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How inclusion affects product design in pharma

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Raafi-Karim Alidina, consultant at Included looks at why diversity is crucial when it comes to product development within pharma and life sciences.

Many organisations are realising the need for change. This has been catalysed by the Black Lives Matter movement and the inequalities highlighted by the pandemic. The need to be actively anti-racist has become more apparent and urgent, with organisations rightly under pressure from internal and external forces. This leaves leaders with the task of addressing bias in processes, structures, and behaviours. Many turned to technology, on the logic that this would remove the bias that is unconscious in people and create a more equal, inclusive approach. This thinking, however, is flawed as these machines and algorithms are still created by people. This leads to the creation of biased technology.

Bias in technology design

Recently, I went to a barbecue restaurant with my partner. When I went to the bathroom to wash my hands, everything was touchless: there were automatic faucets, hand dryers, soap dispensers… even an automatic paper towel dispenser. However, as soon as I tried to use any of them, they wouldn’t work! No matter what I did, I just couldn’t get the sensor to detect my hands and dispense water or soap. Then, someone else came into the bathroom and tried to wash his hands and everything worked perfectly. What was the difference? His skin was white, while mine was brown.

If you’re a person of colour, you are probably familiar with the fact that most automatic taps, hand dryers, and soap dispensers in public bathrooms don’t work as well for you as they do for your white friends.

This stems from how these products were designed and who they were designed by. They were built on a training set that was not diverse, using pictures of predominantly white skinned hands, thus embedding this bias into how the product would function. When it impacts automatic taps, hand dryers, and soap dispensers it is an annoying problem for people of colour. But the real problem comes when the same object-detection system is deployed in technology such as self-driving cars. A study at Georgia Tech University in the US found that many of the autonomous vehicles being developed that used these systems were significantly worse at detecting – and so stopping for – dark-skinned pedestrians. This technology could pose a very real threat to Black and brown people and lead to injuries and deaths. This isn’t the only example of coded bias and it impacts all kinds of products. From crash test dummies that are modelled exclusively on the average male body, Amazon’s biased hiring algorithm, to Google’s failed launch of their reverse image search (which identified Black people as 'gorillas'), or even a lot of voice recognition software that can’t accurately detect the voices of Black people (nor of many accents).

Inclusion needs to be in the design process, not just to avoid inconvenience but to avoid serious consequences for the public.

Two main issues drive this coded bias. Firstly, the lack of diversity in the product building teams. Non-diverse teams are less likely to spot issues that may impact a different demographic group than those they are part of. Secondly, there is a lack of inclusion in these teams. Where diverse teams exist, those from marginalised groups are often not able to speak up and be heard. This can be due to insufficient psychological safety stemming from the organisation’s culture.

How does this impact pharma?

Pharma is not immune to this coded bias. For example, women have been excluded from drug trials for decades with no evidence-based justification for not including a demographic that makes up 51% of the global population. This has very real implications, as the dosage amounts have been decided by male-dominated clinical trials which has led to women experiencing worse side effects than their male counterparts. For example, a recent study from UC Berkeley and UChicago conducted in 2020 found that across the 86 drugs they looked at (all approved by the US Federal Drug Administration) women suffered worse side-effects in more than 90% of cases. These side effects were not just headaches and nausea (though those were some of them), but major issues like seizures, hallucinations, and cardiac anomalies.

The study notes that even extremely common drugs like sleep medication Ambien have different effects on men and women – it “lingers longer in the blood of women than of men, causing next-morning drowsiness, substantial cognitive impairment, and increased traffic accidents.” It wasn’t until 2013 that people noticed and dosage recommendations decreased for women.

As with the coded bias in technology, a lack of team diversity and inclusivity is the driving issue here. Teams made up of people from a similar background are more likely to have a blind spot and less likely to notice that a clinical trial group isn’t representative of the population. Teams that are diverse and representative still must ensure an environment of psychological safety is created in order for team members from non-dominant groups to be able to speak up and be heard if they notice a bias, blindspot or mistake.

What is the solution?

There must be a conscious and deliberate decision to embed inclusion and diversity in the process that is used when designing new products. This includes medications, medical devices, and all treatment methods. By taking this approach, pharma companies can minimise the risk of default biases being reflected in the final product created.

Some ways in which this can be realised are through adding an:

These steps can help pharma and all industries create more inclusive products. Each solution is active, as passive solutions will not help create the better world we are seeking to build. To stop making avoidable mistakes that risk harming people, active steps need to be taken by each of us to embed an inclusive approach to the way we do our work each day.

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