Improving Research Outcomes

💃🏽 “𝗪𝗲 𝗼𝘄𝗲 𝘄𝗼𝗺𝗲𝗻 𝗮 𝗰𝗲𝗻𝘁𝘂𝗿𝘆 𝗼𝗳 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵.” – 𝗟𝗶𝘀𝗮 𝗠𝗼𝘀𝗰𝗼𝗻𝗶 Until 1993, women were largely excluded from clinical trials. Not by accident, but by design 👀 Women were left out of research because our biology was seen as disruptive. Hormones made the data harder to control, so the answer was to exclude us 🤷🏽♀️ The default became male & the consequences followed. What worked in the lab didn’t always work in the real world & it still doesn’t ❌ That choice didn’t stay in the past 🔙 You can still see it in drugs that fail to accurately recognise women’s symptoms, in the medtech equipment that doesn’t quite fit in a female surgeon's hand, in the research that skips over the questions that matter to half the population 🌎 As we move into an AI-first future, we’re building on data that never really saw women to begin with. The risk isn’t just bias, it’s getting things wrong at scale 📈 If women aren’t included in the data, the systems we rely on won’t just miss us, they’ll misrepresent us. We need women shaping the research, the trials, the tech – not just for fairness, but so it actually works 📊 If we want healthcare that works for women, we need to start with research that sees us clearly, not as complications, but as standard 💭 𝗪𝗲’𝗿𝗲 𝗻𝗼𝘁 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝘀𝗽𝗲𝗰𝗶𝗮𝗹 𝘁𝗿𝗲𝗮𝘁𝗺𝗲𝗻𝘁. 𝗪𝗲’𝗿𝗲 𝗮𝘀𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝘀𝗰𝗶𝗲𝗻𝗰𝗲 𝘁𝗵𝗮𝘁 𝗿𝗲𝗳𝗹𝗲𝗰𝘁𝘀 𝗿𝗲𝗮𝗹𝗶𝘁𝘆. 𝗧𝗵𝗲𝗿𝗲’𝘀 𝗻𝗼 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝗳𝗶𝘅 𝘄𝗵𝗮𝘁 𝘄𝗲 𝗿𝗲𝗳𝘂𝘀𝗲 𝘁𝗼 𝗺𝗲𝗮𝘀𝘂𝗿𝗲 📏 -- ♻ Re-share if this resonated with you. 👩🏽⚕️ Follow Dr Fiona Pathiraja-Møller for more. #womenshealth #AI #science #clinicaltrials

Fact Filled Friday. Why we need 'Women in Data'. Diversity Drives Innovation: According to a study by McKinsey, companies with diverse teams are 25% more likely to have above-average profitability. Furthermore, research by Boston Consulting Group indicates that diverse teams drive innovation at a higher rate, with a 19% increase in revenue due to innovation. Closing the Gender Gap: The World Economic Forum reports that the gender gap in STEM fields is gradually closing with more women pursuing education and careers in science, technology, engineering, and mathematics. Organisations are recognizing this trend and initiatives like Girls Who Code have contributed to a 10% increase in female enrolment in undergraduate computer science programs. AI Ethics and Fairness: The Gendered Innovations project emphasizes the importance of gender diversity in AI development. Women's insights contribute significantly to addressing biases, as seen in a study by Nature, which found that gender-diverse teams reduce the risk of biased outcomes in machine learning by up to 40%. Inclusive AI Solutions: Research from the AI Now Institute highlights that diverse teams are more likely to consider and address the needs of various user groups. Women in AI are actively involved in creating inclusive solutions that cater to diverse demographics, ensuring equitable access to technology. A study by Harvard Business Review also notes that diverse teams are 87% better at making decisions. Continuous Learning Opportunities: According to LinkedIn's 2021 Learning Report, women are increasingly participating in upskilling and reskilling programs. The report notes a 21% increase in time spent on learning by women, showcasing their commitment to staying abreast of technological advancements. Additionally, the World Economic Forum's Future of Jobs Report 2020 highlights that the need for upskilling is more significant for women and closing the gender gap in skills could lead to a 3.2% increase in global GDP. Networking and Collaboration: Communities such as Women in Machine Learning (WiML) and organisations like Women in AI are actively contributing to knowledge-sharing and mentorship. The collaborative efforts within these networks empower women to thrive in the Data and AI space. Studies by McKinsey emphasize that gender-diverse companies are 21% more likely to outperform their counterparts in terms of profitability. #WomenInTech #DataScience #AI #DiversityInTech #FutureOfWork EXL

