Biopharmaceutical Sector Research Articles

Characterization of host cell proteins in the downstream process of plant-Based biologics using LC-MS profiling

Host cell proteins (HCPs) are process-related impurities found in biopharmaceutical products that can impair their safety and efficacy. While ELISA has traditionally been employed to quantify HCPs, LC-MS emerges as a powerful alternative for precise identification of individual HCPs. In this study, we used LC-MS for profiling HCPs from Nicotiana benthamiana-derived biopharmaceuticals. Our approach involved rigorous false discovery rate control to ensure data integrity and reliability. Comprehensive analysis revealed a systematic reduction of HCPs following purification, demonstrating the efficiency of purification processes in removing non-essential proteins. Furthermore, LC-MS enabled the identification of potential contaminants, refining purification strategies and improving product purity and integrity. Our findings highlight the potential of LC-MS as an analytical tool for HCPs analysis in biopharmaceutical development and manufacturing. By providing detailed insights into HCPs profiles and contaminants, LC-MS facilitates informed decision-making in downstream processing steps, benefiting product quality, patient safety, and the biopharmaceutical sector.

Analyzing Barriers to Entry in the Biopharmaceutical Sector: an Entrepreneurial Perspective

Analyzing Barriers to Entry in the Biopharmaceutical Sector: an Entrepreneurial Perspective

A Review of Artificial Intelligence and Machine Learning in Product Life Cycle Management.

The pursuit of harnessing data for knowledge creation has been an enduring quest, with the advent of machine learning and artificial intelligence (AI) marking significant milestones in this journey. Machine Learning (ML), a subset of AI, emerged as the practice of employing mathematical models to enable computers to learn and improve autonomously based on their experiences. In the pharmaceutical and biopharmaceutical sectors, a significant portion of manufacturing data remains untapped or insufficient for practical use. Recognizing the potential advantages of leveraging available data for process design and optimization, manufacturers face the daunting challenge of data utilization. Diverse proprietary data formats and parallel data generation systems compound the complexity. The transition to Pharma 4.0 necessitates a paradigm shift in data capture for manufacturing and process operations. This paper highlights the pivotal role of artificial intelligence in converting process data into actionable knowledge to support critical functions throughout the whole process life cycle. Furthermore, it underscores the importance of maintaining compliance with data integrity guidelines, as mandated by regulatory bodies globally. Embracing AI-driven transformations is a crucial step toward shaping the future of the pharmaceutical industry, ensuring its competitiveness and resilience in an evolving landscape.

A factor score clustering approach to analyze the biopharmaceutical sector in the Chinese market during COVID-19

The biopharmaceutical sector is of considerable interest during the COVID-19 pandemic. This study aims to investigate the biopharmaceutical sector using the Shenwan Industry Classification and provides insights into investment strategies. We combine factor and cluster analyses to reduce data dimensions and detect their latent similarities. Specifically, the biopharmaceutical sector is divided into six categories based on second-level industry classification. It is observed that medical devices, medical services, biological products, and chemical pharmaceuticals maintained their upward tendency, while Chinese medicine and pharmaceutical commerce declined slightly. We also develop optimal investment strategies using various metrics for different investor types.

The Combined Effects of Financial and Market Indicators on the Valuation of New Listings: Evidence from the Biopharmaceutical Sector

This study confirms that financial and market data have a significant impact on the valuation of newly listed companies, especially in the biopharmaceutical industry. Using multiple linear regression models, this paper found significant differences in the impact of EBITGR and EBITDAGR on price-to-earnings ratio (P/E Ratio) across years. Other indicators such as Total Asset Turnover, Return on Assets (ROA) and Debt to Equity Ratio (D/E Ratio) have weaker explanatory power and unstable influence. In addition, fluctuations in market valuations of listed companies are influenced by market sentiment and the macroeconomic policy environment. In high-growth, high-risk industries such as biopharmaceuticals, regulatory policies and listing structure reforms in the market can cause structural changes in model performance. At the same time, changes in market sentiment and regulation can also affect the explanatory power of financial indicators to some extent. Further analyses showed that market preferences for valuation changed over time during the study period, especially when the market moved significantly, driven by regulatory policy and the external environment. This makes the conclusions of the study's findings subject to uncertainty in different market environments. Overall, this study reveals a number of key factors affecting the market valuation of newly listed companies and highlights the importance of the interaction between market data and financial indicators. In future research, more attention should be paid to the role of different time periods, market conditions and industry characteristics to avoid potential valuation traps and provide more informative support to market investors and managers.

