Professor Abbott is highly regarded for his scholarship, teaching, and professional activities. He is the author of The Reasonable Robot: Artificial Intelligence and the Law published in 2020 by Cambridge University Press, and he has published widely on issues associated with law and technology, health law, and intellectual property in leading legal, medical, and scientific books and journals. Professor Abbott’s research has been featured prominently in the media, including in the New York Times, Financial Times, Forbes, and VICE. He routinely gives keynote lectures and presents internationally in academic (e.g., MIT, Stanford, Oxford, Cambridge), government (e.g., World Intellectual Property Organization, World Trade Organization, UK Intellectual Property Office), and industry (e.g., AIPPI, American Chemical Society, INTERPAT) settings. Managing Intellectual Property magazine named him as one of the fifty most influential people in intellectual property in 2019.
Professor Abbott has worked as a partner in legal practice, and he has been outside general counsel to life science companies. He has served as a consultant or expert for international organizations, academic institutions and non-profit enterprises including the United Kingdom Parliament, European Commission, World Health Organization (WHO) and the World Intellectual Property Organization (WIPO). Professor Abbott has also worked as an expert witness which has included testifying in U.S. federal court.
Professor Abbott is a licensed physician, attorney, and acupuncturist in the United States, as well as a solicitor advocate in England and Wales. He is board certified by the American Board of Legal Medicine. Professor Abbott is a graduate of the University of California, San Diego School of Medicine (M.D.), the Yale Law School (J.D.), the University of Surrey School of Law (Ph.D.) as well as a Summa Cum Laude graduate from Emperor's College (M.T.O.M.) and a Summa Cum Laude graduate from University of California, Los Angeles (B.S.). He is a registered patent attorney with the U.S. Patent and Trademark Office and a member of the California and New York State Bars. He is also a Senior Fellow of the Higher Education Academy (SFHEA)
28 JUL 2021
World's first patent awarded for an invention made by an AI could have seismic implications on IP law
01 AUG 2019
World first patent applications filed for inventions generated solely by artificial intelligence
In the media
Professor Abbott has a variety of research interests that reflect his multi-disciplinary background. He writes on a range of topics related to law and technology, intellectual property, and health law. For further information and downloadable papers, please see SSRN.
Prospective students interested in pursuing research matching his scholarly and research interests are welcome to make informal enquiries
For more than 60 years, “obviousness” has set the bar for patentability. Under this standard, if a hypothetical person skilled in the art would find an invention obvious in light of existing relevant information, then the invention cannot be patented. The skilled person is defined as a non-innovative worker with a limited knowledge-base. The more creative and informed the skilled person, the more likely an invention will be considered obvious. The standard has evolved since its introduction, and it is now on the verge of an evolutionary leap. Inventive machines are increasingly being used in research, and once the use of such machines becomes standard, the person skilled in the art should be a person using an inventive machine, or just an inventive machine. Unlike the skilled person, the inventive machine is capable of innovation and considering the entire universe of prior art. As inventive machines continue to improve, this will increasingly raise the bar to patentability, eventually rendering innovative activities obvious. The end of obviousness means the end of patents, at least as they are now.
Existing technologies can already automate most work functions, and the cost of these technologies is decreasing at a time when human labor costs are increasing. This, combined with ongoing advances in computing, artificial intelligence, and robotics, has led experts to predict that automation will lead to significant job losses and worsening income inequality. Policy makers are actively debating how to deal with these problems, with most proposals focusing on investing in education to train workers in new job types, or investing in social benefits to distribute the gains of automation. The importance of tax policy has been neglected in this debate, which is unfortunate because such policies are critically important. The tax system incentivizes automation even in cases where it is not otherwise efficient. That is because the vast majority of tax revenue is now derived from labor income, so firms avoid taxes by eliminating employees. More importantly, when a machine replaces a person, the government loses a substantial amount of tax revenue—potentially trillions of dollars a year in the aggregate. All of this is the unintended result of a system designed to tax labor rather than capital. Such a system no longer works once the labor is capital. Robots are not good taxpayers. We argue that existing tax policies must be changed. The system should be at least “neutral” as between robot and human workers, and automation should not be allowed to reduce tax revenue. This could be achieved by disallowing corporate tax deductions for automated workers, creating an “automation tax” which mirrors existing unemployment schemes, granting offsetting tax preferences for human workers, levying a corporate self-employment tax, or increasing the corporate tax rate. We argue the ideal solution may be a combination of these proposals.
