Simulation in medical research

I have come across an interesting article by Mancini et al. (2012), of the University of Amsterdam, in which the authors use simulations instead of clinical trials in order to estimate the effects of (non-)usage of a specific drug.

The use of statistics in medicine is one of my main areas of interest, and something I will try to cover quite a lot on this blog.

Generally, to examine whether a drug or treatment has an effect, medical researchers perform clinical trials in which patients with similar characteristics are split into groups. One group will receive the treatment and one group will not (this last group is often again divided in two, one part which gets a placebo-treatment, and one part which gets no, or traditional, treatment). If statistically significant differences in outcome between the sub-groups are found, the drug or treatment is said to have an effect, and will be launched to the market or studied further.

As can be understood, such an approach takes a lot of time and resources, and there are also ethical difficulties with giving some patients one treatment and other patients another. This is why it is so interesting to find a simulation study used in medicine (this might be commonly applied, but I have not seen it before now). As the authors of the study write:

“Performing this test in silico [simulations, Hedg.] allows us to use the same
virtual patients for each group, whereas in clinical trials the control
groups consist of different individuals. Such choice enables us to
directly relate the survival of rates of each group to the effect of the
different therapies.”

Using this approach, the authors simulate the effect of differences in drug dosage on HIV-patients, something which would be both dangerous and unethical to do on real patients. Their simulations show that if a treatment with pauses in the use of drugs, will be conducted, the optimal plan of dosage is two weeks with drugs and one week without.

Using mathematical and statistical tools (of which simulations is only one example) to describe and model biological processes is increasingly popular, but can at the same time be very challenging, all the time both body and nature are dynamic systems. However, this is also perhaps the area where these methods have the most to offer in terms of human benefits, and I am hoping that it will be possible to conduct even more such simulation studies in the future.



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