Academic literature on the topic 'Pharmaceutical fraud'

Abstract Abstract 4275 Introduction: Annually, $82 billion to $272 billion is reportedly lost to federal health care fraud. Between 1996 and 2005, 379 federal health care fraud cases initiated by qui tam relators (“whistle blowers”) concluded, resulting in $9.3 billion in recoveries. Of these, pharmaceutical companies accounted for 13 cases (False Claims Act (FCA) cases, the primary statute invoked in health care fraud and abuse), but $3.9 billion of recoveries (4% of the cases and 39% of the financial recoveries). We report concluded FCA cases involving pharmaceutical manufacturers between 2006 and 2011. Oncology accounts for the largest per cent of total pharmaceutical expenditures. Over 90% of all new cancer pharmaceuticals cost > $20,000 for 12-weeks of treatment. Methods: Websites for the Department of Justice (DOJ), Taxpayers Against Fraud, Health and Human Services Inspector General's Office, Health Care Fraud and Abuse Control Project, and Lexis/Nexis were queried for pharmaceutical FCA cases (2006 to 2011). Results: Between 2006 and 2011, the DOJ closed 54 cases with pharmaceutical FCA violations, 38 with and 16 without qui tam relators, accounting for recoveries of $11.3 billion (mean $296 million) and $2.6 billion (mean, $165 million), respectively. Illegal marketing is the most common fraud allegations invoked against pharmaceutical manufacturers (19 cases). Pharmaceutical manufacturers accounted for 31% of total FCA cases, and 71.5% of total FCA recoveries (Table 1). Conclusion: Since the DOJ's shift of focus to pharmaceutical corporations in 2001, the trend has intensified, with virtually every large pharmaceutical corporation settling at least one FCA case. Pharmaceutical cases now account for 31% of the federal fraud cases and 71% of the financial recoveries. Fraud and abuse may be an important component of the high costs of cancer care in the United States. Moreover, unless fundamental changes occur, the pharmaceutical industry will continue to be the main FCA investigative target as this sector has the deepest pockets and is the health care sector most resistant to deterrence. Disclosures: No relevant conflicts of interest to declare.

The financial fraud of Kangmei Pharmaceutical was exposed, and the scale of financial fraud reached the largest in the history of A-shares, which is shocking. On November 17, 2021, the Intermediate People’s Court of Foshan City, Guangdong Province publicly pronounced its judgment on the case of 12 people including Kangmei Pharmaceutical’s former chairman and manager of the China Securities Regulatory Commission, Ma Xingtian, for manipulating the securities market. There has been extensive discussion in the industry. This article will firstly sort out the whole story of the financial fraud incident in Kangmei Pharmaceutical, and analyze the means of financial fraud in Kangmei Pharmaceutical; secondly, it will focus on the audit failure and the failure of independent directors in the financial fraud case and the reasons; Finally, some suggestions are put forward from three aspects: Strengthen the internalgovernance, improve the external governance and the independent director system.

The case of financial fraud of Kangmei Pharmaceutical is known as one of the most serious fraud cases ever in A-share. This paper analyzes the cause, course, and result of the financial fraud of Kangmei Pharmaceutical. Data analysis of the share price of Kangmei Pharmaceutical is conducted to investigate the impact of this incident on the market. The case study method, information asymmetry theory, and principal-agent theory are used to illustrate the impact of independent directors in the financial fraud case and the insights from the fraud case of Kangmei Pharmaceutical.

According to the CPA-Journal Fraud Aware report, small businesses (classified as those with less than 100 employees) suffer from fraud more frequently than large organizations and are hit by higher average losses. The purpose of this research was to initially assess the fraud level of a pharmaceutical distributor in Mandaue City. The participating business in this study was a pharmaceutical distributor of medicines. Descriptive design and simple statistics were used in this research. The organization had 11 to 50 employees. The assessment was only a guiding tool to assess the level of fraud, not the existence of fraud in the subject of the study. The fraud risk level was 66.88%. This fraud level meant that the level of fraud of business was moderate. This analysis was based on Williams and Kollar (2013). The controls needed improvement. In the analysis of the second-problem statement, the fraud risk level was moderate. Indeed, moderate risk meant improvement on the internal controls because only the majority of the controls were adhered by the management of the business leaving the rest substantially unattended. Thus, emphasis on certain accounting controls can lower the fraud risk of the business. In general, the recommendations aimed either to correct existing business practices or to enforce the implementation of business controls embodied in the tool used in the study.