Whether causing flash crashes in financial markets, purchasing illegal drugs, or running over pedestrians, AI is increasingly engaging in activity that would be criminal for a natural person, or even an artificial person like a corporation. We argue that criminal law falls short in cases where an AI functionally commits a crime and there are no practically or legally identifiable upstream criminal actors. This Article explores potential solutions to this problem, focusing on holding AI directly criminally liable where it is acting autonomously and irreducibly. Conventional wisdom holds that punishing AI is incongruous with basic criminal law principles such as the capacity for culpability and the requirement for a guilty mind. Drawing on analogies to corporate and strict criminal liability, as well as familiar imputation principles, we show AI punishment cannot be categorically ruled out with quick theoretical arguments. AI punishment could result in general deterrence and expressive benefits, and it need not run afoul of negative limitations such as punishing in excess of culpability. Ultimately, however, punishing AI is not justified, because it might entail significant costs and it would certainly require radical legal changes. Modest changes to existing criminal laws that target persons, together with potentially expanded civil liability, are a better solution to AI crime.
Introduction: Physicians have long worried about gene patents’ potential to restrict their medical practices. Fortune and hindsight have proven these worries exaggerated both in the U.K. and elsewhere. Neither current nor future medical practices appear to be impinged by gene patents, although they may be subject to future intellectual property disputes. Sources of Data: Qualitative and quantitative (survey) studies of gene patents’ effects on medical practice; recent developments in patent law. Areas of Agreement: Traditional gene patents do not appear to have restricted medical practice in the U.K., although their effect elsewhere has been more nuanced. Areas of Controversy: Whether patents will restrict the spread of newer medical technologies is unresolved. Areas Timely for Developing Research: Continuing survey data on practitioners’ views concerning patents’ role in the distribution of newer technologies would be beneficial.
Life science company decision-makers can effectively manage disputes using appropriate dispute resolution techniques without resorting to expensive, complex, and uncertain litigation.
Artificial intelligence is part of our daily lives. Whether working as taxi drivers, financial analysts, or airport security, computers are taking over a growing number of tasks once performed by people. As this occurs, computers will also cause the injuries inevitably associated with these activities. Accidents happen, and now computer-generated accidents happen. The recent fatality caused by Tesla’s autonomous driving software is just one example in a long series of “computer-generated torts.” Yet hysteria over such injuries is misplaced. In fact, machines are, or at least have the potential to be, substantially safer than people. Self-driving cars will cause accidents, but they will cause fewer accidents than human drivers. Because automation will result in substantial safety benefits, tort law should encourage its adoption as a means of accident prevention. Under current legal frameworks, manufacturers (and retailers) of computer tortfeasors are likely strictly responsible for their harms. This article argues that where a manufacturer can show that an autonomous computer, robot, or machine is safer than a reasonable person, the manufacturer should be liable in negligence rather than strict liability. The negligence test would focus on the computer’s act instead of its design, and in a sense, it would treat a computer tortfeasor as a person rather than a product. Negligence-based liability would create a powerful incentive to automate when doing so would reduce accidents, and it would continue to reward manufactures for improving safety. In fact, principles of harm avoidance suggest that once computers become safer than people, human tortfeasors should no longer be judged against the standard of the hypothetical reasonable person that has been employed for hundreds of years. Rather, individuals should be measured against computers. To appropriate the immortal words of Justice Holmes, we are all “hasty and awkward” compared to the reasonable computer.
Clinicians still employ a “trial-and-error” approach to optimizing treatment regimens for late-life depression (LLD). With LLD affecting a significant and growing segment of the population, and with only about half of older adults responsive to antidepressant therapy, there is an urgent need for a better treatment paradigm. Pharmacogenetic decision support tools (DSTs), which are emerging technologies that aim to provide clinically actionable information based on a patient’s genetic profile, offer a promising solution. Dozens of DSTs have entered the market in the past fifteen years, but with varying level of empirical evidence to support their value. In this clinical review, we provide a critical analysis of the peer-reviewed literature on DSTs for major depression management. We then discuss clinical considerations for the use of these tools in treating LLD, including issues related to test interpretation, timing, and patient perspectives. There are no primary clinical trials in LLD cohorts. However, in adult populations, newer generation DSTs show promise for the treatment of major depression. Further independent and head-to-head clinical trials are required to further validate this field.