The Combined Effects of Financial and Market Indicators on the Valuation of New Listings: Evidence from the Biopharmaceutical Sector

This study confirms that financial and market data have a significant impact on the valuation of newly listed companies, especially in the biopharmaceutical industry. Using multiple linear regression models, this paper found significant differences in the impact of EBITGR and EBITDAGR on price-to-earnings ratio (P/E Ratio) across years. Other indicators such as Total Asset Turnover, Return on Assets (ROA) and Debt to Equity Ratio (D/E Ratio) have weaker explanatory power and unstable influence. In addition, fluctuations in market valuations of listed companies are influenced by market sentiment and the macroeconomic policy environment. In high-growth, high-risk industries such as biopharmaceuticals, regulatory policies and listing structure reforms in the market can cause structural changes in model performance. At the same time, changes in market sentiment and regulation can also affect the explanatory power of financial indicators to some extent. Further analyses showed that market preferences for valuation changed over time during the study period, especially when the market moved significantly, driven by regulatory policy and the external environment. This makes the conclusions of the study's findings subject to uncertainty in different market environments. Overall, this study reveals a number of key factors affecting the market valuation of newly listed companies and highlights the importance of the interaction between market data and financial indicators. In future research, more attention should be paid to the role of different time periods, market conditions and industry characteristics to avoid potential valuation traps and provide more informative support to market investors and managers.

How a timely policy contributes to technological capability building: insights from Iran’s biopharmaceutical sector

Abstract Building technological capabilities is influenced by different factors, notably policies. This paper explains the co-evolution of policies, i.e. policy tools, on the technological capabilities in Iran’s biopharmaceutical sector from 1995 to 2022. By adopting a qualitative research method, we gathered primary data through thirty-nine semi-structured as well as secondary data from reports and statistics. This paper explains technological capabilities enhancement from operational capabilities to innovative capabilities based on our proposed framework, which includes six levels. While the lack of an efficient policy tools, until the mid-2000s, was decisive in the inertia of biopharmaceutical sector capabilities, a proactive policy tools in recent years led to considerable promising results in terms of manufacturing and exporting advanced biosimilar products. Our findings shed light on the role of government support in the acceleration and directionality of technological capabilities building. Achieving advanced levels of technological capabilities requires learning, international collaboration, and export-oriented policies.

Microencapsulation of ultrasound-assisted phenolic extracts of sugar maple leaves: Characterization, in vitro gastrointestinal digestion, and storage stability

Sugar maple leaves (SML), usually considered residue plant biomass and discarded accordingly, contain a considerable amount of phenolic antioxidants. In this study, SML phenolics were extracted employing both advanced (homogenization pretreated ultrasound-assisted extraction) and conventional (maceration) methods followed by their encapsulation by freeze drying and spray drying using a combination of maltodextrin and gum arabic as coating agents. Detailed physicochemical analyses revealed that the encapsulated microparticles had high solubility (>90 %) and encapsulation efficiency (>95 %), acceptable thermal stability with good handling properties. Phenolic compounds were completely released from microparticles during simulated gastric conditions. The microparticles influenced the bioaccessibility of more than 43 % of the phenolic fraction in the intestinal phase. The antioxidant capacity of the microparticles was preserved during storage. These findings suggest the effectiveness of the microencapsulation process for producing high quality microparticles of SML phenolic extracts and the possibility of their use in the food, nutraceutical, bio-pharmaceutical sectors.

How does news affect biopharma stock prices?: An event study.

We investigate the impact of information on biopharmaceutical stock prices via an event study encompassing 503,107 news releases from 1,012 companies. We distinguish between pharmaceutical and biotechnology companies, and apply three asset pricing models to estimate their abnormal returns. Acquisition-related news yields the highest positive return, while drug-development setbacks trigger significant negative returns. We also find that biotechnology companies have larger means and standard deviations of abnormal returns, while the abnormal returns of pharmaceutical companies are influenced by more general financial news. To better understand the empirical properties of price movement dynamics, we regress abnormal returns on market capitalization and a sub-industry indicator variable to distinguish biotechnology and pharmaceutical companies, and find that biopharma companies with larger capitalization generally experience lower magnitude of abnormal returns in response to events. Using longer event windows, we show that news related to acquisitions and clinical trials are the sources of potential news leakage. We expect this study to provide valuable insights into how diverse news types affect market perceptions and stock valuations, particularly in the volatile and information-sensitive biopharmaceutical sector, thus aiding stakeholders in making informed investment and strategic decisions.

