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Medicine prices are increasing globally, including in Malaysia where previous studies show prices higher than international averages. Patient Access Scheme (PAS) is a mechanism adopted by Malaysia in 2018 to facilitate access to expensive medicines, similarly used by Italy since 2005. This study aims to compare the implementation of PAS in Malaysia and Italy.

This review systematically searched for peer-reviewed articles in PubMed, Scopus and ScienceDirect on how Italy implemented PAS system from 2012 to 2022 using the related keywords. The systematic review is reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The search identified 363 articles. A total of eight studies were included. Most of the studies found that PAS is able to control the expenditure on expensive drugs. PAS has also had several challenges, such as high administrative burden, high upfront cost and the need for good data infrastructure.

This study’s unique focus on Italy’s adoption of managed entry agreements (MEA) can provide valuable insights for Malaysia’s pricing mechanisms and access to expensive drugs. Notably, this research addresses a gap in the literature regarding the practical implications of MEA implementation in developing countries. The findings have the potential to improve access to essential medicines for Malaysian citizens while offering a fresh perspective on MEA utilization in emerging markets.

The Indian pharmaceutical industry currently faces multiple challenges, including rising costs and slowing export growth, which in turn have limited its ability to expand presence in global canvas. Given the nature of sectoral dynamics, a pharmaceutical firm must undertake huge investments in R&D to introduce product innovation, in turn enhancing market share and sustaining profit streams. The development of novel medicines, confirmed by the granting of patent rights, provides a pharma company edge over its competitors. In addition, presence of innovator firms within the industry invigorates the sectoral value chain and raises efficiency. Hence, it is important to analyze whether granting patent rights enhances the exports of pharmaceutical products in the Indian context.

The current study explored this question using a simultaneous-equation framework. Specifically, the authors use the methods developed by Davidson and MacKinnon (1993) and Greene (2003) to obtain heteroscedasticity-consistent estimates. The time-series properties of the data were further probed, and robust estimates were used to test the theory. Methods developed by Baltagi (1981) have been used further to refine the authors’ estimations.

After controlling for relevant variables, it is observed that granting of patents caused a significantly positive impact on pharmaceutical exports. Furthermore, the change in the patent administration regime had a significant impact on patent fillings, which further impacted their exportability. Compared to patents granted patents filed had a higher impact on pharmaceutical exports.

This study attempts to apply the framework developed by Goldstein and Khan (1978) with necessary modifications to suit the context of a developing country. The application of the 3SLS method to estimate the export supply equation for pharmaceutical products is a novel approach to the research question in general and to the Indian context in particular. System autocorrelation and heteroscedasticity tests were performed to refine the results further.

Biotech companies stand as key actors in pharmaceutical innovation. The high risk and long timelines inherent with their R&D investments might hinder their access to funding, potentially stifling innovation. This study aims to explore into the appeal of biotech companies to capital market investors, whose financial backing could bolster the growth of the biotechnology sector.

This paper uses a dataset of 774 US publicly listed biotech firms to investigate their risk and return characteristics by comparing them to pharmaceutical firms and a sample of matched non-biotech R&D-intensive firms over the sample period 1980–2021. Tests show that the conclusions remain consistent across diverse methodological approaches.

The paper shows that biotech companies are riskier than the average firm in the market index but outperform on a risk-adjusted basis both the market and a matched group of R&D-intensive firms. This is particularly true for large capitalization biotech, which is also shown to provide a diversification benefit by reducing the downside risk in past crisis periods.

This paper provides insight relevant to the current debate about the overall performance of the biotech industry in terms of policy changes and their impact on small, early-stage biotech firms. While small and early-stage biotech firms are playing an increasing role in scientific innovation, this study confirms their greater vulnerability to financial risks and the importance of access to capital markets in enabling those companies to survive and evolve into larger biotech.

The pandemic induced lockdown lead to supply and manufacturing disruptions that were swiftly dealt with by the Indian Pharma Industry through successful industry-government collaboration. By May 2020 production was back to normal and exports were higher than the same period in May 2019. The case deals with the processes that enabled this to happen, the policy responses and the changes that happened in the period from March 2020 to August 2020.

This study explores the relationship between market orientation (MO), marketing capabilities, competitive advantage and firm performance with a focus on productivity and growth. This study answers on how MO and capabilities can enhance the performance of a firm. The following research points have been looked into: (1) business development in uncertain times, (2) strategies that complement both business development and competitive advantage at the same time and (3) how proactive MO helps the business organization to improve performance and attain category leadership in the desired therapeutic segment.

