I came across the book ‘Invisible Women: Exposing Data Bias in a World Designed for Men’, Criado‑Perez, where the author addresses how gender shapes our daily life from a structural, educational, and health standpoint. While this is a hot topic in the light of the re‑emergency of the discussion about the gap between genders, what led me to read the book was the assembled amount of statistical data that goes beyond any ‘feminist movement’. I was particular interested in the data supporting a gender bias in healthcare. The book mentions how studies about the demographics of Swedish patients (fractures and flu), in winter time, resulted in a simple change of the priority of snow‑ploughing of sidewalk over roads (women being the main users of public transportation) and, consequently, in a decrease in the medical care bill. The author also skims the implication of clinical studies using mainly male subjects in the misdiagnosis and treatment of heart diseases in women. Although the book fell short on the gender bias in healthcare, it compiles many surprising evidences of an inadequately designed world. Interestingly, one might even question if the word gender has any meaning in an age where some countries have approved legislation in favor of a neutral gender with repercussions at many levels, from birth certificates to linguistics. In matter of fact, the words sex and gender are often interchangeably used without a clear definition of the concept! While sex refers to the biological physiological nature that is dependent on genetics (chromosomes XX and XY), gender refers to the psycho‑social and cultural representations of sex. And in science, this is of major importance when studying characteristics that are dependent on the sex, either behavior or simply a differential physiological response to medications. However, even in scientific literature there is no consensus and gender is, often, used in place of sex. In order to avoid confusion, hereafter, the term sex‑gender will be used. So, if sex‑gender is of major importance in biology, why there is a bias in clinical studies?
Sex‑gender bias in clinical trials has an historical reason: the (wrong) assumption that man and woman are biologically similar and treatments tested in men are, therefore, equally effective in women. In addition, it is easier to recruit male patients. Recruitment campaigns among military personnel were effective. For many generations women were stay‑home wives and primary caregivers (participation in clinical studies was a time burden for their family obligations), with limited access to information about clinical trials, and a reduced travel mobility to and from clinical trial centers (financial burden). Additionally, recruiters did not wish to deal with the monthly hormonal fluctuations and its direct influence on the pharmacokinectics of a drug. If only this last critical point had been taken into consideration when designing clinical trials, many lives would have been saved! Some studies are quite curious. In the 80’s a trial to evaluate the influence of obesity in uterine cancer used a sample population of male volunteers only. Yep, you read it correctly! It is surprising to notice how the principal investigator designing such study (and the ethical commission approving it) did not take into consideration the rational approach that males don’t even have a uterus! Notably, until the 90’s, FDA recommended the exclusion of women of child‑bearing age in studies to test drugs. In sum, studying the effect of drugs in male models was, simply, the norm!
An effective change in this paradigm happened in the 90’s and resulted from concerns over the health risk of prescription drugs in the female population. Severe side effects were reported, leading to the withdraw of about 10 prescription drugs in a period of 4 years. Strikingly, the safety and efficacy of majority of these approved drugs was evaluated in strict clinical trials where women were, in fact, underrepresented. Cross‑sectional studies advocated by FDA and NIH revealed a dark side of sex‑gender bias in clinical trial studies. A subject that made the headlines was the recurrent incorrect diagnosis and treatment of coronary heart diseases in women. In one hand, there was a major gender stereotyping and bias by healthcare providers. Despite an equal prevalence of cardiac diseases, the perception that it is a male disease led often to misdiagnosis (symptoms were seen as panic attacks or hypochondriac behavior) and reduced follow up tests in female patients admitted to hospital. On the other hand, bias in clinical trial studies result in incorrect prevention measures of coronary heart diseases. For example, while aspirin therapy is efficient in the prevention of heart failure in men, it was, later on, shown to have no preventive effect in women. One way to avoid the negative outcomes of uneven sex‑gender clinical trials was the establishment of single-sex studies before the approval of the drug. This measure ensured that the benefits observed in the studied male population were also applicable to women. Nevertheless, single‑sex studies are far from effective, because the sample size is not big enough to fully detect the effect of the drug in women. The awareness of a sex‑gender disproportional enrollment in clinical trials and its consequences in the prevention and treatment of diseases resulted in major policies change. In fact, the new implemented guidelines specified that participants should be representative of the population (not only at the sex-gender level but also to include minority groups). Moreover, pharmacokinetics, pharmodynamics, safety, and efficacy of the tested drug have to be evaluated in every population subsets before approval for commercialization.
