Targeting the IGF-1R in prostate and colorectal cancer: reasons behind trial failure and future directions

IGF-1Rs enact a significant part in cancer growth and its progress. IGF-1R inhibitors were encouraged in the early trials, but the patients did not benefit due to the unavailability of predictive biomarkers and IGF-1R system complexity. However, the linkage between IGF-1R and cancer was reported three decades ago. This review will shed light on the IGF-1R system, targeting IGF-1R through monoclonal antibodies, reasons behind IGF-1R trial failure and future directions. This study presented that targeting IGF-1R through monoclonal antibodies is still effective in cancer treatment, and there is a need to look for future directions. Cancer patients may benefit from using mAbs that target existing and new cancer targets, evidenced by promising results. It is also essential that the academician, trial experts and pharmaceutical companies play their role in finding a treatment for this deadly disease.

Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzyTOPSIS

PurposeSupplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental uncertainty requires several procedures and considerations. The issue of decision-making in selecting the best among various qualified suppliers remains the major challenge in the pharmaceutical industry. This study investigated the multi-criteria multi-supplier decision-making process and proposed a model for supplier selection problems based on mixed-integer linear programming.Design/methodology/approachThe concept of principal component analysis (PCA) was used to reduce data dimensionality, and the four best criteria have been considered and selected. The result is subjected to decision-makers’ (DMs’) reliability test using the concept of a triangular fuzzy number (TFN). The importance of each supplier to each measure is established using fuzzy technique for order preference by similarity to an ideal solution approach, and the suppliers have ranked accordingly.FindingsThis study proposes a mixed integer linear programming model for supplier selection in a pharmaceutical company. The effectiveness of the proposed model has been demonstrated using a numerical example. The solution shows the model's applicability in making a sound decision in pharmaceutical companies in the space of reality. The model proposed is simple. Readily commercial packages such as LINDO/LINGO and GAMS can solve the model.Research limitations/implicationsThis research contributed to the systematic manner of supplier selection considering DMs’ value judgement under a fuzzy environment and is limited to the case study area. However, interested researchers can apply the study in other related manufacturing industries. However, the criteria have to be revisited to suit that system and might require varying ratings based on the experts' opinions in that field.Practical implicationsThis work suggests more insights practically by considering a realistic and precise investigation based on a real-life case study of pharmaceutical companies with six primary criteria and twenty-four sub-criteria. The study outcome will assist organizations and managers in conducting the best decision objectively by selecting the best suppliers with their various standards and terms among many available contenders in the manufacturing industry.Originality/valueIn this paper, the authors attempted to identify the most critical attributes to be preserved by the top managers (DMs) while selecting suppliers in pharmaceutical companies. The study proposed an MILP model for supplier selection in the pharmaceutical company using fuzzy TOPSIS.

Antitrust Compliance in the Pharmaceutical Industry: Problems and Prospects of Implementation

The article examines the background of legislative consolidation and the main problems of the introduction by pharmaceutical companies of a new legal institution for the prevention of violations of antimonopoly legislation — antimonopoly compliance, introduced by Federal Law No. 33-FL of March 1, 2020.The definition of the concept and a brief description of the current state and trends in the development of the pharmaceutical industry in connection with the relations of competition are given.The necessity of introducing antimonopoly compliance by pharmaceutical companies as a relatively independent part of pharmaceutical compliance as the most general (universal) tool for self-prevention of any offenses by the company itself and all its employees in connection with official activities is substantiated.The main antimonopoly risks associated with the implementation of pharmaceutical companies’ economic activities are named. Typical examples of violations of antimonopoly legislation by pharmaceutical companies are considered.The results of a sample survey of pharmaceutical industry representatives conducted by the author on their attitude to the introduction of antimonopoly compliance are presented.Proposals have been formulated to amend the Code of Administrative Offences of the Russian Federation in order to create additional incentives for the implementation of antimonopoly compliance.

Payments to key opinion leader physicians and drug sales of top pharmaceutical companies during the COVID-19 pandemic

Background: The unprecedented context of the COVID-19 pandemic poses the opportunity to study several questions in circumstances that would probably not otherwise occur. We sought to determine the dynamics of pharmaceutical company drug sales revenue, market capitalization and payments to physicians during the pandemic, focusing on payments to so-called key opinion leaders (KOLs). Methods: We analyzed the CMS Open Payments data of 15 top pharmaceutical company general payments to US physicians. We calculated total payments per year for all physicians, KOLs and 2018 KOLs in subsequent years. Drug-related fold changes in payments, drug revenues and company market capitation were calculated using Q1-2018 as reference. Yearly differences in payments, drug sales revenue and market capitalization were tested using generalized estimation equations (GEE). A double-sided p<0.05 was considered significant. Results: The analyzed dataset comprised 8,563,872 payments to 382,779 physicians. In 2020, we observed a reduction in payments to physicians and KOLs compared to prior years. The total amount per KOL physician per company also decreased for each year for KOLs and the 2018 KOLs in the subsequent years. Payments per drug, but neither drug revenues nor pharmaceutical company market capitalization, followed a downward trend in 2020 compared to prior years. GEE analysis confirmed that, compared to 2018, the decrease in payments to KOLs overall and for the top drugs of each company was statistically significant. Yet, no significant differences in drug sales revenue and market capitalization was observed. Conclusions: A substantial and significant reduction in payments to KOLs during the first fiscal year of the COVID-19 pandemic was not associated with a reduction in drug sales revenue of blockbuster drug products and the market capitalization of 15 top pharmaceutical companies. Overall, these findings suggest that a substantial part of pharmaceutical payments to KOLs do not appear to impact top drug sales revenues.

