A diversity of backgrounds, views, experience and perspectives sets the stage for creativity and innovation - and ultimately, it is the mix of people and exchange of ideas that will help us address the challenges of the future.
When considering diversity, we want to reach beyond the protected characteristics to include wider definitions of identity where barriers to inclusion may exist. For example, socioeconomic status, personal needs for mental wellbeing, neurodiversity and learning needs, gender identity and paternal status. We look at diversity through a model of the three types of diversity (demographic, experiential and cognitive) that, when combined, describe our identity.
We apply this definition to diversity in the workforce, and to research and development. For more on what we currently know about both dimensions of this issue, read below.
What do we currently know about the diversity of the pharmacology community?
Our ambition is that no one should face barriers when it comes to their career or their ability to benefit from pharmacology research. However, we know we are not there yet.
One way of looking at the problem is in terms of representation, that is, what the diversity of the group in question is. Another important aspect is their experience, that is, what is the environment like for individuals from a range of identities and backgrounds and where and how might this fall short. Part of the problem is that we do not have good data on either.
However, there is no denying that there is a widespread problem in the life sciences of which pharmacology is a part. This is clearly because the scientific community exists in a wider social setting, where the challenges remain extensive – as illustrated by global protests such as #BlackLivesMatter and #MeToo. Social inequalities and injustices have deep historical roots. It is imperative that we see these challenges in their fullest extent, but that we focus on making change in our area of influence. We hope that our membership of EDIS Group (Equality, Diversity & Inclusion in Science and Health) and wider networks will help us work with partner organisations to achieve more than we could alone. It is important to learn and act together, especially when trying to understand a complex data picture.
When it comes to drilling down into the data for pharmacology, there are limitations on what we can currently understand. This is in part because not all pharmacologists are members of the Society, in part because our data collection and reporting needs improving, in part because pharmacologists work across a range of sectors so it is hard to collate and track them, and in part because the data collected by the Higher Education Statistics Agency (HESA) combines pharmacology and pharmacy data in its reporting. It is critical that we address issues with our own data collecting and reporting, but also that we consider how to monitor the diversity of the discipline as a whole. Given the extent of the challenge in collecting rigorous data for pharmacology alone, we need to consider whether we may be wiser to approach the issues of representation and experience of defined groups in partnership with other organisations. This will be part of our ongoing work.
In terms of ‘who is doing the research’, we do know that only 37% of our members identify as women, that they are under-represented on our committees (see figure 1) and in senior membership categories (see figure 2), although the former is improving because of targets set by the Society.
We also know that:
- 70% of members have provided data on their gender, 0.3% choose not to disclose their gender and 30% of member records hold no response. As a higher proportion of members provide data on gender than on any other aspect of diversity, this means that almost one in three members have not provided any diversity data at all.
- Just one third of members provide data on ethnicity (33%).
- Just one in five members (20%) provides information on their religion or sexual orientation.
- An increasing number of pharmacology undergraduates are students in the highest socioeconomic bracket, which grew from 22% in 2007 to 27% in 2014. The Society collected this data as part of an examination of the health of pharmacology degrees in 2015/6, and it would be helpful to revisit this.
Our data on experience is even more limited. We want to take the opportunity to ask more questions about the experience of individuals, so we actively listen to the issues people face. We also want to understand ‘what works’ in terms of contributing to a positive experience.
Figure 1. Membership of committees by gender, 2016 v 2019, extracted from the data used to inform the external review
Figure 2. Proportion of women by membership category, extracted from data used to inform the external review
What do we currently know about who is benefiting from pharmacology research?
Everyone should have the opportunity to benefit from the outcomes of research. To ensure its benefits can be shared equally, all aspects of research must be inclusive by design – and must represent the patient groups that are affected by diseases[1]. This is a multi-dimensional issue; the purpose of this section is not to be exhaustive but to outline how it is relevant to the global pharmacology community. Some of the issues include:
1. The scientific and clinical picture is biased towards males
Sex is an experimental variable, and if it is not actively built into research as a study design variable, the scientific and clinical picture will continue to be biased towards males[1]. Masking sex differences in research can lead to problems with translation or reproducibility. Further, a bias towards studying male physiology and the male drug response may also be harmful if this leads to inappropriate treatment recommendations for female bodies[2]. To be clear, “sex” is defined by the genetic status of the subject, whereas “gender” refers to the social and cultural context.
To address this, the British Journal of Pharmacology has set expectations that sex should be considered an experimental variable in all studies submitted for publication[3]; and has recently published a special themed issue[4] drawing relevant studies together. For biological research, sex is the important experimental variable. However, some forms of health research may need to account for gender; the Gendered Innovations Project[5], aims to support researchers and funders to integrate sex and gender analysis into research.