Happy International Women’s Day 💜 A gender gap persists in STEM globally. We’ve made progress, but women are still woefully under-represented. Tackling our greatest challenges - improving health to combating climate change to developing AI as a force for good - must harness all talent. Gender diversity expands and extends the talent pool and is essential as today’s technologies demand different ‘Power’ skills: ▪️Emotional Intelligence: to manage emotions and navigate interpersonal relationships effectively, enhancing teamwork and leadership in STEM ▪️ Collaboration: fostering effective teamwork, with a focus on joint problem-solving ▪️ Adaptability: STEM is moving fast, I see that every day, being able to quickly learn and adjust to is indispensable ▪️ Empathy: drives solutions that truly resonate with human needs ▪️ Creativity: Brings unique perspectives that fuel innovation ▪️ Ethics: development is responsible and beneficial for society However ▫️Women are given smaller research grants and, while 33.3% of all researchers, only 12% of STEM academics are women ▫️In cutting edge fields such as AI, only 1 in five (22%) is a woman ▫️Despite a shortage of skills driving the Fourth Industrial Revolution, women still account for only 28% of engineering and 40% of computer science graduates ▫️Female researchers have shorter, less well-paid careers. Their work is underrepresented in high-profile journals and they are more often passed over for promotion ▫️Although STEM fields are widely regarded as critical to economies, so far most countries have not achieved gender equality in STEM So what? Not only is this unethical, unfair it’s also misinformed, I mean stupid: ▪️The crash test dummy is a classic case. Initially, modelled on the average male body. Women were 47% more likely to be seriously injured and 17% to die in car crashes. Despite efforts, the gap in safety due to a lack of diverse testing persists ▪️Cardiovascular research has long been skewed towards men. Women are 50% more likely to be misdiagnosed with heart attacks and treatment is less effective ▪️Trials for medications did not sufficiently account for gender in pharmacokinetics so dosages were based on male biology, women experience adverse drug reactions nearly 1.7 times more often ▪️Medical devices have focused on male anatomy, for example, women are 20% more likely to have a stroke or die within 30 days of being treated with stents for artery disease ▪️Voice recognition technologies were developed using data from men leading to error rates for women’s voices up to 70% higher ▪️Famously Amazon discovered that its AI-based screening was biased against women favoring male candidates by a significant margin ▪️Facial recognition has error rates of up to 34.7% for dark-skinned women, vs 0.8% for light-skinned men So, should you need it, today is a reminder that women play a critical role in STEMs and that our participation must be strengthened #iwd2024 #BeEqual #GenderEquality #DEI