What is the current situation of sex‑gender bias in clinical trials? This is really a hard question to address. It is widely observed an increase in the number of female participants in clinical trial studies, over the last two decades. Yet, it is difficult to know the accurate recruitment ratio, despite strong policies that foster the analysis of data by sex. Confidentiality policies to safeguard the identity of participants in clinical trials restrict the access to demographic indicators of the sample population. Moreover, depending on the clinical trial database and the peer‑reviewed journal where the study was published, there is no requirement to report the percentage of male and female participants and, thus, a high percentage of studies lack this information. As a consequence, data relative to sex‑gender in clinical trial studies lacks consistency and this is problematic. First, it raises questions on the safety and efficacy of prescription drugs to female patients. Healthcare professionals and female patients have the right to access this kind of information, in order to make conscientious decisions on the diverse treatment options. Second and foremost, the amount of data gathered in large clinical trials is not entirely examined. The inability to sort out the data by sex impairs scientist to gain insight on a variety of biomedical information that is sex specific. There are remarkable differences in pharmacokinetics and pharmacodynamics of a specific drug that are dependent on the physiology of the sexes. A meta‑data analysis of the different biological characteristics inherent to the sex can only result in an insightful knowledge of a variety of diseases and, thus, in the design of effective therapeutics. This is of particular relevance in an age where we evolve to personalized treatments. How can we have personalized prescriptions drugs when we don’t fully understand its effect in the different subsets of the population? And this goes beyond the sex‑gender. An inclusive understanding of the biological variability within a population based on race, ethnicity, age, can only bear globally beneficial fruits.
The scientific community is aware of the sex‑gender bias not only in clinical trials studies but also in basic research. Physiologic differences are observed at a cellular level but most models for pre‑clinical studies of diseases remain based on male cells and/or animals. Quite a big debate on which is the best approach to establish a model to understand diseases in a holistic and integrative manner. Concerning clinical studies, progress in the last decades is remarkable. Some work has been dedicated to monitor whether equal percentage of men and women are enrolled in clinical studies. No statistical significant difference is observed between sex‑genders in phases II and III (48% and 49% females, respectively) of clinical trials, compared to 22% of females in phase I. This is an encouraging indicator that, after an initial safety and efficacy screening, deeper testing of a drug in the different subsets of a population is carried out and ensures a reduced potential health risk for general population who will use the prescription drug. However, some other studies indicate a clear bias in clinical trials, without an explanation for men over-representation, and revealing a pattern hard to change in clinical research. Those studies argue in favor of a full disclosure of the percentage of men and women in the sample population to unravel and solve issues intrinsic to design of trials and interpretation of data but also present in implemented procedures in clinical practice.
Going forward, large set of epidemiological data sorted by sex‑gender, race, ethnicity, age, and even social and environmental living conditions, combined with genetic and metabolic studies can be useful in the better understanding of diseases, discovery of drugs, and the development of accurate diagnosis and treatment options. Medical writers also have a role in this issue. A consistency of terminology used across regulatory and communication documents, both for the scientific community and lay people, can contribute to reduce the variability of findings and misinterpretation of data. In an age where the term gender (specifically gender fluidity) gains popularity, attention to the biological significance of sex in the development of diseases and response to pharmacological therapies is necessary. Only this way we can have an insightful understanding of physiological nature of sexes and provide a better healthcare for all.
Criado‑Perez. Invisible Women: Exposing Data Bias in a World Designed for Men. 1st ed. Harry N. Abrams, 2019.
Daugherty et al., 2017. Implicit Gender Bias and the Use of Cardiovascular Tests Among Cardiologists. J Am Heart Assoc. 6(12). pii: e006872.
Franconi et al., 2019. Sex-Gender Variable: Methodological Recommendations for Increasing Scientific Value of Clinical Studies. Cells 8(5). pii: E476.
Ka et al., 2016. Women’s involvement in clinical trials: historical perspective and future implications.Pharm Pract (Granada) 14(1):708.
Kim & Menon, 2009. Status of Women in Cardiovascular Clinical Trials.Arterioscler Thromb Vasc Biol. 29(3):279-83.
Labots et al. 2018. Gender differences in clinical registration trials: is there a real problem? Br J Clin Pharmacol. 84(4):700-707.