This article is based on an intensive case study that provides a thorough description, interpretation and understanding of the case. To accomplish the given goals, a public sector firm was carefully chosen and data were gathered through interviews with managers from different levels of the case company.

Results of this study explain that the MO concept is highly effective in building the marketing capabilities and sustaining the performance. The study offers business development strategies for the businesses where product differentiation is low and price ceiling is practiced on a certain category of products. MO when combined with marketing capabilities gives the organization a competitive advantage which ultimately enhances the firm performance.

The manuscript is based on a case study representing niche and mid-sized Indian pharmaceutical company, “Indian Immunologicals Limited” (IIL, a public sector firm), that adopted MO along with competitive business strategies in highly competitive, regulated and price control therapeutic category, anti-rabies vaccine. The company with a judicious mix of business strategies, operational excellence and MO not only enhanced productivity but also market share and created new business units for future.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Trust in pharmaceutical firms has fluctuated over the years, with highs reached during the COVID-19 pandemic. Work needs to now be done to rebuild trust levels and work out boosting lived values.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

This paper aims to examine the impact of announcements related to 77 interventions by 46 listed Indian pharmaceutical firms during COVID-19 on the abnormal returns of the firms. The study also finds the variables which explain cumulative abnormal returns (CARs).

This study uses standard event methodology to compute the abnormal returns of firms announcing pharmaceutical interventions in 2020 and 2021. Besides this, the multilayer perceptron technique is applied to identify the variables that influence the CARs of the sample firms.

The results show the presence of abnormal returns of 0.64% one day before the announcement, indicating information leakage. The multilayer perceptron approach identifies five variables that explain the CARs of the sample companies, which are licensing_age, licensing_size, size, commercialization_age and approval_age.

The study contributes to the efficient market literature by revealing how firm-specific nonfinancial disclosures affect stock prices, especially in times of crisis like pandemics. Prior research focused on determining the effect of COVID-19 variables on abnormal returns. This is the first research to use artificial neural networks to determine which firm-specific variables and pharmaceutical interventions can influence CARs.

The devastating acute COVID-19 epidemic crippled the global economy in 2020. Within a month of the COVID-19 epidemic, every industry saw its stock prices plummet the most. Ending the COVID-19 pandemic will need equitable access to safe and effective vaccinations. This study aims to look at the link between COVID-19 vaccination and the stock markets for health and pharmaceutical sector.

The researchers used a mean-adjusted return model and event research approach to figure out how the first dose of the COVID-19 vaccine affects health and pharmaceutical sector stock market returns.

The evidence-based outcome indicates that immunisation announcement affects health and pharmaceutical company returns. Furthermore, the study concludes that the health and pharmaceutical industry is inefficient for a short period of time, but after 41 days, the sector absorbs the noisy information.

Since the outbreak, the development of COVID-19 vaccines has been a key focus of shareholders and investors. This study is unique in that it investigates the effect of the first dosage of SARS-CoV-2 vaccination on equity returns in the health and pharmaceutical industries, and it is likely to make a substantial contribution to the capital market literature on event methodology.

The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.

We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.

Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.

These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.

Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.

The study focuses on drug safety regulation capture, reveals the inner mechanism and evolutionary characteristics of drug safety regulation capture and provides suggestions for effective regulation by pharmacovigilance.

The article introduces prospect theory into the game strategy analysis of drug safety events, constructs a benefit perception matrix based on psychological perception and analyzes the risk selection strategies and constraints on stable outcomes for both drug companies and drug regulatory authorities. Moreover, simulation was used to analyze the choice of results of different parameters on the game strategy.

The results found that the system does not have a stable equilibrium strategy under the role of cognitive psychology. The risk transfer coefficient, penalty cost, risk loss, regulatory benefit, regulatory success probability and risk discount coefficient directly acted in the direction of system evolution toward the system stable strategy. There is a critical effect on the behavioral strategies of drug manufacturers and drug supervisors, which exceeds a certain intensity before the behavioral strategies in repeated games tend to stabilize.

In this article, the authors constructed the perceived benefit matrix through the prospect value function to analyze the behavioral evolution game strategies of drug companies and FDA in the regulatory process, and to evaluate the evolution law of each factor.