Since the case of Kangmei Pharmaceutical Co.,Ltd., financial fraud in the pharmaceutical industry has received increasing attention from all parties in society, and financial fraud in listed companies has an important impact on the sustainable and healthy development of the capital market. Taking the four-year-long financial fraud of Xinjiang Ready Health Industry Co.,Ltd. as an example, this paper analyzes the pressure, opportunities and excuses of financial fraud of this enterprise by applying the fraud triangle theory, and finally puts forward governance suggestions from four aspects: improving corporate governance structure of the company, enhancing the function of auditors and strengthening the effectiveness of regulatory departments to punish financial fraud.

This study aims to examine the effect of internal control, independence, whistleblowing system, anti-fraud awareness, and integrity on fraud prevention at PT Inna Pharmaceutical Industry. This research was conducted using quantitative methods. The data used in this study is primary data. The population used in this study were employees who worked at PT Inna Pharmaceutical Industry in 2022. A total of 69 respondents were selected using the proposive sampling method. The analysis technique in this research is multiple linear regression analysis. The results of hypothesis testing in this study indicate that internal control, independence, and the whistleblowing system have a positive effect on fraud prevention. Meanwhile, anti-fraud awareness and integrity have a significant positive effect on fraud prevention.

In recent years, China's capital market has continued to develop. However, some companies are still fabricating business facts in pursuit of illegal interests, resulting in more and more common financial fraud under the new "Securities Law". Therefore, this paper takes Kangmei Pharmaceutical as the research object, and sorts out the cases of corporate financial fraud as a whole. The inventory and monetary funds are used to analyze its counterfeiting methods. Subsequently, risk factor theory is used to analyze the fraud motivation of Kangmei Pharmaceutical. In general, this paper puts forward suggestions on the prevention and management of financial fraud for listed companies in my country, which provides necessary guarantees for maintaining the market environment and strengthening corporate supervision.