2. Genetic data is predominately from people with European ancestry
Genetic and genomic information has increasing centrality in pharmacology research and clinical practice, including personalised medicine and pharmacogenomics. However, the genomic information available to researchers is known to predominately include those from European ancestry, and whilst this is improving, the information gap is not closing fast enough[6].
Patients who do not descend from these populations are less likely to glean useful insights into their condition or treatment because the information on genomic variants relevant to them has not been collected and studied[7][8]. The Clinical Genetics Ancestry and Diversity Working Group discusses these issues in light of the “scientifically and culturally complex issues of self-reported race, ethnicity, geographic and genomic ancestry”[9]. Priorities for research include standardisation of data collection relating to race, ethnicity and ancestry, a common understanding of use in clinical research and efforts to widen the diversity of participants in genomic research. It is important to close the information gap, so that people from all ancestries can fully benefit from research.
3. The demographics of patients involved in clinical trials does not represent the real-world burden of disease
Historically, a disproportionate number of participants in clinical trials have a predominantly European ancestry and are male[11]. However, as reported through a growing number of studies, the way in which a particular drug responds to and impacts a person can vary based on the individual’s sex, race and ethnicity[12][13][14][15]. Therefore, the needs of many patients are not being fully accounted for by research.
The COVID-19 pandemic has brought the lack of diversity in clinical trials into an even starker reality. A recent study in The Lancet, highlighted that even when taking age into account (the largest disparity factor found), Black males were 4.2 times more likely to die from COVID-19 than white males[16]. A systematic review from June 2020 reported that of 1,518 COVID-19 studies registered only six were collecting data on ethnicity[17]. An earlier study demonstrated clinically relevant differences in responses to heart failure treatments depending on whether the patients were white or Black[18]. Another example is a study investigating systemic lupus erythematosus (SLE), which ethnic minorities are more likely to develop than their white counterparts, despite this, they are not widely represented in SLE clinical trials[19]. Clark et al[20] also argue for consideration of potential for different reactions to drugs (e.g. due to sex or ethnicity) in trial design.
It is important that diversity in clinical trials is improved because it translates to greater understanding of disease, and the benefits or limitations of treatments for specific populations. The needs of patients with the disease in question should also be considered in the early stages of trial design.
Several funders of clinical trials are making headway in terms of ensuring applicants for funding consider diversity in their trial design. Wellcome, for example, expect the demographic of trial participants to represent the population needing the healthcare intervention. They also advise that recruiting more people from under-served groups than is statistically necessary can improve the relevance of findings to these groups. This is in addition to their standard requirement that trials should be conducted in accordance with good practice guidelines[21].
To explore the disparity and lack of diversity in research on a wide-scale, BenevolentAI has developed the ‘Diversity Analysis Tool’[22]. This program is aiming for a more inclusive patient demographic represented in precision medicine. This technology could be deployed for use in clinical trial design e.g. when selecting cohorts.
In terms of the role of regulatory bodies, the Food and Drug Administration in the US has specific guidance[23] in relation to the collecting and reporting of race and ethnicity data so that it is representative of the real-world burden of disease. The UK has no equivalent regulatory policy, and this is something that must be tackled.
4. Clinical trials generally exclude people with multiple long-term conditions
The Academy of Medical Sciences (AMS) recently highlighted[24] that: “a growing number of people suffer from more than one serious long-term medical condition such as diabetes, arthritis or Alzheimer’s disease - a condition known as multimorbidity.” Multiple long-term conditions are particularly prevalent in older people – and an ageing population means that this is a growing challenge. This means that as the number of conditions increases, so does the number of medicines prescribed: the number of patients on multiple medications (polypharmacy) is also growing. Patients can find managing multimorbidity as a full-time job, faced with a research and care system that does not see the patient holistically as a full person. Whole person-centred research and care would be the gold-standard.
However, the traditional research paradigm focuses on one target, one disease and one treatment – often overseen by multiple specialists in secondary care pathways. This is a challenge that pharmacology and clinical pharmacology is well-placed to help address.
Whole-person centred research would use methodology that is inclusive, appropriately focused and powered. Whole-person care would invest in multi-professional teams, including medicines specialists such as clinical pharmacologists who can provide support for complex polypharmacy. There also needs to be a shift in the drug development paradigm to address multimorbidity – to ensure the medicines that are developed have the best chance of working safely in the patients who need them. The challenge is to define the population that the drug is being developed for, and then to ensure that study design yields results that can be meaningfully translated to these patients.
As the AMS report notes, this is a significant challenge because:
- Most studies are single issue
- Single issue studies often exclude patients with multiple long-term conditions
- Few trials have looked at treatment strategies in such patients
- There is little data from known disease clusters
- More research is needed on healthy ageing and preventing multimorbidity
Patients with multiple long-term conditions are often excluded from research because of concerns about masking treatment effects, and because of safety concerns. Strategies to improve inclusion, whilst maintaining scientific rigour and patient care are urgently needed if research and the development of medicines is to be relevant to all those who require it.