Today, artificial intelligence (AI) and people do not compete on a level playing field. From a safety perspective, AI may be the best choice for driving a vehicle, but laws often prohibit driverless vehicles. At the same time, a person may be better at packing boxes at a warehouse, but a business may automate because AI receives preferential tax treatment. Or, AI may be better at helping businesses to innovate, but these same businesses may not want to use AI if doing so restricts future intellectual property rights. In The Reasonable Robot, Ryan Abbott argues that the law should not discriminate between people and AI when they are performing the same tasks, a legal standard that will help to eliminate market distortions and to ensure that decisions are made on the basis of efficiency. This work should be read by anyone interested in the rapidly evolving relationship between AI and the law.
While the use of complementary, alternative and integrative medicine (CAIM) is substantial, it continues to exist at the periphery of allopathic medicine. Understanding the attitudes of medical students toward CAIM will be useful in understanding future integration of CAIM and allopathic medicine. This study was conducted to develop and evaluate an instrument and assess medical students' attitudes toward CAIM. The Complementary, Alternative and Integrative Medicine Attitudes Questionnaire (CAIMAQ) was developed by a panel of experts in CAIM, allopathic medicine, medical education and survey development. A total of 1770 CAIMAQ surveys (51 of US medical schools participated) were obtained in a national sample of medical students in 2007. Factor analysis of the CAIMAQ revealed five distinct attitudinal domains: desirability of CAIM therapies, progressive patient/physician health care roles, mind-body-spirit connection, principles of allostasis and a holistic understanding of disease. The students held the most positive attitude for the mind-body-spirit connection and the least positive for the desirability of CAIM therapies. This study provided initial support for the reliability of the CAIMAQ. The survey results indicated that in general students responded more positively to the principles of CAIM than to CAIM treatment. A higher quality of CAIM-related medical education and expanded research into CAIM therapies would facilitate appropriate integration of CAIM into medical curricula. The most significant limitation of this study is a low response rate, and further work is required to assess more representative populations in order to determine whether the relationships found in this study are generalizable. Copyright © 2011 Ryan B. Abbott et al.
The aim of this article is to educate physicians about the current litigation climate in cardiology and cardiac surgery, with a focus on the most frequently litigated areas of practice, including failure to diagnose and treat myocardial infarction, coronary artery bypass graft surgery, percutaneous coronary intervention, and the use of tissue plasminogen activator. Empirical research on cardiology malpractice is presented, along with a sampling of up-to-date cases designed to illustrate common issues and important themes. The principles for reducing legal liability are also discussed, including the informed consent process, spoliation of records, and the role of documentation. Finally, practical recommendations are provided for cardiologists and cardiac surgeons to limit their legal liability. © 2013 Lippincott Williams & Wilkins.
The rising popularity of complementary and alternative medicine (CAM) in child and adolescent psychiatry raises unique ethical and legal concerns for psychiatrists and other conventional health care providers. This article explores these concerns and provides clinical advice for promoting patient health and safety while minimizing the psychiatrist's risk. Although any departure from the conventional standard of care is a potential risk, the risk of malpractice liability for practicing integrative medicine in child and adolescent psychiatry is low. CAM is most safely recommended from a legal standpoint when there is some published evidence of safety and efficacy. © 2013 Elsevier Inc.
This article argues that an administrative bounty proceeding should be established to motivate third parties to submit data on drug safety and efficacy to the food and drug agency. The administrative bounty proceeding should be modeled after the Federal Claims Act qui tam regime, and the federal government should pay petitioner rewards based on a portion of the money that the government will save by avoiding adverse effects and medically ineffective therapies in patients with government health insurance.
The Patient Protection and Affordable Care Act (PPACA) intends to take American health care in a new direction by focusing on preventive medicine and wellness-based treatment. But, in doing so, it does not adequately take into account the potential contribution of complementary and alternative medicine (CAM). CAM is already used by a large and growing number of individuals in the United States, although to date there is limited scientific evidence to support the efficacy of most CAM treatments. This article proposes statutory reforms to PPACA to encourage CAM research and development (R&D), and the use of demonstrably effective CAM treatments. A hybrid system of limited intellectual property protection and government prizes based on regulatory approval may be the best option for incentivizing R&D on CAM, along with increased funding for research through the National Institutes of Health. PPACA should require health insurance plans to reimburse for evidence-based CAM and empower an existing government agency (NCCAM) to regulate CAM standards and to recommend evidence-based CAM services. Together these policy and funding mechanisms should help reduce U.S. healthcare costs and improve quality of life.
