Gender Imbalance in Science

There is a gender imbalance in science. This is most obvious when looking at math, physics or engineering programs. It's easy to look around biomedical labs, see the number of women, and assume this isn't a problem for the biological sciences. And indeed, in the biological sciences, women make up 62% of bachelor's recipients and 56% of graduate students¹. Beyond that, the numbers drop off for a number of reasons. Again, in the biological sciences, only 41% of postdoctoral fellows, 33% of tenure-track and 22% of tenured scientists are women. (Nevermind the fact that their salaries also tend to be lower)

Those numbers are pretty shameful. Some might argue that it doesn't matter, as long as the science being done is good (though I'm really not sure who they might be). The problem is, it isn't. Even the research being done is gender biased, as highlighted by a series of recent editorials in Nature. The first points out that there's a gender bias in clinical trials: except for a few key areas (eg. breast, cervical or ovarian cancers) women are underrepresented

Generally, women remain underrepresented in biomedical research. Studies published in 2000 and in 2008 concluded that women were still not included in mixed-sex cardiovascular trials in numbers that reflect the disease prevalence among the general population. A survey of studies published in 2004 in nine influential medical journals found that only 37% of participants were women (24% when restricted to drug trials), and only 13% of studies analysed data by sex.

It's no secret that women and men have different physiologies, and can be differently affected by diseases and their treatments. So why should sex differences not be considered when designing a clinical trial? You can't treat differently if you don't know the differences, and even where gender is known to affect outcomes, there's still no difference in treatment

A 2005 study of 300 new drug applications between 1995 and 2000 found that even those drugs that showed substantial differences in how they were absorbed, metabolized and excreted by men and women had no sex-specific dosage recommendations on their labels. This may be part of the reason why women are 1.5 times more likely to develop an adverse reaction to prescription drugs than men.

And if you're a pregnant woman, it gets even worse. You're forced to either forego treatment or potentially settle for drugs of unknown effectiveness or safety (for you or the fetus), since pregnant women are usually excluded from trials and new drugs are often not approved for them. This despite the obvious fact, that the second article points out, that "pregnant women get sick, and sick women get pregnant." Obviously diving right into clinical trials with pregnant women is a bit risky, in no small part for the fetus (though a controlled clinical trial is probably still safer than rolling the dice with off-label use), but there are ways this can be approached.

There is an obvious alternative: small, well-designed trials for pregnant women, starting with phase I safety trials that would begin at the same time as phase III efficacy trials in the general population. With this staggered approach, pregnant women and fetuses would not be exposed to any compounds that failed in phase I and II trials.

This strategy is simple, and makes sense: it allows pregnant women the same standard of evidence-based care afforded to everybody else (even better, if you consider the lack of sex consideration described above), accounting for their own particular changes while mitigating risk.

Most surprising, to me at least, is the fact that gender bias even extends to animal models. In some ways, it makes sense to keep models simple and avoid potential complications from hormone cycles. Depsite the fact that male mice tend to fight when caged together and single housing takes both space and money, a survey of 2000 studies done in 2009 found a male bias in animals used.

We found a male bias in 8 out of 10 biological disciplines, most pronounced in neuroscience (5.5 males to 1 female), pharmacology (5 males to 1 female) and physiology (3.7 males to 1 female).

Though this might be more convenient or have a practical rationale, it doesn't necessarily result in the best model. So we have biased models feeding into imbalanced clinical trials, with women getting the short end at each step. And the end result:

However justifiable these imbalances may be on a case-by-case basis, their cumulative effect is pernicious: medicine as it is currently applied to women is less evidence-based than that being applied to men.

Which is just sad.

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¹All numbers based on US statistics from the NSF, 2006.