Understanding clinical efficacy of drugs (2) - variability in a population

This is a another way of looking at the same plot that was shown in the previous post. A plot representing the chance of a beneficial effect (blue) and a similar plot representing the chance of a detrimental effect (red). The difference here, is that the plots are now a sample of a simulated population with a variation in sensitivity to the drug effect. Likewise, the toxicity profile. In this plot, the therapeutic range is defined as being between an empirical 'average' threshold for the beneficial effect (on the left), and the unacceptable 'average' level of toxicity (on the right). The understanding here, is that potentially you can continue to increase the dose from the left boundary of the therapeutic range, if a stronger drug response is needed. The downside to this is that there will be an increased risk of toxicity. The right boundary to the therapeutic range basically limits the dose increase as any further increase in toxicity risk becomes unacceptable.

As in the previous post, the clinical efficacy plots can be generated from the simulated population. It is shown here with the therapeutic range superimposed. As can be seen, there is an optimal zone where clinical efficacy is maximum. Here is concentration where you can expect maximum benefits with minimum risk of toxicity.

But it should be recognized that this only an expectation of the 'average' response within a population. What should be specifically noted here is the variability and wide scatter of response types within the population sample. For any specific patient within this simulated population, the clinical efficacy is unique, and may look totally unlike the population 'average'

The question is, how do you recognize and deal with this response variability?

The issue of clarithromycin and increased cardiac deaths #5 - How can we deal with the variability?

Clinical efficacy is never only about therapeutic efficacy. It is always a balance between benefits and risks. Drug response variability shapes the clinical efficacy curve by altering the relative distance between benefits and risks along the dose or concentration range. Good therapeutics therefore is always about being able to manage the variability in drug response, so that the optimal dose or concentration for the patient can be selected that will maximize benefits and minimize risk.

If we just consider the anti-microbial effects.... we actually manage the variability rather badly. Theoretically, there is a therapeutic target that is based on maintaining drug concentrations at the target site (where the bugs are actually growing) above the minimum inhibitory concentrations (MIC). By drug concentrations we refer mainly to the trough concentrations. Therapeutically, the assumption is that if we dose according to published guidelines, we will achieve target concentrations at the site of action. In reality, we do not know that for certain. In fact, we have absolutely no idea whether we are dosing too much or too little, and basically act on faith that a certain dose (quantum and frequency) will allow trough concentrations at the site of action to exceed the MIC.

Therapeutic drug monitoring of clarithromycin had been proposed, but has never ever been taken up seriously for it to be included in routine patient management.

This is fine, if there were no serious toxicities, because you can administer more drug than really necessary just to make sure you have adequate concentrations at the target site. However, clarithromycin use does carry a serious risk of toxicity....namely sudden death. Therefore the correct dosing schedule is important to deliver only adequate levels of clarithromycin so that the troughs are over the MIC and the peaks do not approach the IC10 of IC20 of HERG channel blockade.

Currently we have no means to doing this.

On the flip side of the coin, there is the problem of cardiac toxicity. Although there is a considerable gap between routinely achieved levels of clarithromycin and the IC10 or IC20 of HERG channel blockade, obviously this gap can sometimes, though rarely, be crossed. The Danish study suggests this might be happening at least in 37 out of 1 million dosing regiments. How do we monitor and manage this? Routine ECG to look for QT prolongation would certainly be helpful. But this is almost never done during clarithromycin use.

Effectively therefore we have no means to manage variability where clarithromycin use is concerned. There is an over-dependence on published dosage guidelines, and faith in the adequacy and safety of these guidelines. Am I surprised by the association with cardiac deaths? Definitely not. Understanding the pharmacology of clarithromycin, this risk is predictable. The risk is not high. But one sudden death occurring in a relatively healthy individual, no matter how infrequent, is one death too many.

Can we do better? Yes.

Stress - Nature vs Nurture: Lessons for drug response variability

This has been abstracted from Darlene Francis and Daniela Kaufer's essay in Reading Frames: The Scientist October 2011

Recent advances in neuroscience make a compelling case for finally abandoning the nature vs. nurture debate to focus on understanding the mechanisms through which genes and environments are perpetually entwined throughout an individual’s lifetime. As neurobiologists who study stress, we believe that research in this area will help reframe the study of human nature.

Researchers have historically approached the study of stress from two perspectives: 1) a physiological account of the stress response, which consists of tracking the stress hormone cortisol and its effects on metabolism, immune function, and neural processes; and 2) a psychological/cognitive focus on how the perception and experience of a stressor influences the stress response. These approaches align with the nature vs. nurture debate, pitting nature, represented by the biology of cortisol responses, against nurture, in the form of external experience influencing cognitive processing. Academic researchers typically study stress by adopting one of these perspectives. However, anyone who’s been stuck in rush hour traffic or faced a looming deadline knows that the causes and consequences of stressful experiences do not adhere to these academic divides.

Scientists and laymen alike still spend too much time and effort trying to quantify the relative importance of nature and nurture.
In the past decade, researchers have made great strides in understanding the cellular, molecular, genetic, and epigenetic processes involved in the regulation of the stress response. Surprisingly, as stress research elucidated this molecular dimension, it shed light on the powerful role of environment and experience in remodeling our molecular makeup. It became clear that the environmental effects (nurture) are modulated by genetic polymorphism and epigenetic programming of gene expression (nature) to shape development. So, as the molecular underpinnings are elucidated, the need to study the interaction between environment and our genome is highlighted, and the divide seems less relevant.