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Should “the purple pill” by any other drug company still be as purple? The changing face of trade dress protection for pharmaceutical manufacturers

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... For example, one study that involved customers for vitamins packaged in a black container with white lettering showed that they mistook the vitamins for poison because black color is often related to poison in Western culture [17]. Other researchers studied patients' perception of color in pharmaceutical products and found that patients who took drugs daily preferred brightly colored tablets, and the right selection of color can make an emotional appeal to the patients, which eventually reduces medication errors and increases patients' compliance with and adherence to their prescription medication plan [18]. Furthermore, color can aid pharmaceutical companies in identifying their products among counterfeit drugs by quantitative measurement of the color on the surface of tablets with a colorimetric technique [10]. ...
... Certain pharmaceutical companies manufacture their tablets and capsules with some words, numbers, or even a logo to ease their identification by patients and make medication products more complicated to counterfeit. Therefore, a unique property, such as an imprint with a good and readable quality, also helps patients to differentiate between counterfeit and generic drugs [21] and prevents confusion among other solid dosage forms [18]. ...
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The physical description of dosage forms is one of the most important considerations in avoiding patient confusion and minimizing medication errors. This study aimed to determine the quality and accuracy of the physical descriptions in patient information leaflets (PILs). This cross-sectional study constituted a total of 200 drugs and PILs that were randomly selected, by pharmacy students, from Al-Dawaa community pharmacies in the Hail region of Saudi Arabia, from January 2021 to July 2021. The drugs and PILs were thoroughly evaluated in accordance with the Gulf Cooperation Council (GCC) guidelines for PILs. The accuracy screening of the total solid dosage forms (capsules + tablets) revealed that 45% showed complete accuracy and compliance, 1.5% showed poor accuracy and compliance, and 53% showed no accuracy and no compliance with the GCC guidelines and the Saudi Food and Drug Authority (SFDA) guidelines. In the frequency test, color, shape, and imprints accounted for 95.6%, 79.1%, and 73.6%, respectively. However, the size of the dosage form was the least (2.2%) used physical description feature. These findings recommend pharmaceutical companies to pay more attention to the written physical description in their PILs. Additionally, the process of PIL approval should be optimized, evaluated, and updated systematically to ensure that they contain the essential information.
... At the same time, however, it is important to bear in mind here that pharmaceutical products should neither be too sensorially appealing, nor should they be too easily confusable with regular food and beverage or confectionary products (as will be highlighted later). While direct-to-consumer (DTC) marketing of medications has been rejected in Europe (see Cassels, 2003;Cozens, 2002), recent years have seen a significant growth of this sector in the US (Erlich, 1995), with many campaigns showing images of the medications themselves (Fritch, 2006;Matheson & Justus, 2009), as well as, of course, the brand name, thus offering further scope for multisensory marketing interventions. ...
... Over the years, a few pharmaceutical products have managed to establish a distinctive signature colour for themselves, such as, for example, bright Pepto-Bismol pink (Worthington, 2007), or the distinctive blue of Pfizer's little blue pill Viagra (Worthington, 2007): "And who can forget how AstraZeneca successfully got ahead of the patent expiration curve by migrating millions of Prilosec users to Nexium on the backs of the colour purple (Prilosec: "The Purple Pill" became Nexium: "Today's Purple Pill")." (Worthington, 2007, p. 38; see also Fritch, 2006;Matheson & Justus, 2009). In such cases, one might consider the distinctive colour to be something of a signature sensory feature associated with a given brand. ...
Article
People’s expectations concerning the functional properties and efficacy of pharmaceuticals are influenced by a wide variety of product-extrinsic factors, such as the colour (of both product and pack), form (e.g., tablet vs. capsule), and shape (e.g., round, oval, or diamond-shaped) of medicines, and the multisensory design of the product packaging. The sound symbolic properties of a medicine’s brand name, as well as its processing fluency, have also been shown to exert a significant influence over people’s expectations. However, given that non-adherence has long been a key issues with medical treatment, further research is urgently needed in order to determine the extent (albeit likely limited) to which these various product-extrinsic factors influence non-compliance, while at the same time avoiding the confusion that has been caused by the proliferation of look-alike/sound-alike drugs in the marketplace in recent years. Further research is also needed in order to help establish the cross-cultural consensuality of the meanings that are attached by consumers to these various different product-extrinsic sensory cues (especially colour) in the pharmaceutical category, and to firmly establish the robustness of any colour-based placebo effects. At the same time, however, it is currently unclear which cue (or cues) dominate(s) when multiple product attributes are manipulated simultaneously given that the influence of colour, shape, sound symbolism, etc., have typically only been studied individually to date. The multisensory design of pharmaceuticals and their packaging therefore constitutes a particularly intriguing, not to mention important, applied area for food/sensory scientists, marketing researchers, and cognitive neuroscientists.