The pressure of the global competition, continuously asking for lower costs and improved productivity, is forcing companies to seek global supply chains to cut production costs down. As a result, it is becoming more and more difficult to accurately monitor each step of a production process and to protect products from economically motivated fraud, adulterations and counterfeiting. In such context, traditional methods for product quality characterization, such as lab assays, are expensive, destructive, time-consuming, and for these reasons they have become inadequate in several applications. On the other hand, other approaches, such as absorption spectroscopy and computer vision, have been gaining much attention in the last decade, successfully contributing to speed up and automate the quality assessment exercise. Statistical modeling tools, particularly latent variable models (LVMs), are usually employed to exploit the information embedded in the large amount of highly correlated data (spectra and images) that absorption spectroscopy and computer vision generate. In the food and pharmaceutical sectors, product quality assessment still relies mainly on the judgment (of product color, odor, form, taste, etc.) of a panel of trained experts. Although the number of applications of LVMs as predictive tools for product quality monitoring is growing in these sectors, the use of LVMs for product quality assessment is usually tailored to each application, and general approaches to product quality assessment based on LVMs are lacking. The main objective of the research presented in this Dissertation is to overcome some of the limitations that hinder the diffusion of LVM tools in the food and pharmaceutical industrial practice. Three main strategies for product quality assessment are explored, namely the use of computer vision, the use of absorption spectroscopy, and the possibility of combining the information derived from different analytical instruments. With respect to the use of computer vision systems, the problem of maintaining such systems is discussed. Computer vision systems are deemed to be quick, accurate, objective and able to return reproducible results. However, likewise all other measurement systems, they need to be maintained. Alterations or failures (e.g. of the illuminating system or of the camera sensors) can dramatically affect measurement reproducibility, leading to a wrong product quality characterization. The problem of how to detect and manage these alterations or failures is discussed through a pharmaceutical engineering case study. General strategies are proposed to adapt a quality assessment model, which has been calibrated under certain environmental conditions, to new conditions. Results show that long downtime periods, which may be necessary to recalibrate the quality assessment model after a failure of the camera or of the lighting system, can be significantly reduced. Additionally, it is shown how image analysis can be effectively used not only to characterize the quality of a product, but also to improve the understanding on the production process (e.g., for troubleshooting or optimization purposes). In a specific pharmaceutical application, image analysis is used to investigate the causes leading to the erosion of tablets, allowing one to evaluate the effect of different physical phenomena occurring in the film-coating process. Additionally, the model relating the process conditions to the tablets quality is shown to be useful for process monitoring purposes. With respect to the use of absorption spectroscopy, a novel methodology to preprocess and classify spectral data is proposed. Traditionally, LVMs are built after some preprocessing of the raw spectra, and the optimal preprocessing strategy is chosen trough a time consuming trial-and-error procedure. Results from three different food engineering case studies show that the proposed methodology performs similarly to other existing approaches, but it uses a sequence of totally automated preprocessing steps, with no need for trial-and-error searches. Especially in the food industry, LVMs are usually tailored on the specific product being analyzed. For instance, for the detection of the fresh/frozen-thawed substitution fraud in fish fillets, a model is calibrated for each fish species possibly subject to substitution. This Dissertation considers a different approach: some strategies are proposed to design a multi-species, and possibly species-independent, classification model to detect this substitution fraud. The most promising strategy decomposes the information embedded in the spectral data using a single model, and it is shown to return the same overall accuracy of traditional approaches that employ one classification model for each species under investigation. Finally, with respect to the use of data fusion, it is shown how to effectively combine the information derived from different analytical instruments (such as spectrometers, digital cameras, texture analyzers, etc.) to enhance product quality characterization. Results on two food engineering case studies show that fusing the available information, rather than using them separately, improves the ability of assessing product quality.
In un sistema economico globalizzato come quello in cui viviamo, garantire elevati standard in termini di qualità di prodotto costituisce per ogni azienda produttiva un fattore di successo. Monitorare in modo accurato la qualità del prodotto lungo tutti gli stadi della filiera produttiva, tuttavia, è divenuto progressivamente più complesso a causa della dimensione globale che quest’ultima ha assunto. É questo un effetto dei fenomeni di delocalizzazione della produzione, legati alla necessità delle aziende di non perdere quote di mercato a discapito di paesi emergenti caratterizzati da costi di produzione inferiori. In un tal sistema, aumenta anche il rischio di frodi, adulterazioni e contraffazioni del prodotto. Per certe categorie di prodotti, come quelli alimentari e farmaceutici, tali attività non solo danneggiano i consumatori dal punto di vista economico, ma possono anche causare seri problemi di salute. Nonostante la grande importanza del monitorare la qualità di prodotto, a livello industriale si è ancora lontani da un sistema che permetta di caratterizzarla in modo