📚 #theSTORYprinciple - page 99 Sex in metabolomics Last time, we took our first peek at the second part of the book: 𝗧𝗵𝗲 𝗦𝗧𝗢𝗥𝗬 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 𝗶𝗻 𝗮𝗰𝘁𝗶𝗼𝗻 (https://lnkd.in/e2e2xJd3). This week, I want to give you my perspective on the importance of sex metadata in metabolomics. In this chapter, I cite the book by Caroline Criado Perez, "Invisible women", that I hope many of you are already familiar with (if not, do check it out!). As a seasoned biologist I thought I knew the role sex played in my experiments, and it is while reading this book that I realized I had only scratched the surface of the influence of sex in biology. And I don't mean the usual "powerful influence of hormones on our physiology". I mean how analyzing female and male results together can hide the truly interesting results in your experiments. Worse, how we (as a community) still rely on results from a single sex to draw conclusions on both. And as I put more of my focus on metabolomics, I saw just how many differences exist between women and men at the metabolic level. I discuss this in the chapter on "Intrinsic sources of variability" as sex is primarily considered a gene-driven characteristic, but given the sensitivity of metabolomics to lifestyle factors (from what we eat to the type of work we do), the line between nature and nurture is extremely blurred in this context. As a consequence, when comparing the metabolomes of people who self-identify as woman or man, metabolomics gives clear differences in terms of metabolic patterns, so if I have one piece of advice to give to anyone analyzing (metabolomics) data these days, it's this: 𝑳𝒐𝒐𝒌 𝒊𝒏𝒕𝒐 𝒔𝒆𝒙-𝒔𝒑𝒆𝒄𝒊𝒇𝒊𝒄 𝒆𝒇𝒇𝒆𝒄𝒕𝒔! As I discuss in page 99 and further, scientists generally agree that this is a good thing, while (i) not really doing it, and (ii) not being sure how to do it. There is progress on this front, in part thanks to journals that now more than ever demand a clear statement on the relevance of results to one or more sexes. So it is time to keep up in your project planning and your data analysis. To make sure you don't miss any important effects, here are a few #tips: 🎒 always keep the sex metadata for your experiment at hand 🔎 always check (early on!) if you get the same response in females and in males 👩💻 if you do find sex-based differences, don't leave it at that! Dig deeper! You now have two stories to tell! This is great 👍 ️❌ never rely on data from one sex only to infer an effect occurs in both sexes _______________________________________ 📚 To read more from #theSTORYprinciple and the tips and tricks to help you find your best story, get the #book in your own hands here: https://lnkd.in/d9x4cFgX #datainterpretation, #omics, #DItips, #datascience, #precisionmedicine, #metabolomics, #health.

Today, FDA is announcing the availability of a draft guidance for industry entitled “Study of Sex Differences in the Clinical Evaluation of Medical Products.” Differences in physiology between females and males can lead to differences in disease manifestation, pharmacokinetics, pharmacodynamics, and response to treatment. Analyzing sex-related differences in medical product response is an important component of assessing product safety and effectiveness and can inform what goes into product labeling. This guidance provides recommendations for : (1) Increasing enrollment of females in clinical trials (Phase-I, II, III and IV) and non-interventional studies to help ensure the generalizability of results, (2) Analyzing and interpreting sex-specific data, and (3) Including sex-specific information in regulatory submissions of medical products. As mentioned in section II.B of this guidance, sponsors must include in their annual reports for drug and biological products conducted under an IND, the number of participants entered into the study to date tabulated by “age group, gender, and race,” and sponsors must present safety and effectiveness data in the clinical data section of an NDA by “gender, age, and racial subgroups.” Because the enrollment demographics of the clinical study may impact the generalizability of the conclusions, for clinical studies of devices, FDA recommends that sponsors report the number and proportion of study participants by sex, and gender as appropriate, So, this is not applicable for BE study but FDA is also aware about proportion of female volunteer participation in the BE study for ANDA submission.

Addressing the sex disparities in psychedelic research is crucial for advancing therapeutic outcomes. Historically, research has neglected sex-oriented approaches, leading to gaps in our understanding of how psychedelics affect men and women differently. Current clinical studies often show a recruiting imbalance, and animal studies lack standardization in understanding these mechanisms. Given the interactions between serotonin (5-HT) and estrogen, the role of sex hormones, especially estrogen, in these differences cannot be overlooked. Estrogen may significantly influence the effects of psychedelics, highlighting the need for sex-specific research methodologies. Incorporating Sex as a Biological Variable (SABV) into research design is essential, though challenging due to traditional practices, ethical concerns, and increased study complexities. An important first step is inclusive investigations involving female participants across different menstrual cycle stages and age ranges. By examining the effects of psychedelics throughout these stages, we can better understand their efficacy and develop tailored treatments for psychiatric conditions. This approach ensures a more comprehensive understanding of psychedelic efficacy and paves the way for more effective therapies for both sexes.