Mechanism Effect Corporate Governance and Characteristics Company on Disclosure Intellectual Capital on Registered Pharmaceutical Companies on the Indonesia Stock Exchange

The purpose of this study was to analyze the effect of the mechanism corporate governance and company characteristics to disclosure intellectual capital in pharmaceutical companies listed on the Indonesia Stock Exchange in 2015-2020. The population of this study were pharmaceutical companies listed on the Indonesia Stock Exchange in 2015-2020. The sample in this study was 6 pharmaceutical companies which were determined through purposive sampling. This study analyzes the company's annual report using the method content analysis. Data analysis was carried out by classical assumption test, hypothesis testing and multiple regression analysis methods. The results of this study indicate that the size of the board of commissioners, the number of meetings of the board of commissioners, and profitability have an effect partially or simultaneously on disclosure. intellectual capital. Meanwhile, independent commissioners, audit committees, number of audit committee meetings, company size, and leverage has no partial or simultaneous effect on disclosure intellectual capital.

Intelligent pharmaceutical patent search on a near-term gate-based quantum computer

Pharmaceutical patent analysis is the key to product protection for pharmaceutical companies. In patent claims, a Markush structure is a standard chemical structure drawing with variable substituents. Overlaps between apparently dissimilar Markush structures are nearly unrecognizable when the structures span a broad chemical space. We propose a quantum search-based method which performs an exact comparison between two non-enumerated Markush structures with a constraint satisfaction oracle. The quantum circuit is verified with a quantum simulator and the real effect of noise is estimated using a five-qubit superconductivity-based IBM quantum computer. The possibilities of measuring the correct states can be increased by improving the connectivity of the most computation intensive qubits. Depolarizing error is the most influential error. The quantum method to exactly compares two patents is hard to simulate classically and thus creates a quantum advantage in patent analysis.

Technologies of Expertise: Opioids and Pain Management’s Credibility Crisis

Journalistic accounts of the opioid crisis often paint prescription opioids as the instrument of profit-minded pharmaceutical companies who enlisted pain specialists to overprescribe addictive drugs. Broadening beyond a focus on pharmaceutical power, this article offers a comparative-historical explanation, rooted in inter- and intra-professional dynamics, of the global increase in rates of opioid prescribing. Through archival analysis and in-depth interviews with pain specialists and public-health officials in the United States and France, I explain how and why opioids emerged as the “right tool for the job” of pain relief in the 1980s and 1990s, affecting how pain science is produced, pain management is administered, and a right to pain relief is promised in different national contexts. I argue that opioids, selected and destigmatized as the technology for pain relief, helped establish a global network of pain expertise, linking a fledgling field of pain specialists to the resources of global-health governance, public-health administration, humanitarian organizations, and pharmaceutical companies. I then compare how U.S. and French pain specialists leveraged opioids to strengthen the boundaries of their emergent fields. Pain specialists’ differing degrees of autonomy in each country’s network of pain expertise shaped the extent to which opioids could dominate pain management and lead to crisis. Tracing the relationship between opioids and pain expertise, I show how technologies can drive crises of expert credibility if and when they escape the control of the networked fields that selected them.

Trust in Medicine as a Factor Conditioning Behaviors Recommended by Healthcare Experts during the COVID-19 Pandemic in Poland

Objective: Due to the COVID-19 pandemic, public health experts have faced the challenge of convincing people to change their everyday habits. This study aims to evaluate the impact of trust in medicine on Polish citizens’ adherence to recommended behaviors. Methods: An online survey was conducted on a quota sample of adult Poles (n = 1072) during the second wave of COVID-19. Results: The trust-in-medicine index was created from statements relating to trust in healthcare professionals, vaccines, and medicines. This index showed that 27.1% of respondents expressed low trust, 36.7% expressed moderate trust, and 36.3% expressed high trust. The recommended behavior index was created from nine statements. This index showed that 15.8% of respondents had low adherence, 38.2% had moderate adherence, and 46.0% had high adherence to the healthcare experts’ recommendations. One-way analysis of variance showed that people with a high trust had significantly higher scores on the recommended behavior index when compared to people with a moderate or low trust. Conclusions: This study suggests that those responsible for health policy should put more effort into building trust not only in health professionals, but also in pharmaceutical companies. We also determined the socio-demographic features of people to whom such actions of trust building should be directed.