Book Review: Łukasz Puślecki, Cooperation in the Biopharmaceutical Sector in the Countries of Central and Eastern Europe – Diagnosis, Challenges and Perspectives CeDeWu, Warsaw 2023

Book Review: Łukasz Puślecki, Cooperation in the Biopharmaceutical Sector in the Countries of Central and Eastern Europe – Diagnosis, Challenges and Perspectives CeDeWu, Warsaw 2023

The Impact of the Deregulation of Covid-19 on the Pharmaceutical Industry

The current COVID-19 has lasted for a long time, and the Chinese government has relaxed the control of the pandemic after many considerations. Numerous researches about the COVID-19's effects on the economy and business are currently available. But few studies are on the pharmaceutical industry and the Deregulation. Therefore, this paper selects the Pharmaceutical and Biological Full Benefit as the research object. And then uses the ARIMA model to perform time series fitting and prediction of the closing price series in the past period. By comparing the predicted and real values, how the Deregulation affected the stock price of the biopharmaceutical sector could be determined. After modeling analysis, it is concluded that a positive effect has been produced by the Deregulation on the stock price of the pharmaceutical industry. Further study shows that there is a short-term lag in the impact, and the relative growth rate is not large. And the impact has been observed with certain short-term nature through the prediction results. This paper innovatively uses stock price fluctuations as an insertion point to explore the impact of the Deregulation on the pharmaceutical industry, which has profound practical guiding significance. For Chinese policy makers, it is suggested that the country should cooperate with the improvement and upgrading of the pharmaceutical industry. For investors, it is suggested that they should maintain a more stable and positive wait-and-see attitude towards the pharmaceutical industry.

An Empirical Analysis of Sacha Inchi (Plantae: Plukenetia volubilis L.) Seed Proteins and Their Applications in the Food and Biopharmaceutical Industries.

Sacha Inchi (Plukenetia volubilis L.) is a plant native in the Amazon rainforest in South America known for its edible seeds, which are rich in lipids, proteins, vitamin E, polyphenols, minerals, and amino acids. Rural communities in developing nations have been using this plant for its health benefits, including as a topical cream for rejuvenating and revitalising skin and as a treatment for muscle pain and rheumatism. Although Sacha Inchi oil has been applied topically to soften skin, treat skin diseases, and heal wounds, its protein-rich seeds have not yet received proper attention for extensive investigation. Proteins in Sacha Inchi seeds are generally known to have antioxidant and antifungal activities and are extensively used nowadays in making protein-rich food alternatives worldwide. Notably, large-scale use of seed proteins has begun in nanoparticle and biofusion technologies related to the human health-benefitting sector. To extract and identify their proteins, the current study examined Sacha Inchi seeds collected from the Malaysian state of Kedah. Our analysis revealed a protein concentration of 73.8 ± 0.002mg/g of freeze-dried seed flour. Employing liquid chromatography-tandem mass spectrometry (LC-MS/MS) and PEAKS studio analysis, we identified 217 proteins in the seed extract, including 152 with known proteins and 65 unknown proteins. This study marks a significant step towards comprehensively investigating the protein composition of Sacha Inchi seeds and elucidating their potential applications in the food and biopharmaceutical sectors. Our discoveries not only enhance our knowledge of Sacha Inchi's nutritional characteristics but also pave the way for prospective research and innovative advancements in the realms of functional food and health-related domains.

Biopharmaceutical Financialization and Public Funding of Medical Countermeasures (MCMs) in Canada During the COVID-19 Pandemic.