Jordan dramatically strengthened the level of intellectual property protection it provides for pharmaceutical products in consequence of joining the World Trade Organization in 2000 and signing a Free Trade Agreement with the United States in 2001. This study assesses the impact of higher levels of intellectual property protection on access to medicines by quantifying the effects on the private retail pharmaceutical market of delayed market entry of generic products. Adjusted for increased sales volume and inflation, from 1999 to 2004 there was a 17% increase in total annual expenditure for medicines in Jordan. When assessing originator medicines that were marketed in both 1999 and 2004, and for which there were generic equivalents, the weighted average price of originator medicines increased while the weighted average price of equivalent generic medicines decreased. Delayed market entry of generics due to enhanced intellectual property protection is estimated to have cost Jordanian private consumers approximately 18 million U.S. dollars in 2004. Jordan should consider amending its current regulatory scheme on data protection and amending the Unfair Competition and Trade Secrets Law of 2000. Jordan should also consider increased spending on public health to offset the adverse impact on consumers of strengthening its intellectual property protection relevant to pharmaceutical products. © 2012 The Author(s).
This study examined whether a traditional low-impact mind-body exercise, Tai Chi, affects health-related quality-of-life (HRQOL) and headache impact in an adult population suffering from tension-type headaches. Forty-seven participants were randomly assigned to either a 15 week intervention program of Tai Chi instruction or a wait-list control group. HRQOL (SF-36v2) and headache status (HIT-6™) were obtained at baseline and at 5, 10 and 15 weeks post-baseline during the intervention period. Statistically significant (P < 0.05) improvements in favor of the intervention were present for the HIT score and the SF-36 pain, energy/fatigue, social functioning, emotional well-being and mental health summary scores. A 15 week intervention of Tai Chi practice was effective in reducing headache impact and also effective in improving perceptions of some aspects of physical and mental health. © 2006 The Author(s).
Tai Chi and Qigong are traditional Chinese exercises that are widely practiced for their health benefits and as martial arts. Evidence suggests that these practices may be effective at treating a range of physical health conditions, and at improving health-related quality of life. There is growing interest in the use of Tai Chi and Qigong to treat mental disorders, because they are noninvasive, exercise-based therapies, and because patients with mental disorders frequently use complementary and alternative medicine. Evidence is promising that these treatments may be effective in reducing depressive symptoms, stress, anxiety, and mood disturbances. © 2013 Elsevier Inc. All rights reserved.
Data on individual patients collected through state and federal health information exchanges has the potential to usher in a new era of drug regulation. These exchanges, produced by recent health care reform legislation, will amass an unprecedented amount of clinical information on drug usage, demographic variables, and patient outcomes. This information could aid the Food and Drug Administration ("FDA") with post-market drug surveillance because it more accurately reflects clinical practice outcomes than the trials the FDA relies upon for drug approval. However, even with this data available, the market-driven impetus to use it to police drugs is weak. This is fixable; the post-market drug regulatory process needs new incentives to boost third party participation. While a variety of mechanisms could achieve this, the best option for generating robust results may be an administrative bounty proceeding that will allow third parties to submit evidence to the FDA to contest the claimed safety and efficacy profiles of drugs already on the market. This Article uses a case study of Merck's former blockbuster drug Vioxx to demonstrate how this system might work. In creating a new incentive that counters the powerful financial motivation of drug manufacturers to obscure or misrepresent safety profiles, the proposed bounty proceeding could lead to an improved balance of the risks and benefits of drugs used by the American public. More broadly, this Article illustrates how to create an incentive for the private sector to supplement regulatory activity in a complex field.