... The ability to identify prescribed medicines by name may be helpful for screening and responding to patients at greater risk of making medication errors or being less engaged with their regimen for adherence purposes. Patients often rely on the visual characteristics of their medications as a way to ensure that they are taking the right drug (Cohen & Smetzer, 2011; Fritch, 2006). However, because of the increasing prevalence of generic medications in the prescription drug marketplace, the appearance of a patient's medication may change considerably over time (Fritch, 2006). ...
... Patients often rely on the visual characteristics of their medications as a way to ensure that they are taking the right drug (Cohen & Smetzer, 2011; Fritch, 2006). However, because of the increasing prevalence of generic medications in the prescription drug marketplace, the appearance of a patient's medication may change considerably over time (Fritch, 2006). Trade dress protection, a portion of U.S. copyright law entitling companies to claim ownership of the physical characteristics of their products, allows drug manufacturers to protect the size, shape, and color of their medications (Greene & Kesselheim, 2011). ...
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Understanding and organizing medication regimens can be challenging, and many patients struggle to properly dose prescribed medicine, potentially leading to less effective treatment or even harm. Generic prescriptions are increasingly common and may change in appearance, adding further complexity. The authors aimed to investigate familiarity with the drug regimen among a cohort of patients with diagnosed hypertension. Specifically, they determined the prevalence of patients' knowledge of their prescribed drug names and dosages compared to those who relied only on physical characteristics (size, shape, color) of their medications. The relationship between patients' identification strategies, self-reported adherence, and health outcomes (blood pressure control, hospitalization) were investigated. Patients who were dependent on the visual identification of their prescription medicine reported worse adherence. In addition, they had significantly lower rates of blood pressure control and greater risk of hospitalization. The ability to identify prescribed medicines by name may be helpful for screening and responding to patients at greater risk of making medication errors or being less engaged with their regimen for adherence purposes.
... Nowadays, there is growing concern as to how far ''trade dress'' (i.e., packaging, product shape, colour that is part of serves a branding function) may extend in order to protect or differentiate brand-name drugs from their generic rivals (e.g., Fritch, 2006;Greene & Kesselheim, 2011). Nevertheless, considering that a system with greater consistency in the sensory properties of pills might increase adherence to treatments and reduce the danger of medication error, the practise of trade dress may actually have a detrimental effect on patients. ...
Article
Two experiments are reported in which people’s sensory, hedonic, and efficacy expectations associated with pharmaceutical pills of differing colour and shape were assessed. In Experiment 1, 101 participants from the USA viewed online photos of tablets having one of 7 colours and 3 shapes. The participants had to arrange the 21 tablets based on the expectations generated solely by the tablets’ visual properties. The results revealed that the colour of the tablets influenced expected bitterness, expected alertness, and expected efficiency in combating headaches, whereas the shape of the tablets influenced the expected difficulty of swallowing. In Experiment 2, the major findings of Experiment 1 were replicated while using a greater variety of colours, in 358 participants from China, Colombia, and the USA. Importantly, the results revealed some shared expectations across cultures, such as the high expected efficacy of white tablets in combating headaches, or the high expected difficulty of swallowing the diamond-shaped tablets. The results also revealed some differences among the three groups, such as that the colour of the pills influenced how difficult the Chinese participants (but not the other two groups) expected the pills would be to swallow. These findings clearly demonstrate that the differing colours and shapes of pharmaceutical pills set-up significantly different expectations which likely play an important role in terms of people’s subsequent experience.
Chapter
In this chapter, an attempt has been made to understand the effects of non-traditional trademarks in the area of pharmaceutical products and issues of competition along with a normative case against the unconventional trademarks, further proceeding towards a discussion on inherently valuable freedom of expression and to assess why affording legal protection for non-traditional marks in this area may hamper access to medicine/health. In order to answer this question effectively, this chapter is divided into three parts: the first part explores the prevalence of non- traditional marks in the area of pharmaceuticals; the second part analyzes whether protection for non-traditional marks could pose impediments to access to medicine/health; and the last part ponders the issues of competition and freedom of expression with analytical approach.
