, highly specialized software environment. We developed an evaluation framework tailored to ASML's proprietary codebase and introduced a new benchmark. Additionally, we proposed a new evaluation metric, build@k, to assess whether LLM-generated code successfully compiles and integrates within real industrial repositories. We investigate various prompting techniques, compare the performance of generic and code-specific LLMs, and examine the impact of model size on code generation capabilities, using both match-based and execution-based metrics. The findings reveal that prompting techniques and model size have a significant impact on output quality, with few-shot and chain-of-thought prompting yielding the highest build success rates. The difference in performance between the code-specific LLMs and generic LLMs was less pronounced and varied substantially across different model families.

R. Brands, L. Fuchs, J. M. Seyffer et al.

The pharmaceutical industry is moving from off-line quality testing to real-time release testing (RTRT) to improve drug quality while reducing costs. The implementation of RTRT requires advanced in-line process analytics, where UV/Vis spectroscopy has proven its suitability. However, quantification of the sample size requires detailed knowledge of the penetration depth. In this study, bilayer tablets were produced using a hydraulic tablet press. The lower layer contained titanium dioxide and microcrystalline cellulose (MCC), while the upper layer consisted of MCC, lactose or a combination with theophylline. The thickness of the upper layer was stepwise increased. Spectra from 224 to 820 nm were recorded with an orthogonally aligned UV/Vis probe. Thereby, the experimental penetration depth reached up to 0.4 mm, while the Kubelka-Munk model yielded a theoretical maximum penetration depth of 1.38 mm. Based on these values, the effective sample sizes were determined. Considering a parabolic penetration profile, the maximum volume was 2.01 mm$^3$. The results indicated a wavelength and particle size dependency. Micro-CT analysis confirmed the even distribution of the API in the tablets proving the sufficiency of the UV/Vis sample size. Consequently, UV/Vis spectroscopy is a reliable alternative for RTRT in tableting.

Gjeorgiev Blagoj, Miceva Dijana, Karpicarov Dino et al.

Medicine registration refers to evaluating a medical product's safety, efficacy, and quality, leading to the granting of a Marketing Authorization. Given the intense globalization of the pharmaceutical industry, harmonizing regulatory procedures between the European Medicines Agency (EMA) and the United States's Food and Drug Administration (FDA) is critical for accelerating the availability of new medicines. The EMA oversees three different procedures for medicine registration: Centralized, Decentralized and Mutual Recognition Procedure. Conversely, the FDA offers three registration applications - Investigational New Drug Application, New Drug Application and Abbreviated New Drug Application. A comparison between the FDA and EMA reveals numerous discrepancies within each system and highlights opportunities for harmonization. While both agencies achieve high concordance in their final decisions, the FDA is faster and more streamlined, benefiting from a centralized authority and expedited pathways. The EMA's structured approach ensures thorough evaluations but can delay approvals. Efforts to harmonize procedures, such as the FDA-EMA Parallel Scientific Advice program and the Mutual Recognition Agreement, aim to enhance alignment and reduce development resources, creating a global regulatory environment to streamline the registration of new medicines.

Thayná Figueredo Góis, Amanda Maria Paixão Soares, Anna Gabriela Souto Maior Nascimento

Introdução: A efetividade do tratamento farmacológico está intimamente relacionada à disponibilidade do medicamento de forma acessível ao usuário1. O Componente Especializado da Assistência Farmacêutica (CEAF) busca garantir a integralidade do tratamento medicamentoso para agravos crônicos e raros, com custos de tratamento mais elevados ou de maior complexidade2. Durante o fluxo padrão, do cadastro à dispensação do medicamento, por vezes se faz necessário o comparecimento do paciente ou familiar à sede do CEAF, fato que, em alguns casos, se torna uma barreira de acesso; principalmente para pacientes idosos, com mobilidade reduzida ou vulneráveis financeiramente, comprometendo assim a disponibilidade do medicamento ao usuário e a adesão ao tratamento farmacológico3. O Programa Remédio em Casa é uma iniciativa pública que, inicialmente, foi instituída visando à entrega domiciliar de medicamentos a pacientes atendidos nas unidades de atenção básica. Mas, recentemente, observa-se a expansão ou implementação do programa no CEAF em alguns estados4,5. Objetivo: Neste contexto, este estudo foi conduzido com o objetivo de avaliar a extensão, em âmbito nacional, do Programa Remédio em Casa no Componente Especializado da Assistência Farmacêutica (CEAF), e o seu impacto no tratamento medicamentoso de pacientes vulneráveis portadores de agravos crônicos e raros. Material e Método: Tratou-se de um estudo quantitativo de caráter descritivo, cuja análise foi realizada a partir de dados coletados em publicações científicas, sites oficiais do governo ou contato direto com as coordenações dos CEAFs estaduais. Resultados: No levantamento realizado, encontraram-se registros do programa de entrega domiciliar de medicamentos do CEAF em 50% dos estados brasileiros e no Distrito Federal, sendo eles Acre, Alagoas, Bahia, Ceará, Espírito Santo, Mato Grosso, Mato Grosso do Sul, Paraná, Pernambuco, Rio Grande do Sul, Rondônia, São Paulo e Sergipe; com variações no nome do programa como “Medicamento em Casa”, “Remédio aqui em Casa” ou apenas “Entrega à Domicílio do CEAF”. Sobre os demais estados, não foram encontrados registros públicos a respeito, tampouco houve sucesso nas tentativas de contato. Como impacto do programa nos estados em que está implantado, têm-se uma maior adesão terapêutica e alto nível de satisfação dos pacientes beneficiados, com geração de bem-estar e qualidade de vida, além do melhoramento do fluxo de atendimento a todos os usuários, com redução de filas e do tempo de espera dos atendimentos presenciais. Conclusões: Assim, conclui-se que o serviço de entrega domiciliar de medicamentos do CEAF, comumente nomeado “Programa Remédio em Casa”, é uma estratégia eficiente de apoio à saúde pública, através da garantia do acesso ao medicamento e melhoria da adesão terapêutica. Além da promoção da inclusão social, ao fortalecer a cidadania de uma parcela vulnerável da população, é evidenciado, ainda, a grande possibilidade de replicação, adaptabilidade e expansão do projeto para os demais estados do país.

