AI for Pharma Growth
E190: AI-Powered Women's Health: Closing the Gender Data Gap in Medical Research
AI for Pharma Growth
•November 5, 2025•33 min
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AI for Pharma Growth•Nov 5, 2025
Key Takeaways
- •Women underrepresented in clinical trials, causing ineffective treatments.
- •AI can analyze diverse real‑world data to close gender gap.
- •Bias in AI models amplifies racial and gender health disparities.
- •Menotracker uses AI to personalize perimenopause symptom tracking.
- •Diverse, user‑generated data improves AI accuracy for women's health.
Pulse Analysis
The episode spotlights a persistent gender data gap: most medical research and drug testing still rely on male participants, yet results are applied to women. This mismatch leads to misdiagnoses, ineffective pain medication, and even fatal outcomes such as missed heart attacks. By leveraging AI‑driven analytics, researchers can mine large, real‑world datasets—wearables, electronic health records, and patient‑reported outcomes—to uncover how diseases and treatments uniquely affect women. Closing this gap is essential for equitable care and for pharmaceutical companies seeking accurate efficacy data.
Artificial intelligence offers a double‑edged sword. On one hand, machine‑learning models can rapidly process millions of data points, revealing subtle symptom patterns that clinicians miss during brief appointments. On the other, biased training sets—often lacking racial and gender diversity—can amplify existing health inequities, as seen in AI‑based dermatology tools that perform poorly on darker skin tones. Entrepreneurs like Sonia Rincon, founder of Menotracker, illustrate how purpose‑built AI can turn perimenopausal symptom diaries into actionable insights, while deliberately curating a global, multilingual user base to mitigate bias. Success stories such as AI‑enhanced mammography further demonstrate the technology’s potential when data diversity is prioritized.
Looking forward, pharma executives must embed diversity at the earliest stages of AI model development, integrating patient‑generated data from apps, wearables, and longitudinal health records. Real‑world evidence platforms can reduce trial costs, expand enrollment beyond traditional clinic settings, and accelerate personalized medicine for women. By committing to inclusive datasets and transparent algorithms, the industry can transform the gender data gap from a systemic flaw into a catalyst for innovative, equitable healthcare solutions.
Episode Description
For decades, medical research has been built around male data — leaving women dangerously underrepresented in clinical trials, drug development, and symptom understanding. The result? Misdiagnoses, ineffective treatments, and life-threatening blind spots in women’s healthcare.
In this episode, Sonja Rincon, CEO and founder of MenoTracker, reveals how artificial intelligence is finally beginning to close the gender data gap in medicine. By using AI-powered analytics, machine learning, and real-world data, her platform is transforming how we understand perimenopause, menopause, and the broader landscape of women’s health research.
Sonja explains how AI can:
Detect patterns in women’s symptoms that doctors miss due to limited time and fragmented data
Use mobile health apps, wearables, and electronic health records to build inclusive, large-scale data sets
Address bias in healthcare algorithms and promote diversity in AI training data
Enable personalised medicine and tailored treatments for women
Empower women to track, understand, and advocate for their health
From uncovering why AI algorithms have racial and gender bias to reimagining perimenopause tracking for 177 countries, this episode is a must-listen for anyone passionate about the future of AI in healthcare, digital health innovation, and gender equality in medicine.
Sonja also highlights shocking realities — like how 58% of medical textbooks don’t cover menopause — and how AI can shorten the average diagnosis time for perimenopause from 7.4 years to just days.
Whether you’re a healthcare innovator, data scientist, or simply someone who believes in inclusive innovation, this episode will reshape how you think about AI’s role in women’s health.
About the Podcast
AI for Pharma Growth is a podcast focused on exploring how artificial intelligence can revolutionise healthcare by addressing disparities and creating equitable systems. Join us as we unpack groundbreaking technologies, real-world applications, and expert insights to inspire a healthier, more equitable future.
This show brings together leading experts and changemakers to demystify AI and show how it’s being used to transform healthcare. Whether you're in the medical field, technology sector, or just curious about AI’s role in social good, this podcast offers valuable insights.
AI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr. Andree Bates created to help organisations understand how the use of AI based technologies can easily save them time and grow their brands and business. This show blends deep experience in the sector with demystifying AI for all pharma people, from start up biotech right through to Big Pharma. In this podcast Dr Andree will teach you the tried and true secrets to building a pharma company using AI that anyone can use, at any budget.
As the author of many peer-reviewed journals and having addressed over 500 industry conferences across the globe, Dr Andree Bates uses her obsession with all things AI and futuretech to help you to navigate through the, sometimes confusing but, magical world of AI powered tools to grow pharma businesses.
This podcast features many experts who have developed powerful AI powered tools that are the secret behind some time saving and supercharged revenue generating business results. Those who share their stories and expertise show how AI can be applied to sales, marketing, production, social media, psychology, customer insights and so much more.
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