The American health care system is plagued by high costs and poor public health outcomes, due in part to the overuse of costly diagnostic tests and treatments. In 2009, the Institute of Medicine estimated that unnecessary care wastes $750 billion, equivalent to about 30 percent of health care spending. Moreover, overtreatment can directly harm patients as a result of surgical complications, drug toxicity, and hospital-acquired infections. Yet while the problem of medical waste has long been recognized, solving the problem has proven elusive. In part, this difficulty is due to perverse economic incentives for physicians and hospitals, which still primarily receive reimbursement on a fee-for-service basis. Providers are financially motivated under this system to generate a higher volume of invasive procedures independent of their likely benefits. Patients generally lack the information needed to decline unnecessary services, even when they wish to actively share in medical decision-making, and a strong cultural bias pushes both patients and physicians to “do more,” even when evidence suggests that doing more may result in harm. In the 1990s, managed health care organizations attempted to rein in health care waste by stringently reviewing and prospectively denying payment for unnecessary tests and treatments, but that experiment was a political failure. Similarly, attempts to reduce overuse by shifting financial risk directly onto providers through capitated payment mechanisms have had limited success. The ability of these mechanisms to limit waste is compromised by the real or perceived incentive to also reduce spending on appropriate care. We propose a new conception of medical necessity that will reduce inappropriate care by allowing informed consumers to actively participate in decisions about their medical care. Where evidence-based guidelines are available, medical necessity should be determined on the basis of an objective, multi-level Matrix of Appropriateness rather than the subjective binary decision of an insurance company’s medical reviewer. Such Matrices have already been created by systematically combining published evidence with expert judgment to create clinically detailed, evidence based, multilevel medical necessity ratings for elective procedures based on individual patient characteristics. In our proposed system, if a patient desires a service proposed by a physician under clinical circumstances that receive low medical necessity ratings, the third-party payer would offer to cover the service but at a sliding co-payment scale imposing greater patient cost sharing based on the service’s appropriateness. This system would preserve patient choice while discouraging the overuse of costly treatments that provide little marginal value, reducing medical waste and improving the overall value of medical care.
In some cases, a computer’s output constitutes patentable subject matter, and the computer rather than a person meets the requirements for inventorship. As such machines become an increasingly common part of the inventive process, they may replace the standard of the person skilled in the art now used to judge nonobviousness. Creative computers require a rethinking of the criteria for inventiveness, and potentially of the entire patent system.
A recurring issue for evidence-based regulation of medicine is deciding whether to extend governmental approval from an approved use with sufficient current evidence of safety and efficacy to a novel use where such evidence is currently lacking. This “extrapolation” problem can arise in several contexts: (i) diagnosis extrapolation occurs when physicians want to use an approved drug or device to treat a new condition; (ii) patient extrapolation occurs when physicians want to use an existing drug or device to treat a new population with a given condition; (iii) dosage extrapolation occurs when physicians want to use an existing drug or device for a new duration, schedule of use, or at a new dosage; (iv) treatment extrapolation occurs when physicians want to use a new drug or device that is related to an approved counterpart. The logic of pre-approval testing, and the precautionary principal (first, do no harm), would seem to counsel prohibiting extrapolation approvals until after traditional safety and efficacy evidence exists. We reject that approach as overly conservative and instead propose a more dynamic and evolving evidence-based regime based on Bayes’ Law fundamentally, the science of learning. To apply Bayesian decision-making, one needs to (i) form a “prior” belief based on existing evidence, (ii) gather additional information, and (iii) update the prior belief. A system that allows interim periods of use can provide physicians and patients with greater treatment options while providing regulators with valuable evidence about the safety and efficacy of the proposed extrapolation. Indeed, off label drug use is legal and sometimes the medical standard of care. In contrast, a precautionary requirement conditioning all approvals on pre-existing evidence for uses that constitute just slight extrapolations along just one of these four dimensions sacrifices probable short-term health benefits at the alter of precaution. Harm is not only associated with permitting access to unsafe products but also with restricting access to beneficial products. We call for policy changes in reporting, testing, and enforcement regulations to provide a more layered and dynamic system of regulatory incentives. Our proposals are Bayesian because they force policymakers to (i) assess and acknowledge the imperfect nature of their prior beliefs regarding off-label use, (ii) gather, when cost-effective, additional information, and (iii) take action in terms of approvals, reimbursements, and enforcement based on continual updating. We aim to put Bayesianism into regulatory practice.
Last November in Beijing, government officials representing member states of the World Health Organisation adopted a declaration that provides a powerful endorsement of traditional medicine and may one day become the foundation for a legally binding resolution.
