Inclusive experiment design: making research work for everyone

To make sure that everyone can benefit from scientific advances, the principles of equality, diversity and inclusion should be built into research from the start. In the run-up to the 2019 EDIS (Equality, Diversity and Inclusion in Science and Health) Symposium, we spoke to Adepeju Oshisanya from Benevolent AI and Robin Lovell-Badge from the Crick to find out more about current efforts to diversify research.

Neuropathic pain isn’t the result of a physical injury or illness. It is the nervous system itself generating pain and patients often lack effective treatments. One research group looking for a cause made a significant discovery when they found that cells called microglia generate neuropathic pain in mice.

We're hosting the EDIS (Equality, Diversity and Inclusion in Science and Health) Symposium 2019.

Find out more about the meeting

With a specific cell to target, their newly published results opened up new opportunities for potential treatments. But when the experiments were rerun using both male and female mice, rather than the male mice used in the first experiments, they found that blocking the microglia still reversed the pain in male mice, but had no effect in female mice. If treatments had been developed to target microglia, the drugs could have been useless to half of all patients.

This is just one of the topics up for discussion at the 2019 EDIS Symposium held at the Crick, examining how the principles of equality, diversity and inclusion can be applied to scientific research. Truly inclusive research means using these principles throughout the course of research, from prioritising which topics to study and designing early-stage experiments, to diversifying participation in clinical trials and large-scale genomic data projects, to ensuring that new products and innovations have been designed with a diverse group of users in mind.

Hidden factor

Crick group leader Robin Lovell-Badge studies sex determination and will be discussing the impact of sex on biomedical research and the need for sex diversity in research animals and cells at the symposium. 

Robin explains, “Neuroscientists have been terrible at this in the past and have completely ignored female mice, often for the sake of convenience. The hormone cycles of female mice mean that there will be greater variation in your results and in order to see significant results, you have to use more mice than you would ideally want to, or maybe more mice than you can afford. But this can mean missing vital insights.”

We’re finding that sex plays a role in so many unexpected aspects of health and disease.
Robin Lovell-Badge, The Francis Crick Institute

The National Institutes of Health in the United States recently mandated that any research in mice funded by the NIH must declare the sexes of the mice used. Robin thinks that policies like these are only part of the solution, “I think mandates like these have at least been useful to raise awareness of the issue, but there’s still some way to go before it’s fully embedded in research. We’re finding that sex plays a role in so many unexpected aspects of health and disease. It’s a factor that needs to be taken into account, even in topics that we might have historically thought of as ‘sexless’ like memory and learning.”

The implications of a lack of diversity continue far beyond early-stage research. Adepeju Oshisanya is the Clinical Development Operations Leader at Benevolent AI, a company using AI to rethink the drug discovery process, and will be discussing the importance of diversity in clinical trials at the symposium. 

“When a new drug is approved, the majority of patients that it’s been tested on are from Western countries, are Caucasian and, at least in the early stages, are male,” says Adepeju. “There are significant sections of the world’s population where we don’t have the necessary information to be confident that a drug will work on them before they receive it.

“Now that we have the resources to use and interpret big data sets and combine data from trials, AI could represent an enormous opportunity to broaden the diversity of clinical trials participants. Historically, drugs have been designed for the people whose background and circumstances allow them to spend their time involved in research. Our fundamental goal should be to treat as many people as possible, and clinical trials haven’t been set up to do this.”

We’re making this amazing progress, but we have to make sure that the progress applies to everyone.
Adepeju Oshisanya, Benevolent AI

Making the change

But to increase the participation in clinical trials in these groups, Adepeju describes the “paradigm shift” that will need to occur through a number of different approaches. Running in parallel with new technology-driven initiatives like those at Benevolent AI, the United States’ Food and Drug Administration has recently issued new recommendations to expand the diversity of groups taking part in clinical trials in the United States.

Under the new FDA guidelines, clinical trials would be designed to reduce the burden on participants by, for example, replacing in person visits with electronic self-reporting. Reimbursement would be strongly recommended and clear declaration of reimbursement would be required. To safely include patient groups that could be at higher risk, clinical trials are now recommended to start with the ‘safest’ groups and expand the pool of participants to gradually include younger ages of children and adolescents and older ages of elderly people.

But Adepeju agrees that trial regulations alone won’t cause the necessary shift, “To have real change, every organisation will need to diversify the data that they use, the people that they employ and the ways that they use that data,” says Adepeju. “It’s all part of the same ecosystem – they feed into each other and you can’t do one effectively without the others.”

Truly inclusive research is nuanced and requires collaboration at every stage. While recent advances mean that biomedical research could be more inclusive than ever before, they also come with limitations.

Adepeju points to examples like the Human Genome Project, “It’s an enormous amount of data and obviously a very important project, but the genome that they published only included data from European donors, a small section of the world’s population. As the scale of our data increases, the scale of any deficiencies in that data will increase exponentially. We’re making this amazing progress, but we have to make sure that the progress applies to everyone.”

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