Technology
approach, where the clinician has additional information and interaction with the patient to confirm the results of AI systems is seen by many as crucial for maintaining the integrity of AI systems in healthcare. The emergence of FemTech and the
incorporation of AI in MedTech offer promising opportunities to enhance women’s health and well-being. Regulation needs to address the important issue of data privacy and security as this is closely connected to women’s rights and trust in providing sensitive health data, while ensuring that existing data sets are broadened to be more inclusive to consider differences between male and female health experiences and outcomes. While digital advancements are exciting and hold much promise, they also pose significant issues, especially concerning bias in AI models. Tackling these challenges necessitates comprehensive strategies for detecting and mitigating bias, alongside robust regulatory frameworks to ensure the overall performance, safety and efficacy of the medical device they are used in. Only by taking a joined-up approach that sees the involvement of industry as well as regulators will it be possible to adequately address these issues, enabling the market to fully leverage AI’s potential in FemTech, resulting in more equitable and effective healthcare outcomes for women worldwide.
References 1. Technology’s Legal Edge, Femtech and the use of AI, 6th June 2024, Accessed at: https://www.
technologyslegaledge.com/2024/06/femtech- and-the-use-of-ai/
2. Business ITN, Women’s Health in Focus: Closing the UK Gender Health Gap, 12th February 2024. Accessed at:
https://business.itn.co.uk/ womens-health-in-focus-closing-the-uk- gender-health-gap/
3. Sifted, Even in femtech, it still pays to be a male founder, 18th October 2023, Accessed at:
https://sifted.eu/articles/even-in-femtech-it- still-pays-to-be-a-male-founder
4. Taylor CR, Monga N, Johnson C, Hawley JR, Patel M. Artificial Intelligence Applications in Breast Imaging: Current Status and Future Directions. Diagnostics (Basel). 2023 Jun 13;13(12):2041. doi: 10.3390/diagnostics13122041. PMID: 37370936; PMCID: PMC10296832.
5. Almeida, Teresa & Mehrnezhad, Maryam. (2021). Caring for Intimate Data in Fertility Technologies. 10.1145/3411764.3445132.
6. Orcha Health, Period Tracker Apps Share Data, 21st July 2022
7. Science, Dissecting racial bias in an algorithm used to manage the health of populations,
34
www.clinicalservicesjournal.com I August 2024
25th October 2019 Accessed at: https://www.
science.org/doi/10.1126/science.aax2342
8. Scientific American, Racial Bias Found in a Major Health Care Risk Algorithm, 24th October 2019. Accessed at: https://www.
scientificamerican.com/article/racial-bias- found-in-a-major-health-care-risk-algorithm/
CSJ
9. Epstein NK, Harpaz M, Abo-Molhem M, Yehuda D, Tau N, Yahav D. Women’s Representation in RCTs Evaluating FDA-Supervised Medical Devices: A Systematic Review. JAMA Intern Med. Published online June 10, 2024. doi:10.1001/jamainternmed.2024.1011, https://
lifesciencesintelligence.com/news/women- are-underrepresented-in-medical-device- clinical-trials
10. Women at the Table, Gender Data Health Gap, November 2023. Accessed at:
https://femtechnology.org/wp-content/ uploads/2019/07/Copy-of-Gender-Data-Health- Gap-PFG.pdf
11. Ibid. 12. Ibid. 13.
Gov.co.uk, MHRA launches AI Airlock to address challenges for regulating medical devices that use Artificial Intelligence, 9th May 2024. Accessed at:
https://www.gov.uk/government/ news/mhra-launches-ai-airlock-to-address- challenges-for-regulating-medical-devices- that-use-artificial-intelligence
14. FDA, Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices. Accessed at:
https://www.fda.gov/medical- devices/software-medical-device-samd/ artificial-intelligence-and-machine-learning- aiml-enabled-medical-devices
15. FDA, Marketing Submission Recommendations
for a Predetermined Change Control Plan for Artificial Intelligence/Machine Learning (AI/ ML)-Enabled Device Software Functions Draft Guidance for Industry and Food and Drug Administration Staff, April 2023. Accessed at:
https://www.fda.gov/regulatory-information/ search-fda-guidance-documents/marketing- submission-recommendations-predetermined- change-control-plan-artificial
About the author
Tim Bubb is the Technical Director at IMed Consultancy. With more than ten years’ experience in QA/RA roles, Tim has breadth and depth of knowledge across the regulatory, engineering, clinical, design and development, and quality assurance disciplines. Tim has a passion for empowering innovation in medical devices, contributing insight and pragmatism to projects, and bringing complex lifesaving and life enhancing products to market.
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