An innovation revolution is on the horizon. Artificial intelligence (AI) has been generating inventive output for decades, and now the continued and exponential growth in computing power is poised to take creative machines from novelties to major drivers of economic growth. A creative singularity in which computers overtake human inventors as the primary source of new discoveries is foreseeable.
A recurring, foundational issue for evidence-based regulation is deciding whether to extend governmental approval from an existing use with sufficient current evidence of safety and efficacy to a novel use for which such evidence is currently lacking. This "extrapolation" issue arises in the medicines context when an approved drug or device that is already being marketed is being considered (1) for new conditions (such as off-label diagnostic categories), (2) for new patients (such as new subpopulations), (3) for new dosages or durations, or (4) as the basis for approving a related drug or device (such as a generic or biosimilar drug). Although the logic of preapproval testing and the precautionary principle-first, do no harm-would counsel in favor of prohibiting extrapolation approvals until after traditional safety and efficacy evidence exists, such delays would unreasonably sacrifice beneficial uses. The harm of accessing unsafe products must be balanced against the harm of restricting access to effective products. In fact, the Food and Drug Administration's (FDA's) current regulations in many ways reject the precautionary principle because they largely permit individual physicians to prescribe medications for off-label uses before any testing tailored to those uses has been done. The FDA's approach empowers physicians, but overshoots the mark by allowing enduring use of drugs and devices with insubstantial support of safety and efficacy. This Article instead proposes a more dynamic and evolving evidence-based regime that charts a course between the Scylla and Charybdis of the overly conservative precautionary principle on one hand, and the overly liberal FDA regime on the other. Our approach calls for improvements in reporting, testing, and enforcement regulations to provide a more layered and nuanced system of regulatory incentives. First, we propose a more thoroughgoing reporting of off-label use (via the disclosure of diagnostic codes and "detailing" data) in manufacturers' annual reports to the FDA, in the adverse event reports to the FDA, in Medicare/Medicaid reimbursement requests, and, for a subset of FDA-designated drugs, in prescriptions themselves. Second, we would substantially expand the agency's utilization of postmarket testing, and we provide a novel framework for evaluating the need for postmarket testing. Finally, our approach calls for a tiered labeling system that would allow regulators and courts to draw finer reimbursement and liability distinctions among various drug uses, and would provide the agency both the regulatory teeth and the flexibility it presently lacks. Together, these reforms would improve the role of the FDA in the informational marketplace underlying physicians' prescribing decisions. This evolutionary extrapolation framework could also be applied to other contexts. © 2014 Ryan Abbott and Ian Ayres.
Artificial intelligence has been generating inventive output for decades, and now the continued and exponential growth in computing power is poised to take creative machines from novelties to major drivers of economic growth. In some cases, a computer’s output constitutes patentable subject matter, and the computer rather than a person meets the requirements for inventorship. Despite this, and despite the fact that the Patent Office has already granted patents for inventions by computers, the issue of computer inventorship has never been explicitly considered by the courts, Congress, or the Patent Office. Drawing on dynamic principles of statutory interpretation and taking analogies from the copyright context, this Article argues that creative computers should be considered inventors under the Patent and Copyright Clause of the Constitution. Treating nonhumans as inventors would incentivize the creation of intellectual property by encouraging the development of creative computers. This Article also addresses a host of challenges that would result from computer inventorship, including the ownership of computer-based inventions, the displacement of human inventors, and the need for consumer protection policies. This analysis applies broadly to nonhuman creators of intellectual property, and explains why the Copyright Office came to the wrong conclusion with its Human Authorship Requirement. Finally, this Article addresses how computer inventorship provides insight into other areas of patent law. For instance, computers could replace the hypothetical skilled person that courts use to judge inventiveness. Creative computers may require a rethinking of the baseline standard for inventiveness, and potentially of the entire patent system.
