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
  2. Genetic data is predominately from people with European ancestry
  3. The demographics of patients involved in clinical trials does not represent the real-world burden of disease
  4. Clinical trials generally exclude people with multiple long-term conditions

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.

In their recent paper, Bentley et al (2020) consider the impact of efforts to improve inclusion of African ancestry in genomics, noting welcome advances alongside ongoing challenges:[10]

“…ancestry is defined using genetic variants based on the distribution of those variants in worldwide populations. An individual’s genome is a mosaic of segments from different ancestral populations. By comparing segments of DNA with the distribution of genetic variants in worldwide populations, it is possible to determine the likely “parental” or source population for each segment of DNA, indicating a component of the individual’s overall ancestry. Using this process to interrogate an individual’s entire genome, the proportion of an individual’s genomic inheritance from specific ancestral populations can be estimated. Importantly, someone’s genetic ancestry may have little to do with their identity in terms of race or culture. An individual with a relatively small proportion of African ancestry may not self-identify as “Black” or “African American”, yet they may have African ancestry at a specific region of the genome where that ancestry may confer risk, for instance, by carrying a pharmacogenomic risk allele that is more prevalent among those with African ancestry.”


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.


How can you get involved?

We want to make change. As part of this, and our work going forwards, we have opened a call for submissions to hear about what you are already doing in this area, and to explore how we may be able to work together. Please send a short summary of your work on equality, diversity and inclusion to Sophia McCully (Policy Officer) as soon as possible, indicating whether you would be interested in discussing this at our annual meeting .

If you feel that there is anything else we should be thinking about or focusing on, please also get in touch.

To discuss this work, please contact Anna Zecharia via email or through the BPS Community.