rapido, economico, non invasivo (e quindi utilizzabile in tempo reale), riproducibile e multivariato (cioè in grado di quantificare contemporaneamente più parametri di qualità). Le tecniche che si sono dimostrate più promettenti in tal senso sono la spettroscopia d’assorbimento nella regione del visibile e del vicino infrarosso e l’analisi d’immagine. Per analizzare la moltitudine di dati (spettri e immagini) caratterizzati da forti correlazioni che queste generano, è necessario ricorrere a tecniche statistiche apposite, in particolare i modelli a variabili latenti (LVM, latent variable models). Tali tecniche, che sono pensate per trattare tali tipologie di dati, nascono dall’assunto che un sistema possa essere descritto mediante pochi fattori (detti anche variabili latenti) esprimibili come combinazione lineare delle variabili originali e interpretabili sulla base dei fenomeni chimico/fisici che interessano il sistema. Il numero di applicazioni di LVM nel campo della caratterizzazione di prodotti alimentari e farmaceutici è cresciuto rapidamente negli ultimi anni. La maggior parte dei contributi pubblicati, tuttavia, offre soluzioni a specifici problemi anziché fornire approcci generali. L’obiettivo di questa Dissertazione è quello di superare alcune delle limitazioni esistenti al fine di favorire la diffusione di questi strumenti nella comune pratica industriale. La ricerca presentata si suddivide in tre macro aree di applicazione, che si differenziano a seconda della tecnica utilizzata per caratterizzare la qualità di prodotto, e cioè l’analisi d’immagine, la spettroscopia, e la fusione di dati (data fusion), cioè la combinazione delle informazioni provenienti da più strumenti analitici. Per ciascuna di queste aree, l’efficacia della modellazione a variabili latenti viene dimostrata applicando i modelli in diversi casi studio di tipo industriale o di laboratorio. Con riferimento all’analisi d’immagine, vengono proposte applicazioni nel campo farmaceutico. Nel Capitolo 3, l’analisi d’immagine viene utilizzata per il miglioramento della comprensione di un processo industriale di rivestimento di compresse. In tale processo la qualità finale del prodotto, che è legata all’omogeneità del rivestimento e al grado di erosione superficiale, viene tradizionalmente valutata da un panel di esperti, che necessariamente fornisce un giudizio soggettivo e poco riproducibile. Inizialmente, il Capitolo discute come, a partire da immagini del prodotto finito, sia possibile valutare in modo quantitativo e riproducibile i parametri di qualità. Le metriche sviluppate vengono quindi utilizzate per il troubleshooting del processo stesso, con il fine di indagare il meccanismo che porta all’erosione superficiale. A tal scopo, le metriche vengono correlate ai parametri di processo tramite un modello a variabili latenti, e i parametri del modello vengono utilizzati per definire le condizioni operative ottimali da utilizzare per garantire un prodotto in specifica. Il Capitolo 4, usando ancora come pretesto un processo di rivestimento di compresse, discute in modo critico il problema della riproducibilità dei risultati ottenuti tramite analisi d’immagine. Tale riproducibilità, infatti, è garantita solamente se le condizioni sperimentali utilizzate per raccogliere le immagini destinate alla calibrazione del modello di stima della qualità vengono mantenute inalterate. Tali condizioni includono il sistema di illuminazione e la fotocamera stessa. Viene proposto innanzitutto un modello per il monitoraggio dello stato dell’apparato sperimentale, da utilizzare ogniqualvolta viene avviata una campagna di controllo qualità e basato semplicemente sull’acquisizione di un’immagine di standard colorati. In caso venga rilevato un cambiamento, viene proposta una strategia per adattare il modello di stima della qualità alle nuove condizioni. I risultati dimostrano l’efficacia della strategia proposta, che si basa su una tecnica già nota nel contesto della sincronizzazione vocale e dell’allineamento di traiettorie temporali in processi produttivi di tipo batch. Con riferimento alla spettroscopia d’assorbimento, le applicazioni presentate riguardano prodotti alimentari, con particolare attenzione alle tecnologie per la rilevazione rapida di frodi di sostituzione (di un prodotto avente un certo valore di mercato con uno a valore di mercato inferiore). Nel Capitolo 5, viene presentata una nuova tecnica per la classificazione di dati spettrali, che ha l’obiettivo di razionalizzare il pretrattamento cui i dati stessi sono generalmente sottoposti. I risultati dimostrano come la tecnica proposta garantisca di ottenere la stessa accuratezza di altri metodi, senza tuttavia ricorrere a procedure di tipo trial-and-error, onerose in termini computazionali, per la scelta del miglior pretrattamento. Nel Capitolo 6, accanto a due applicazioni di autenticazione di prodotti alimentari (filetti pescati di branzino e formaggio Asiago d’allevo) tramite spettroscopia, viene presentata una tecnica multi specie per la rilevazione di una tipica frode del settore ittico, cioè la sostituzione di filetti freschi con filetti decongelati. Rispetto al tradizionale approccio di costruire un modello di rilevazione della frode per ciascuna specie, lavorare con un modello multi specie (e, magari, indipendentemente dalla specie) riduce notevolmente i tempi e i costi necessari nella fase di calibrazione. Delle tre strategie proposte, quella che fornisce risultati migliori lavora decomponendo l’informazione contenuta nei dati spettrali in due componenti, una legata alla specie e una legata allo stato fresco o decongelato. La tecnica, convalidata su un numero di spettri molto maggiore rispetto alla applicazioni riportate in letteratura, si è dimostrata efficace anche nell’autenticazione di campioni di specie non utilizzate nella fase di calibrazione. Infine, con riferimento alla fusione di dati, il Capitolo 7 dimostra, attraverso due applicazioni in campo alimentare, come unire le informazioni ottenute da più strumenti analitici permetta di migliorare la caratterizzazione della qualità di un prodotto. La combinazione dei segnali a disposizione (detta low level, per distinguerla da altre tecniche di fusione di dati), opportunamente pesati, permette di ottenere risultati migliori rispetto all’utilizzo dei singoli segnali.