Traditional medical knowledge is experiencing increased attention worldwide in light of global health care demand and the significant role of traditional medicine in meeting the public health needs of developing countries. Traditional medicines already comprise a multi-billion dollar, international industry, and the biomedical sector is increasingly investigating the potential of genetic resources and traditional knowledge. Documenting and protecting these medicines is becoming a greater priority. Traditional knowledge has historically been at odds with modern intellectual property systems designed to protect innovations such as new pharmaceutical drugs. However, as the financial value of many forms of traditional medicine becomes recognized, traditional knowledge holders and nations rich in genetic resources are arguing for greater protection through non-conventional systems of intellectual property protection. Traditional knowledge holders are increasingly demanding fair and equitable distribution of benefits from the commercialization of traditional medicine, as well as the prior informed consent of indigenous peoples to prevent misappropriation. Many problems associated with the protection of traditional medical knowledge lack clear solutions. In attempting to protect traditional medicine, traditional knowledge holders are confronted by a confusing and diverse group of national and international policies, regulatory systems designed primarily to accommodate pharmaceutical medicines, safety and efficacy concerns, and challenges to ownership. This text is designed to assist traditional medical knowledge holders, government representatives and third-party collaborators to think about issues of intellectual property law specifically related to traditional medical knowledge. It is not intended to provide legal advice, but rather to help stimulate thinking about traditional knowledge and to provide illustrative case studies. There is no generic way to protect traditional medical knowledge. Traditional knowledge holders should carefully consider identified community goals for the use of traditional medicine and the risks and benefits of documentation. Whether traditional medical knowledge is documented can have far reaching consequences on intellectual property protection, commercialization and promotion of traditional medicine, regulatory submissions and interactions with collaborators. It is important that traditional knowledge holders be adequately informed to safeguard their reputations and interests when interacting with third parties. Hopefully, this text will help traditional knowledge holders better understand the issues related to traditional medicine and intellectual property and make informed decisions about the best use of their knowledge.
About 10% of Jordan's gross domestic product is spent on health care, almost one-third of which is spent on pharmaceuticals. Jordan's pharmaceutical spending is a substantially higher percentage of gross domestic product than that of other developed countries. Generic substitution is a mechanism that could lower pharmaceutical spending costs in Jordan, but Jordan's domestic law currently forbids pharmacists in the private market from dispensing generic equivalents to branded medicines without a physician's approval. This article provides the results of a study that surveyed prominent organizational stakeholders (n=17, RR 100%) in Jordan's health care system and evaluates their opinions about generic substitution. The study finds there is abroad base of support for allowing and encouraging generic substitution in the private sector, and for mandating generic substitution in the public sector. Given that generic substitution may help to reduce health care costs and improve access to medicines, policymakers should consider legal and policy changes to facilitate generic substitution. The research suggests that key players in Jordan's health care system will support such proposals. © The Author(s) 2014.
BACKGROUND: The efficacy of perineal self-acupressure in treating constipation is uncertain. OBJECTIVE: We aimed to evaluate whether perineal self-acupressure would improve patient reports of quality of life and bowel function at 4 weeks after training. DESIGN: A randomized, parallel group trial was conducted. SETTING: The study took place at the UCLA Department of Medicine. PATIENTS: One hundred adult patients who met Rome III criteria for functional constipation participated. INTERVENTION: The control group received information about standard constipation treatment options, while the treatment group received training in perineal self-acupressure plus standard treatment options. MEASUREMENTS: Primary outcome was the Patient Assessment of Constipation Quality of Life (PAC-QOL). Secondary outcomes included patient assessments of bowel function (as measured by a modified Bowel Function Index (BFI)), and health and well-being (as measured by the SF-12v2). RESULTS: The mean PAC-QOL was improved by 0.76 in the treatment group and by 0.17 in the control group (treatment-effect difference, 0.59 [95 % CI, 0.37 to 0.81]; p < 0.01). The mean modified BFI was improved by 18.1 in the treatment group and by 4.2 in the control group (treatment-effect difference, 13.8 [95 % CI, 5.1 to 22.5]; p < 0.01). The mean SF-12v2 Physical Component Score was improved by 2.69 in the treatment group and reduced by 0.36 in the control group (treatment-effect difference, 3.05, [95 % CI, 0.85 to 5.25]; p < 0.01); and the mean SF-12v2 Mental Component Score was improved by 3.12 in the treatment group and improved by 0.30 in the control group (treatment-effect difference, 2.82, [95 % CI, −0.10 to 5.74]; p < 0.07). LIMITATION: The trial was not blinded. CONCLUSION: Among patients with constipation, perineal self-acupressure improves self-reported assessments of quality of life, bowel function, and health and well-being relative to providing standard constipation treatment options alone. © 2014, Society of General Internal Medicine.