Mazure & Jones, 2015. Twenty years and still counting: including women as participants and studying sex and gender in biomedical research. BMC Womens Health. 15:94.
Phillips & Hamberg, 2016. Doubly blind: a systematic review of gender in randomised controlled trials. Glob Health Action. 9:29597.
First of all, what is a medical writing? Well, it is a written text about medicine, simple right? Actually, it’s not that straightforward. Many types of documents fall under the umbrella of medical writing, from scientific manuscripts, medical brochures, regulatory documents, or educational material, just to name few. To add a layer of complexity, medical writing can be a fluid concept, with the different branches interlinked or even overlapping. In recent years, medical writing became an attractive career path for many scientific researchers with a passion for writing. Regulatory and medical communications, two known branches within medical writing, are important departments in Pharma/Medical Devices industries. The increasing stringent legislations triggers a need for qualified writers who effectively communicate discoveries, provide documentation certifying all requirements are met, and guarantee, through lay language, the benefit and safety of the products to the general public. Academic modus operandi is also transmuting and medical writers are gaining a pivotal role. This is evident at top‑notch Institutes, where medical writers support complex funding applications and ensure the publication of data with the highest quality level at short timelines. Moreover, the emerging business of ‘wellness/healthy lifestyle’ is leading to a paradigm change in healthcare communication. We observe a shift from the individual blog (and other social medial), aiming to share personal experiences and convictions, to a growing demand for a much credible, scientific based communication. In this line, many entrepreneurs and corporations soon realized the benefit to invest in effective medical communication and educational material to attract customers, creating, thus, a new niche for medical writers. Taking all together, one can only predict a bright future and that medical writing is, indeed, a trendy career path with many opportunities for growth. So, why are uncertainty clouds invading a sky bursting of prospects?
The advance of technology results in globally accessible medicines and a longer life expectancy, making medical and healthcare industries a growing business with a revenue of billions. Paradoxically, this sector remains quite traditional and resistant to a rapid implementation of technology. This is the case of Artificial intelligence (AI), which is a reality transforming many business sectors, from transports to telecommunications. Remarkably, the potential application of machine-learning technology in the medical and healthcare industries is revolutionary, yet its implementation is, still, at an embryonic stage. A growing number of start‑ups and companies invest millions to develop and improve tools to alleviate the burden of medical and healthcare professionals. DeepMind Health and IBM Watson have already successfully placed some AI programs in the market. Notably, AI developed by IBM Watson for Oncology, has accurately diagnosed a patient through analysis of thousands of genetic data, databases of patients medical records, and millions of research articles. In the Pharma industry, AI also has numerous applications in clinical trials, from the initial step of drug discovery (drug identification, validation, biomarker identification, target discovery…) to a complete analysis of tens of thousands of patient data, reducing greatly the process (and costs!) by which a drug is approved. Overall, the prospects of AI in the medical and healthcare industries translates into a customized, cost effective healthcare service, with increasing treatment options and practical implications in the daily life of billions.
AI grows towards a technological disruption and, consequently, a disruption of the current medical writing landscape is expected. Many Pharma/Medical Devices companies are investing in supercomputers to facilitate the complex regulatory writing process. AI tools, such as Natural Language Processing (NPL), are rapidly revolutionizing the ‘language’ technology, greatly due to the competitive interest of Microsoft, Google, or Amazon. The ongoing development of NLP customized to the needs of Pharma/Medical Devices industries results in tools that easily scan meta‑data, perform deep and tailored literature searches, and extract targeted information from vast unstructured full-text databases. This simplifies the preparation of many documents in a fraction of time (with cost benefits) and is relevant in the case of Clinical Study Reports, where a large percentage of the final text is pulled out from source documents. The automation of standard documents by AI tools has also undeniable advantages at many levels. It reduces the burden of medical records by clinical staff, decreasing human errors and promoting a higher anonymization of patients enrolled in clinical trial studies. Moreover, NPL technology is useful for exhaustive systematic reviews and, even, for the design of new studies, based on the identification of potential relevant data issued from a customized cross‑check of thousands of (full text) publications otherwise missed in citation or keyword based searches.