Depuis les années 1950, l'industrie pharmaceutique n'est pas épargnée par les affaires de scandales sanitaires (thalidomide 1961, 1962 et 1963), Distilbène (1977), Médiator (2009) etc. Il s'agit en général des produits de santé dont les effets indésirables graves n'ont pas été identifiés plus tôt ou simplement dissimulés par les fabricants tout au long de la chaîne de développement des produits de santé (CDPS). Ces effets ont généré des conséquences désastreuses en France et à l'étranger, augmenté les dépenses de santé publique et dégradé l'image de l'industrie pharmaceutique et la confiance des populations à l'égard de ladite industrie. Ce diagnostic laisse présager l'existence d'un dilemme auquel cette industrie fait face. Dans cette recherche, nous abordons ce dilemme sous l’angle de la fraude normalisée par les grandes entreprises pharmaceutiques (G.E.P) dans la CDPS qui illustre le parcours d’un produit de santé. Notre sujet de recherche, positionné dans le champ de recherche de la criminalité d'affaires (criminalité en col blanc, Edwin. Sutherland, 1930), pose une question pratique : de quelle manière la grande entreprise pharmaceutique fait « faire » pour normaliser la fraude dans la chaîne de développement des produits de santé (CDPS) ? Le déploiement de la M.C.R.A.A (Méthode de Contextualisation et d'analyse par la Recherche des Alliés et des affinités) a été l'approche méthodologique mobilisée dans le cadre de cette recherche. Cela nous a permis de produire des résultats en deux temps. Le premier type de résultat est assimilé à l’émergence du concept de Poche Organisationnelle Informelle (« P.O.I. »), en tant que dispositif formé par ses ressources matérielles, symboliques et ses membres affiliés, c’est-à-dire des acteurs équipés partageant un secret organisationnel autour d’un produit de santé faisant l’objet de fraude d’une part, et des acteurs externes d’autre part. Ce résultat a été progressivement transformé en résultats définitifs après renouvellement de notre processus de recherche. Cette transformation met en évidence les deux phases du cycle de vie de la P.O.I : sa réussite (résultats principaux de la thèse) et son échec (résultats secondaires de la thèse) dans la normalisation de la fraude dans la chaîne de développement des produits de santé (CDPS)
Since the 1950s, the pharmaceutical industry is still affected by the scandals of health scandals (thalidomide 1961, 1962 and 1963), Distilbène (1977), Vioxx (2004), Mediator (2009), breast prostheses PIP (2010), ...These are generally health products that have a harmful effect that is not detected earlier in the collective management of these products throughout the health product development chain. These harmful effects have generated disastrous consequences in France and abroad ( some organizations say that these are cases of pain that have caused illness, cancer or death), but also in economic and financial terms (national health costs), image and trust. This is the diagnosis made about the functioning of the pharmaceutical industry. This diagnosis reveals the existence of a dilemma that this sector must undoubtedly resolve. Various situations are often mentioned to refer to this dilemma. Some situations refer to the negligence and imprudence of institutions and organizations for the control and supervision of health products, others are oriented towards the fault and error of the actors involved in the collective management of these products, and others are about fraud perpetrated by actors mandated to develop health products that help the population to eliminate the different diseases. This thesis focuses on situations of fraud committed by big pharma as a research subject. She positions him in the field of white-collar crime, a term invented by American sociologist Edwin. Sutheland in the 1930s). The analysis of this research subject poses a practical question: How big pharma performs to normalize fraud in the health product development chain that includes national, transnational and global levels. It is important to note that this thesis does not aim to stigmatize big pharma, which are essential actors because they contribute to the disappearance of diseases by providing health products to society. Rather, it focuses on a phenomenon that has been clearly identified and that represents a threat to the planet, which has already affected health systems several times, thousands of people in the world and caused considerable human and financial losses. Thus, it relies on the experience of institutional, organizational and individual actors in the health sector, in terms of health scandals marked by pharmaceutical fraud, to answer research questions. The research results show that, big pharma is instrumentalising P.O.I, a structured and structuring organisation, to perform the actors who are involved in the collective management of health products in such a way that their practices and discourse are consistent with what she thinks, says and does. It is through this mechanism that pharmaceutical fraud is normalized at the national, transnational and global levels. More specifically, the P.O.I is a network organisation composed of human and non-human actors.Hidden within the big pharma, it materializes the ability of this enterprise to produce a generalized effect in the process that describes the different phases of realization of a health product, which will encourage the actors involved to legitimize the fraud in order to serve the interests of the entreprise in which it is housed

With traditional ERP systems, there is a lack of networking among suppliers, partners, and logistics providers. So, there is a need to have a holistic view of production and movement of goods from production to last mile delivery. The physical and digital supply chains need to be integrated to ensure secure supply chains that promote business excellence, collaboration among stakeholders, and reduce costs. The high-level view over their supply chains allows them to function better in a multi-channel world. It also helps them identify where to reduce stock without compromising customer service. Otherwise, it leads to a delay in delivery, counterfeit products, thefts, fraud, and cyberpiracy, which may lead to lawsuits and losing of brand image. The tacit function of supply chain management is to provide tracking of specific goods in the supply chain. So, it is imperative to leverage the blockchain technology stack to map multi-enterprise value networks and enable connected multi-modal networks.