Preprint
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[Background] Drug label, or packaging insert play a significant role in all the operations from production through drug distribution channels to the end consumer. Image of the label also called Display Panel or label could be used to identify illegal, illicit, unapproved and potentially dangerous drugs. Due to the time-consuming process and high labor cost of investigation, an artificial intelligence-based deep learning model is necessary for fast and accurate identification of the drugs. [Methods] In addition to image-based identification technology, we take advantages of rich text information on the pharmaceutical package insert of drug label images. In this study, we developed the Drug Label Identification through Image and Text embedding model (DLI-IT) to model text-based patterns of historical data for detection of suspicious drugs. In DLI-IT, we first trained a Connectionist Text Proposal Network (CTPN) to crop the raw image into sub-images based on the text. The texts from the cropped sub-images are recognized independently through the Tesseract OCR Engine and combined as one document for each raw image. Finally, we applied universal sentence embedding to transform these documents into vectors and find the most similar reference images to the test image through the cosine similarity. Results] We trained the DLI-IT model on 1749 opioid and 2365 non-opioid drug label images. The model was then tested on 300 external opioid drug label images, the result demonstrated our model achieves up-to 88% of the precision in drug label identification, which outperforms previous image-based or text-based identification method by up-to 35% improvement. [Conclusion] To conclude, by combining Image and Text embedding analysis under deep learning framework, our DLI-IT approach achieved a competitive performance in advancing drug label identification.
Preprint
Full-text available
[Background] Drug label, or packaging insert play a significant role in all the operations from production through drug distribution channels to the end consumer. Image of the label also called Display Panel or label could be used to identify illegal, illicit, unapproved and potentially dangerous drugs. Due to the time-consuming process and high labor cost of investigation, an artificial intelligence-based deep learning model is necessary for fast and accurate identification of the drugs. [Methods] In addition to image-based identification technology, we take advantages of rich text information on the pharmaceutical package insert of drug label images. In this study, we developed the Drug Label Identification through Image and Text embedding model (DLI-IT) to model text-based patterns of historical data for detection of suspicious drugs. In DLI-IT, we first trained a Connectionist Text Proposal Network (CTPN) to crop the raw image into sub-images based on the text. The texts from the cropped sub-images are recognized independently through the Tesseract OCR Engine and combined as one document for each raw image. Finally, we applied universal sentence embedding to transform these documents into vectors and find the most similar reference images to the test image through the cosine similarity. [Results] We trained the DLI-IT model on 1749 opioid and 2365 non-opioid drug label images. The model was then tested on 300 external opioid drug label images, the result demonstrated our model achieves up-to 88% of the precision in drug label identification, which outperforms previous image-based or text-based identification method by up-to 35% improvement. [Conclusion] To conclude, by combining Image and Text embedding analysis under deep learning framework, our DLI-IT approach achieved a competitive performance in advancing drug label identification.
Preprint
Full-text available
[Background] Drug label, or packaging insert play a significant role in all the operations from production through drug distribution channels to the end consumer. Image of the label also called Display Panel or label could be used to identify illegal, illicit, unapproved and potentially dangerous drugs. Due to the time-consuming process and high labor cost of investigation, an artificial intelligence-based deep learning model is necessary for fast and accurate identification of the drugs. [Methods] In addition to image-based identification technology, we take advantages of rich text information on the pharmaceutical package insert of drug label images. In this study, we developed the Drug Label Identification through Image and Text embedding model (DLI-IT) to model text-based patterns of historical data for detection of suspicious drugs. In DLI-IT, we first trained a Connectionist Text Proposal Network (CTPN) to crop the raw image into sub-images based on the text. The texts from the cropped sub-images are recognized independently through the Tesseract OCR Engine and combined as one document for each raw image. Finally, we applied universal sentence embedding to transform these documents into vectors and find the most similar reference images to the test image through the cosine similarity. [Results] We trained the DLI-IT model on 1749 opioid and 2365 non-opioid drug label images. The model was then tested on 300 external opioid drug label images, the result demonstrated our model achieves up-to 88% of the precision in drug label identification, which outperforms previous image-based or text-based identification method by up-to 35% improvement. [Conclusion] To conclude, by combining Image and Text embedding analysis under deep learning framework, our DLI-IT approach achieved a competitive performance in advancing drug label identification.