Analysing the Canadian government's efforts to support the development of COVID-19 "medical countermeasures" (MCMs), this article seeks insights into political economy as a driver of pandemic response. We explore whether Canadian public funding policy during the pandemic involved departures from established practices of financialisation in biopharmaceutical research and development (R&D), including the dominance of private sector involvement in an intellectual property (IP) intensive approach to innovation underscoring profit, and governance opacity. We interrogate public funding for MCMs by analyzing how much the Government of Canada (GoC) spent, how those funds were allocated, on what terms, and to whom. We identify the funding institutions, and the funds awarded between February 10, 2020, and March 31, 2021, to support the research, development, and manufacturing of MCMs, including diagnostics, vaccines, therapeutics, and information about clinical management and virus transmission. To collect these data, we conducted searches on the Internet, public data repositories, and filed several requests under the Access to Information Act (1985). Subsequently, we carried out a document-based analysis of electronically accessible research contracts, proposals, grant calls, and policy announcements. The GoC announced CAD$ 1.4 billion for research, development and manufacturing of COVID-19 MCMs. Fully 68% (CAD$ 959 million) of the announced public funding was channelled to investment in private sector firms. Canadian public funding showed a consistent focus on early and late stage development of COVID-19 MCMs and the expansion of biopharmaceutical manufacturing capacity. Assessing whether Canada's investments into developing COVID-19 MCMs safeguard affordable and transparent access to the products of publicly funded research, we found that access policies on IP management, sharing of clinical data, affordability and availability were not systematic, consistent, or transparent, and few, if any, mechanisms ensured long-term sustainability. Beyond incremental change in policy goals, such as public investment in domestic biomanufacturing, the features of Canadian public policies endorsing financialization in the biopharmaceutical sector remained largely unchanged during the pandemic.

Fast-Training Deep Learning Algorithm for Multiplex Quantification of Mammalian Bioproduction Metabolites via Contactless Short-Wave Infrared Hyperspectral Sensing.

Within the biopharmaceutical sector, there exists the need for a contactless multiplex sensor, which can accurately detect metabolite levels in real time for precise feedback control of a bioreactor environment. Reported spectral sensors in the literature only work when fully submerged in the bioreactor and are subject to probe fouling due to a cell debris buildup. The use of a short-wave infrared (SWIR) hyperspectral (HS) cam era allows for efficient, fully contactless collection of large spectral datasets for metabolite quantification. Here, we report the development of an interpretable deep learning system, a convolution metabolite regression (CMR) approach that detects glucose and lactate concentrations using label-free contactless HS images of cell-free spent media samples from Chinese hamster ovary (CHO) cell growth flasks. Using a dataset of <500 HS images, these CMR algorithms achieved a competitive test root-mean-square error (RMSE) performance of glucose quantification within 27 mg/dL and lactate quantification within 20 mg/dL. Conventional Raman spectroscopy probes report a validation performance of 26 and 18 mg/dL for glucose and lactate, respectively. The CMR system trains within 10 epochs and uses a convolution encoder with a sparse bottleneck regression layer to pick the best-performing filters learned by CMR. Each of these filters is combined with existing interpretable models to produce a metabolite sensing system that automatically removes spurious predictions. Collectively, this work will advance the safe and efficient adoption of contactless deep learning sensing systems for fine control of a variety of bioreactor environments.

Design of a process development workflow and control strategy for single-pass tangential flow filtration and implementation for integrated and continuous biomanufacturing

Integrated and continuous biomanufacturing (ICB) offers several advantages compared to traditional batch methods, prompting the development of novel technologies and infrastructure for the implementation of ICB in the biopharmaceutical sector. However, most of the advancements have been in the early stages of the purification process, with relatively fewer advancements in the final filtration steps. This work focuses on some of the last major unit operations of a traditional bioprocess: ultrafiltration and diafiltration. Our proposed technological solution involves robust control algorithms for (1) precisely maintaining consistent protein concentration in single-pass ultrafiltration (SP-UF) and (2) achieving the targeted buffer exchange in single-pass diafiltration (SP-DF). Specifically, we adopted an integrated experimental, modeling, and simulation approach to develop a robust process understanding of SP-UF/SP-DF operations via semi-empirical maximum permeate flux models. These models were employed in the optimization of key design variables such as the filter area and the development of control strategies. Finally, we demonstrate the applicability of our proposed solution by operating a single-pass tangential flow filtration (SP-TFF) system in an integrated and continuous manner for six days. We believe that this work is instrumental for the successful realization of SP-UF/SP-DF operations in both batch and ICB processes.

Perceptions of types, influences, and how select Central European entrepreneurship ecosystems developed in the biopharmaceutical sector

Perceptions of types, influences, and how select Central European entrepreneurship ecosystems developed in the biopharmaceutical sector

Obstetrics and Gynecology - Femtech: how digital technologies are serving women's healthcare

Over the past ten years, a growing number of technological tools have been developed to improve women's health and well-being, grouped under the name FemTech. This growing field has the potential to improve gynecological care and covers solutions that are less invasive and more personalized to the patient's needs. Thanks to its world-renowned universities and hospitals, its high involvement in the research field and its strong biopharmaceutical sector, Romandy has demonstrated the rapid rise of start-ups dedicated to women's health, thus providing a promising landscape in the FemTech industry. Several Swiss FemTech companies yield innovative solutions related to fertility, menopause and gynecological instruments. This article aims to present the emerging Femtech companies in Romandy over the past years and their use among young women.