O. V. Shapovalova, N. P. Neugodova

INTRODUCTION. Beta-glucans and peptidoglycans are cell wall components of bacteria and fungi that are potential sources of pyrogenic contamination of parenteral medicines. Such impurities can cause adverse immune reactions. Therefore, recently, certain attention has been paid to identification of beta-glucans and peptidoglycans in medicines. Despite the lack of a harmonised detection method for beta-glucans and/or peptidoglycans, pharmaceutical industry uses several methods for identification and quantitation of these impurities.AIM. This study aimed to assess applicability of the existing detection methods for beta-glucans and / or peptidglycans in the medicinal products.MATERIALS AND METHODS. Applicability of detection was examined for beta-glucans and peptidoglycans using amoebocyte lysate and silkworm larvae plasma as reagents. Beta-glucans were detected in Bupivacaine, the product that was previously found to have random glucan impurities. In the drug tests, three types of amoebocyte lysate reagents of different compositions were used reacting to 1) bacterial endotoxins and beta-glucans (lysate with factors C and G); 2) only bacterial endotoxins (lysate with factor C); 3) only beta-glucans (lysate with factor G). Peptidoglycans in Icodextrin were assessed using a reagent from the silkworm larvae plasma. For qualitative analysis, colour of the test solutions was visually assessed after heating them in a dry-air block heater. Kinetic photocolorimetric method was used for quantitation; the primary data were processed using R software.RESULTS. As a result of two tests with amoebocyte lysate reagents (factors C and G) and (factor C), beta-glucans were detected in Bupivacaine. Chromogenic kinetic method using amoebocyte lysate (factor G) quantified the impurity, which exceeded 2,000 pg/mL. For Icodextrin, peptidoglycan reference content (not more than 200 pg/mL) was not exceeded.CONCLUSIONS. Identification methods for beta-glucans and/or peptidoglycans using amoebocyte lysate and silkworm plasma are applicable for identifying these impurities in the medicinal products. While choosing a study method, product composition and analytical purpose are to be considered.

XYv Zhao, Su Wang, Su Wang et al.

Digital inclusive finance, with ‘universality’ as its core feature, can stimulate enterprises to increase capital investment in research and development (R&D) through diversified channels. Using the digital financial inclusion index of 337 prefecture-level cities in China and the empirical data of Shanghai and Shenzhen A-share-listed pharmaceutical manufacturing enterprises from 2011 to 2022, the article empirically examines the impact mechanism of digital financial inclusion on R&D investment of pharmaceutical manufacturing enterprises from the perspective of government subsidy by using a high-dimensional fixed-effects model, a two-stage systematic GMM, and a moderated-effects test method. It is found that digital financial inclusion has a positive incentive effect on pharmaceutical manufacturing enterprises to increase R&D investment, and this positive effect still holds after the endogeneity test and robustness test. The results of the moderating effect test indicate that government subsidies play a positive moderating role in the process of digital financial inclusion affecting enterprises’ R&D investment. Further analyses show that digital financial inclusion has a more significant role in promoting the intensity of R&D investment in pharmaceutical enterprises in private enterprises, small and medium-sized enterprises, and regions with lower levels of traditional financial development. Finally, policy suggestions are put forward according to the conclusion. Including the government to promote digital infrastructure and policy support, financial institutions to build data platforms to support pharmaceutical innovation, and enterprises to increase investment in research and development and expand financing channels to jointly promote the transformation and upgrading of the industry.

I. Khanna