The revolutionary progress of AI in the coming years will, indubitably, transform the field of medical writing. Will AI replace the medical writer? AI will trigger a shift in the craft of medical writing. The medical writer will no longer be the person who gathers pieces of information from the different sources into a final succinct document. The medical writer of the future will expand his skills to use AI tools, in a complementary fashion, and enhance the writing process. A big advantage of AI technology is the reduction of the burden of clinical review. The extraction of information from source documents accurately and consistently coupled to standardized structured documents will reduce the errors and, consequently, the review cycles. The medical writer will ensure the final document has a clear and concise language and meets all requirements. Highly skilled medical writers can apply their know‑how to produce complex scientific work. The plethora of data available is invaluable yet it’s a challenge to extract meaningful information from complex and often unstructured databases. Medical writers can successfully use AI technology to perform target analyses of meta‑data, identify potentially new treatments or even hidden findings that will contribute to the advancement of a personalized and effective medicine. Furthermore, it is important to keep in mind that medical writers have a major role bridging Pharma/Medical Devices industries, legal authorities, healthcare providers, patients and the general public. The success of this role is correlated with their distinctive set of soft skills, unlikely to be easily mimicked and surpassed by AI.
In summary, the intersection between medical writer and AI will have major implications across medical and healthcare industries, with significant reduction of time and costs required for the commercialization of new medical products. Moreover, a higher disclosure of information to a wider audience, in a transparent and accessible language, will promote a strong awareness and trust in medical and healthcare industries, expand the access to innovative treatments, and contribute to better (and personalized) decisions of patients and healthcare professionals. AI‑driven innovations can only be a window of opportunities for medical writers to expand their skills and to thrive in this trendy career path!
Extance A, 2018. How AI technology can tame the scientific literature. Nature 561(7722):273-274.
Loh E, 2018. Medicine and the rise of the robots: a qualitative review of recent advances of artificial intelligence in health. BMJ Leader 2:59–63.
Velupillai et al., 2018. Using clinical Natural Language Processing for health outcomes research: overview and actionable suggestions for future advances. J Biomed Inform 88:11-19
Ensuing John Oliver’s (Last Week Tonight, HBO) humorous analysis of very serious problem within the Medical Devices Industry, I took a look at the current regulatory landscape of medical devices (MD) in the European Union (EU). Like in USA, MD industry has been involved in many scandals over the years. The PIP silicone breast implants’ fraud (France, 2009-2013) was publically scrutinized and led to an increasing mistrust in the multimillion euro MD industry.
The European Commission expressed concerns for the protection and safety of patients by outdated MD’s legislations and proposed revision and amendments, which entered into force in 2017. Currently, we are in a transition period between EU directives and EU regulations for MD. These regulations are divided in two categories, namely Medical Devices Regulation (Regulation (EU) 2017/745, applicable in May 2020) and the In-vitro Diagnostic Regulation (Regulation (EU) 2017/746, applicable in May 2022). The aim is to strength the process by which a MD earns the CE (Conformité Européenne) mark certification that guarantees its quality, safety, efficacy, as well its post‑market monitoring. What does this mean for us, medical writers and European citizens?
A first change with the new regulatory framework is the reinforcement of the responsibility of the European Medicine Agency (EMA) to ensure MD meet all legal requirements, including the assessment of conformity issued by accredited Notified Bodies (certified agencies by the country where the marketing application is filled). For the manufacturers, this translates into a large amount of documentation to be updated, or generated, for each MD already placed in the market. This is problematic for the MD industry because of the short transition time between directives and new regulations (3 years for MD), yet it represents a window of opportunity for medical writers.
A major change with the Regulation EU 2017/745 concerns the classification of MD, with the application of new definitions and up‑classification of some MD. This is a critical point due to the different requirements and scrutiny for each class of MD. The MD classification is based on the potential risks and vulnerability of the human body and is divided into 3 classes (I, II, III). Class I (plaster, bandages, stethoscope) represent the lowest risk class and it is subject to the least scrutiny, while class III (implantable MD) represents the highest risk and must conform to a strict clinical evaluation and an independent conformity assessment by Notified Body. With the increasing use of software applications (apps) and online remote patient monitoring systems, an update on the definition of MD was necessary to legally protect the patients. Now, software with a medical purpose is considered to be an active medical device and its classification is dependent on its risk to the patient. Moreover, software associated with a device now falls automatically into the same class of the device and is evaluated accordingly. In practice, this means that MD that were exempted of a strict evaluation now will be extensively scrutinized during the assessment of conformity.
