The events of 2020 exposed stark healthcare and social disparities in the U.S., emphasizing the urgent need for more inclusive clinical trials, especially in the wake of Moderna's initial underrepresentation of communities of color in their COVID-19 vaccine study. While the FDA has introduced policies promoting diversity, equity, and inclusion in clinical trials, there's a growing recognition that simply following guidance isn't enough; intelligent data-driven strategies are crucial to ensure meaningful progress and accountability in addressing these disparities.

Inequities in clinical trial participation persist, with underrepresented communities often missing out due to barriers and biases. Artificial intelligence (AI) offers a promising solution by identifying underrepresented populations, breaking down language barriers, tailoring outreach, enabling virtual participation, improving trial design, and mitigating biases, thereby fostering greater diversity and inclusivity in clinical trials.

Article in Forbes regarding Diversity in BioTech

Artificial intelligence could help improve diversity, equity, and inclusion in clinical trials and drug development by overcoming some traditional human bias in these areas, but we’re not there yet, experts say. The technology could also assist doctors with data insights to make diagnosis and treatment more precise.

A new resource platform, launched by the nonprofit Digital Medicine Society and industry collaborators, aims to address the lack of diversity, equity, and inclusion in digitized clinical trials. The platform focuses on aligning industrywide definitions, providing digital tools for trial stages, and offering recommendations to enhance the enrollment and retention of diverse participants, addressing a pressing issue in the drug development industry highlighted by the FDA and industry leaders.

The UK BioIndustry Association (BIA) has released its first benchmark report on diversity, equity, and inclusion (DEI) in the country's innovative life sciences and biotech sector. The report highlights the need for increased diversity in the industry and the positive impact it can have on innovation and economic growth, urging organizations to track their DEI objectives to drive sustained change.

Clinical research continues to face calls to increase the diversity of patient pools. Regulators and patient advocacy groups all demand higher inclusivity in clinical development, but so does common sense: we should be developing drugs with the entire market, in its full diversity, in mind – not a restricted subset. However, reaching out to traditionally excluded and underserved groups is easier said than done. Artificial Intelligence (AI) has made significant forays into the life sciences in the last few years, and many are already examining how it can be employed to improve diversity in clinical investigations – as well as the conclusions that are drawn from them.

Here, we’ve collated a handful of BIO 2023 impressions from attendees representing small and mid-size biotech/pharmas, consultancies, and professional organizations.

This is where our software is invaluable and helps to overcome such barriers in clinical trials. Using AI methods like natural language processing (NLP) and machine learning, we can reduce biases and reach new communities to precision-match patients for trials. These methods can help increase diversity, equity and inclusion while providing access to life saving treatments.

Sally Embrey explains how DataRobot used AI to ensure participants in COVID-19 vaccine clinical trials were representative of the entire US population

Inadequate ethnic diversity in clinical trials, restrictive eligibility criteria, delayed or absent prescribing guidance for specific populations, and access lags impacting global health are under active discussion across academic, industry, and regulatory sectors. Outreach efforts, regulatory guidelines, and pragmatic trials are bridging these gaps. Transformative progress will require cross-stakeholder commitment to responsibly embrace diversity in intrinsic and extrinsic factors in clinical development, enabled by quantitative translational sciences, a Totality of Evidence mindset, purpose, and trust.

The Center for Artificial Intelligence in Medicine (CAIM) promotes diversity and inclusion in AI research for healthcare. Its initiative DAIM (Diversity for AI in Medicine) was launched in May 2022 with a keynote lecture by a renowned medical robotics researcher.