Despite the growing use of in vitro models to study neurological disorders, one critical factor is still often overlooked: biological sex and gender! In their new Review, Laura Castro-Aldrete Dr Antonella Santuccione Chadha and team from the Women's Brain Foundation explore how the historical neglect of sex and gender differences in preclinical and clinical research has contributed to a persistent translation gap in neuroscience. They discuss how sex differences impact mechanisms in neuropsychiatric and neurodegenerative disorders and the importance of integrating sex as a biological variable in both in vitro and in vivo models. They also provide a roadmap for best practices using cell lines, iPSCs, 3D organoids and organ-on-a-chip systems. Incorporating sex differences is not just good science, it is essential for developing more precise, replicable and translatable research tools for brain disorders. https://lnkd.in/eZHmQ3g4

Have you heard of the MESSAGE project? MESSAGE as in - MEdical Science Sex And Gender Equity Integrating sex and gender into biomedical research is essential for advancing scientific quality and health outcomes. The MESSAGE project highlights the need for a whole system approach and technical capacity-building to drive this change. 💰Funder Policies: Initial steps to shape study designs. 🤝Sector-Wide Collaboration: Ensuring cohesion between organizations. 🌈Transparency: Publishing detailed sex and gender characteristics. I agree, greater transparency and collaboration can lead to a paradigm shift in research practices, promoting robust and reproducible science. Advocating for these necessary changes will empower women's health. But I cannot help to notice that one core element is missing: 💘Accessibility. The way we design research studies and clinical trials is not always accessible to women or compatible with the female physiology. Something I have experienced first hand. And this is important because genders even differ when it comes to: 🗝️Recruitment: Traditional recruitment methods may not reach diverse populations of women, particularly those from underrepresented groups. 🩸Physiology: Many studies don’t account for the menstrual cycle, pregnancy, and menopause, leading to gaps in data and potentially flawed conclusions. 💁♀️Participant Support: Providing appropriate support for female participants, such as childcare or flexible scheduling, can increase participation and retention, thus improving the quality of the research. Greater transparency and collaboration can lead to a paradigm shift in research practices, promoting robust and reproducible science. Any idea on how we could do this right?

Our latest study, published in BMJ Global Health, underscores a crucial yet often overlooked truth: women’s leadership isn’t just about equity—it’s about impact. The majority of studies reported a positive impact of women's leadership in 6 areas of impact: 1. Financial performance, risk, and stability 2. Innovation 3. Engagement with ethical and sustainability initiatives 4. Health outcomes 5. Organizational culture and climate, including reputation, employee retention, and team cohesion and communication 6. Influence on other women’s careers and aspirations. Even those studies reporting mixed findings still largely pointed to positive results, particularly when modified by other factors, such as better education, greater levels of experience, and opportunities to work with other women across an organization. This paper sheds light on the evidence behind why we must do more to support and sustain women’s leadership. 🌍 📖 Read more here: https://lnkd.in/e9imfQyV This research is funded by The Global Financing Facility (GFF) and is part of a mixed-methods study conducted across sub-Saharan Africa on the impact of women's leadership on gender and health outcomes. More to come! Johns Hopkins Bloomberg School of Public Health, Johns Hopkins Center for Global Women's Health & Gender Equity, Department of International Health, Johns Hopkins Bloomberg School of Public Health, WomenLift Health, Women in Global Health, Rosemary Morgan, PhD, Charlotte Pram Nielsen, Katherine Banchoff, Kelly E. Perry, MPH, Anju Malhotra