In order to be approved for marketing, the MD undergoes evaluation studies. Briefly, these studies consist of (a) a systematic review of literature to determine the safety and performance of similar devices, (b) an extensive analyse of clinical investigation data ensuring the safety and benefit of the MD, and (c) a collection of the alternative treatment options available to demonstrate the advantage of the MD. On top of these proofs, class IIB and III MD are required to show further clinical evidence of safety and efficacy, through clinical trials, and the manufacturer has to submit clinical investigation protocols and clinical reports/evaluation among other technical documents. Thus, the stringent rules of the new regulatory framework results in an extensive list of documents to be provided by manufacturers and the MEDDEV (MEDical DEVice) guidelines have already been amended to meet the new requirements.
Surveillance, monitoring, tractability and transparency are critical points to take in consideration. The PIP silicone breast implants’ scandal brought to light a gap in the surveillance of the MD post-market. To comply with Regulation (EU) 2017/745, manufacturers will have to frequently provide safety update and clinical performance reports (annually for class IIB and III), and declare all adverse events occurred during the clinical studies and throughout the MD lifecycle (post‑market). The post‑market surveillance requires PMCF (Post‑market Clinical Follow‑up) studies to evaluate of the risk/benefit of the MD, particularly for high risk classes. This includes new clinical investigation data, analysis of data from observational studies and also from the continuous follow‑up of the patients from the pre‑market clinical investigations studies. An additional major implementation of the new regulatory framework is the obligation of a lay summary for each device published in every official European language. Also, it will be mandatory to attribute an identification number (UDI for Unique Device Identification) to each MD that identifies the labeller and the specific version/model. This measure will enhance the safety of patients by promoting a close traceability and transparency of MD during their lifecycle and facilitate an efficient recall in case defects are reported in similar devices. Moreover, and in line with the transparency measures, information about the safety of MD must be publically available. For this purpose, Eudamed will be partially accessible to the general public. Eudamed is a centralised repository for information exchange between competent authorities that promotes market’s surveillance and aims to increase the safety standards for MD industry. While only competent authorities have full access to the Eudamed database, information regarding the MD, manufactures and authorized representatives, notify bodies, as well as certificates and field safety notices will be available for consultation by the general public. A transparent, official, and intuitive database enables patients, families, and healthcare providers to make informed decisions and promotes a trust of the general public in the MD industry.
In sum, with the new regulatory framework that will be applicable in 2020 for MD, manufacturers have to generate and update extended documentation that ensures MD complies with stringent conformity assessments and meets the surveillance requirements for safety throughout its lifecycle. This translates to a demanding need for qualified professionals that are able to write a plethora of documents in the short transition period between the previous directives and the implementation of new regulations. Furthermore, surveillance and transparency are critical measures and manufacturers are obligated to provide frequent evaluation reports to competent authorities, besides lay information to the general public. Science moves at fast pace and, technologically speaking, times are revolutionary! Humans are living longer and longer and to maintain (or attain, in some cases) a good life quality, the replacement of ‘defective parts’ becomes trivial. A medical cyborg is no longer a futuristic utopic creature, they are already among us and, at some stage in our lives, we will also (gladly) become one. The future holds huge perspectives for therapy, from tissue engineering and organ printing to brain‑machine interfaces. Moreover, a new generation of implantable MD is at the corner, where prosthetics will be, progressively, replaced by biocompatible integrated electronic devices and immune therapy will rely on nano-machines that selectively target the area to be treated. A whole range of technology will converge to create a personalized medicine, from the initial steps of diagnose to the final therapeutic. This high‑speed technological prospect entails a multidisciplinary team (scientists, healthcare professionals, politicians, lawyers, ethical experts, stakeholders…) that bring a holistic view to evaluate the risks and benefits of MD. It is inevitable, in the near future, amendments of the regulations that entered into force in 2017 and the implementation of new ones that keep up with technological advances. Medical writers have a role in those multidisciplinary teams and are key players in the disclosure of information, within the MD industry and to the general public. The window of opportunities is, therefore, wide open for medical writers. We can only embrace these revolutionary times to expand horizons and thrive in an ever-growing MD industry, which, indubitably, will have a profound impact in our healthcare in the following decade(s)!
Giselbrecht et al., 2013. The chemistry of cyborgs- interfacing technical devices with organisms. Angew Chem Int Ed Engl. 52 (52):13942-57. doi: 10.1002/anie.201307495.