The industry of therapeutic monoclonal antibodies in Brazil: Public policies as instruments of technology upgrading

AbstractTherapeutic monoclonal antibodies (MAbs) are biopharmaceuticals prescribed in oncology, rheumatology, and for other chronic and autoimmune diseases. Over the last decade, the demand for MAbs grew significantly in developing countries like Brazil, concomitant to the restructuring of the global biopharmaceutical industry, opening windows of opportunities for catching-up economies. This paper aims to analyze the capacity of a public policy, the so-called Production Development Partnership Program (PDPP), to encourage the generation of national capabilities to the local biopharmaceutical industry and technological upgrading in the biopharmaceutical sector in Brazil. It is a case study supported by qualitative data from twenty-three interviews. By focusing on technology transfer processes rather than on more complex strategies of technological learning and upgrading in domestic agents, the impact of PDPP has been marginal. We draw insights from this empirical appraisal to outline some lessons and challenges involved in the implementation of technology-upgrading policies in developing countries.

Current situation and future development of the biopharmaceutical industry in China: A mixed-method study

Introduction: The biomedical industry has grown significantly both globally and in China; however, there are still challenges. This study aimed at evaluating the biopharmaceutical sector of China, in terms of ability to innovate, current sales volume, investment, and R&D expenditure, as well as providing a case study detailing the progress and challenges of the industry in Shaanxi province. Method: A cross-sectional mixed-method study design was used to generate a comprehensive profile of the nature of biopharmaceutical innovation capacity and development in China by triangulating country-wide survey and interview data from Shaanxi province. Only biopharmaceutical companies that are currently marketing or conducting research and development were eligible for inclusion, and Shaanxi province was selected for conducting the interviews. Categorical and continuous variables were analyzed descriptively. Interviews were thematically analyzed by using NVivo version 12. Results: The analysis includes responses from 77 biopharmaceutical enterprises; the majority (36, 46.8%) are in Eastern China, followed by 26 (33.8%) in Central China. In 2018, the total sales of biological products amounted to 26.28 billion yuan, and in 2019, a slight increase was observed (30.34 billion); the amount doubled in 2020 to about 67.91 billion yuan. The top three biopharmaceutical products on sale in 2020 were Camrelizumab (5.14 billion yuan), human albumin (4.56 billion yuan), and human immunoglobulin for injection (3.78 billion yuan). Expenditure on R&D has also increased; it amounted to 1657.7 million yuan in 2018, which more than doubled in 2019 to 3572.1 million yuan and further increased to 5857.7 million yuan in 2020. Nonetheless, the progress is not uniform across all provinces, as shown from the results from Shaanxi province, because of lack of local government policies that will impact on the funding, incentives, and market share that motivate the producers. Conclusion: China’s biopharmaceutical industry has expand significantly. The increase in sales indicates that there is an increase in demand for biologicals; moreover, R&D funding is increasing. These are key indicators that influence innovation and development. However, the sector’s capacity to innovate and develop needs to be improved, particularly in the western region, where research and production are relatively weak.

Academic, Сommercialization and Societal Effects of Joint Research

The work investigates the effects that a specific science industry collaboration scheme, joint research, generates in three areas, such as: production of academic activities, scientific knowledge commercialization and society at large. It is an in-depth work on joint research in a developing country that covers three different types of effects. The work highlights the specific industrial contributions that make it possible such effects to be verified, with special attention to societal effects, an aspect rarely present in the literature. Based on some dimensions that recent literature has identified and where more empirical evidence is needed, a multiple case study has been carried out through the selection of three public private collaborations in Argentine biopharmaceutical sector responding to joint research characteristics. Among the main findings, the identification of the different ways in which relationship with industry allows science: to intensify its publication activity, by having more resources and identifying new thematic niches to publish; to improve teaching, using co-generated knowledge and shared equipment; to expand its research agenda both towards applied topics and towards more basic ones. Likewise, relationship with industry allows knowledge generation that, in addition to being central in the creation of start-ups and patents, also contribute to perform new services of commercial nature. Finally, joint research generates effects that benefit society in general, through cheaper domestic diagnostic or therapeutic solutions improving public health.