Chapter
Full-text available
Over the years, many pharmaceutical companies have sought trademark protection for non-traditional aspects of their products. However, the potential consequences that could arise from granting such protection to pharmaceutical products have not received due attention from policy makers, especially in the case of access to medicine. The provisions regarding non-traditional marks in the leaked IP Chapter of Regional Comprehensive Economic Partnership is just one example in this regard. In this context, this chapter examines the question of whether protection for non-traditional marks could adversely affect access to medicine/health. For answering this, we first looked at how non-traditional marks operate in different jurisdictions and its prevalence in the area of pharmaceuticals. We have then attempted to analyse the potential consequences of non-traditional marks in the pharmaceutical sector from a law and economics perspective. Our analysis shows that protection for non-traditional marks in the pharmaceutical sector could pose significant barriers to access to medicine. This includes increase in transaction costs and new barriers to generic entry. Our study recommends that policymakers should take into account these public health aspects while framing policies with regard to non-traditional marks. We recommend more rigorous use of traditional trademark doctrines like functionality to prevent the rise of non-traditional barriers to access to medicine.
Article
This article narrates a late twentieth century controversy in American medicine over the clinical, public health, and financial value of ‘look-alike drugs’ a set of generic pharmaceuticals that imitated their brand-name counterparts down to exact parameters of size, shape, and color. At stake in these conflicts was the emerging landscape of market exclusivity for formerly innovative pharmaceuticals once their patent rights expired. After the patent, which qualities of a brand-name drug could still be considered to be private property, and which became part of the public commons? This dispute invoked thorny epistemological questions about pharmaceuticals as therapeutic technologies. Was the active pharmaceutical ingredient (API) the only public, knowable part of a drug, while other parts – binders, fillers, dyes, scores, and bevels – could be kept as trade secrets? Did these other physical parts of a pill bear some clinical function as well? Could the color of a capsule affect its therapeutic effects?
Article
In this article, we review the legal basis of trade dress as it has applied to pharmaceutical products and consider the public health implications of variations in pill appearance. We then discuss how a system of more uniform drug appearance could be designed to reduce medical error and promote patient adherence to treatment regimens that involve generic drugs.
at 359 (finding no error in District Court finding that "Shire had failed to show that its product configuration was non-functional
  • Id
Id. at 359 (finding no error in District Court finding that "Shire had failed to show that its product configuration was non-functional.").
supra note 7 (noting current generic pharmaceutical marketshare)
  • Jaeger
Jaeger, supra note 7 (noting current generic pharmaceutical marketshare);
Food and Drug Admin., to Health Practitioners
  • Stuart L Letter From
  • Assoc Nightingale
Letter from Stuart L. Nightingale, Assoc. Comm'r for Health Affairs, U.S. Food and Drug Admin., to Health Practitioners, (Jan. 28, 1998), available at http://www.fda.gov/cder/news/ nightgenlett.htm.
claiming that no "additional clinical scrutiny is necessary when interchange [of generic equivalent for NTI drugs] ocurrs."). The FDA maintains that "generic alternatives act the same way as the brand-name drugs-that they are just as safe and effective
  • Id
Id. (claiming that no "additional clinical scrutiny is necessary when interchange [of generic equivalent for NTI drugs] ocurrs."). The FDA maintains that "generic alternatives act the same way as the brand-name drugs-that they are just as safe and effective." FDA White Paper, supra note 15.
) (urging physicians to use caution in substituting generics for NTI drugs and urging the FDA to alter the approval process for NTI generic equivalents
  • E G See
  • R Peter
  • Kowey
See, e.g., Peter R. Kowey, American Heart Association, Issues in Bioequivalence and Generic Substitution for Antiarrhythmic Drugs, Dec. 7, 2005, at, http://www.americanheart.org/ presenter.jhtml?identifier=3015266 (last visited Sept. 7, 2006) (urging physicians to use caution in substituting generics for NTI drugs and urging the FDA to alter the approval process for NTI generic equivalents "to assure a greater sense of clinical security");
Three in four (75%) physicians strongly or somewhat agree that there are some drugs with therapeutic indices that should not be substituted
  • Linda L Barrett
  • American Association
  • Retired Persons
LINDA L. BARRETT, AMERICAN ASSOCIATION OF RETIRED PERSONS (AARP), PHYSICIANS' ATTITUDES AND PRACTICES REGARDING GENERIC DRUGS, 17 (Mar. 2005), available at http://assets.aarp.org/rgcenter/health/phys_generic.pdf ("Three in four (75%) physicians strongly or somewhat agree that there are some drugs with therapeutic indices that should not be substituted [with generics] even when required by third parties.");
at 978 (finding look-alike generic manufacturer's "wrong
  • Id
Id. at 978 (finding look-alike generic manufacturer's "wrong... in designedly enabling" unscrupulous phrmacists to palm off generic prescriptions as that of the brand name drug).