Further reading


[1] The Independent Medicines and Medical Safety Review (2020) First Do No Harm: The report of the Independent Medicines and Medical Devices Safety Review. (last accessed 21 July 2020).
[2] Zakiniaeiz Y, Cosgrove KP, Potenza MN, Mazure CM. Balance of the Sexes: Addressing Sex Differences in Preclinical Research. Yale J Biol Med. 2016;89(2):255-259. Published 2016 Jun 27.
[3] Franconi F. et al (2007) Gender differences in drug response. Pharmacology Research 55 (2):81-95.
[4] Docherty, J.R., Stanford, S.C., Panattieri, R.A., Alexander, S.P., Cirino, G., George, C.H., Hoyer, D., Izzo, A.A., Ji, Y., Lilley, E., Sobey, C.G., Stanley, P., Stefanska, B., Stephens, G., Teixeira, M. and Ahluwalia, A. (2019), Sex: A change in our guidelines to authors to ensure that this is no longer an ignored experimental variable. Br J Pharmacol, 176: 4081-4086.
[5] British Journal of Pharmacology (2020) Special issue: Sex as an experimental variable.
[6] Gendered Innovations in science, health & medicine, engineering, and environment. (last accessed 4 August, 2020).
[7] Landry, L. G., Ali, N., Williams, D. R., Rehm, H. L. & Bonham, V. L. Lack of diversity in genomic databases is a barrier to translating precision medicine research into practice. Health Aff. 37, 780–785 (2018). https://www.healthaffairs.org/doi/10.1377/hlthaff.2017.1595
[8] Landry LG, Rehm HL. Association of Racial/Ethnic Categories With the Ability of Genetic Tests to Detect a Cause of Cardiomyopathy. JAMA Cardiol. 2018;3(4):341–345. doi:10.1001/jamacardio.2017.5333https://jamanetwork.com/journals/jamacardiology/fullarticle/2673286
[9] Hindorff, L., Bonham, V., Brody, L. et al. Prioritizing diversity in human genomics research. Nat Rev Genet 19, 175–185 (2018). https://www.nature.com/articles/nrg.2017.89
[10] Popejoy, A., Ritter, D., Crooks, K., Currey, E., Fullerton, S., Hindorff, L., Koenig, B., Ramos, E., Sorokin, E., Wand, H., Wright, M., Zou, J., Gignoux, C., Bonham, V., Plon, S. and Bustamante, C., 2018. The clinical imperative for inclusivity: Race, ethnicity, and ancestry (REA) in genomics. Human Mutation, 39(11), pp.1713-1720. https://onlinelibrary.wiley.com/doi/epdf/10.1002/humu.23644
[11] Bentley, A.R., Callier, S.L. & Rotimi, C.N. Evaluating the promise of inclusion of African ancestry populations in genomics. npj Genom. Med. 5, 5 (2020).
[12] Financial Times (2019) How to stop a lack of diversity undermining clinical trial data. (Accessed 21 October, 2020).
[13] Franconi F, Campesi I, Colombo D, Antonini P. Sex-Gender Variable: Methodological Recommendations for Increasing Scientific Value of Clinical Studies. Cells. 2019;8(5):476. Published 2019 May 17. doi:10.3390/cells8050476
[14] Docherty, J., Stanford, S., Panattieri, R., Alexander, S., Cirino, G., George, C., Hoyer, D., Izzo, A., Ji, Y., Lilley, E., Sobey, C., Stanley, P., Stefanska, B., Stephens, G., Teixeira, M. and Ahluwalia, A., 2019. Sex: A change in our guidelines to authors to ensure that this is no longer an ignored experimental variable. British Journal of Pharmacology, 176(21), pp.4081-4086.
[15] Ramamoorthy, A., Pacanowski, M., Bull, J. and Zhang, L., 2015. Racial/ethnic differences in drug disposition and response: Review of recently approved drugs. Clinical Pharmacology & Therapeutics, 97(3), pp.263-273.
[16] Shah, R. and Gaedigk, A., 2017. Precision medicine: does ethnicity information complement genotype-based prescribing decisions?. Therapeutic Advances in Drug Safety, 9(1), pp.45-62.
[17] Treweek, S., Forouhi, N., Narayan, K. and Khunti, K., 2020. COVID-19 and ethnicity: who will research results apply to?. The Lancet, 395(10242), pp.1955-1957.
  Treweek, S., Forouhi, N., Narayan, K. and Khunti, K., 2020. COVID-19 and ethnicity: who will research results apply to?. The Lancet, 395(10242), pp.1955-1957.
[18] Carson, P., Ziesche, S., Johnson, G. and Cohn, J., 1999. Racial differences in response to therapy for heart failure: Analysis of the vasodilator-heart failure trials. Journal of Cardiac Failure, 5(3), pp.178-187.
[19] Williams, J., Dall’Era, M., Lim, S., Feldman, C., Arntsen, K., Blazer, A., Goode, T., Merrill, J., Sheikh, S., Stevens, A., Lipsky, P. and Costenbader, K., 2020. Increasing Ancestral Diversity in Systemic Lupus Erythematosus Clinical Studies. Arthritis Care & Research,.
[20] Clark, L., Watkins, L., PiƱa, I., Elmer, M., Akinboboye, O., Gorham, M., Jamerson, B., McCullough, C., Pierre, C., Polis, A., Puckrein, G. and Regnante, J., 2019. Increasing Diversity in Clinical Trials: Overcoming Critical Barriers. Current Problems in Cardiology, 44(5), pp.148-172.
[21] Wellcome (2020) Clinical trials policy. (Accessed 21 October, 2020).
[22] BenevolentAI (2020) The Diversity Analysis Tool: Towards Better Diversity in Data for Precision Medicine. (Accessed 21 October, 2020).
[23] Enhancing the Diversity of Clinical Trial Populations – Eligibility Criteria, Enrolment Practices, and Trial Design Guidance for Industry. FDA-2019-D-1264.  (Accessed 21 October, 2020).
[24] Academy of Medical Sciences (2018) Multimorbidity: a priority for global health research. (Accessed 20 October, 2020)