Pharmacodynamics

When drugs are used in clinical practice, the prescriber is unable to construct a careful dose–response curve for each individual patient. Therefore, most drugs are licensed for use within a recommended dose range that is expected to be close to the top of the dose–response curve for most patients. This ensures that most patients will achieve a good clinical response without the need for frequent review and dose increases. However, this means that it is sometimes possible to achieve the desired therapeutic response at doses towards the lower end of the recommended range (or below).

The adverse effects of drugs are often dose-related in a similar way to the beneficial effects. It is possible to construct a dose-response curve for these adverse effects in the same way as shown for the beneficial effects, with higher doses usually required to cause the adverse effect. The ED50 points for each curve in the Figure indicate that the ratio between the doses that have similar proportionate effects on the two outcomes is 10/0.1 = 100. This ratio is known as the ‘therapeutic index’. In reality, drugs have multiple potential adverse effects but the concept of therapeutic index is usually reserved for those requiring dose reduction or discontinuation. For most drugs, the therapeutic index is greater than 100 but there are some notable exceptions with therapeutic indices less than 10, which are in common use (e.g. digoxin, warfarin, insulin, phenytoin, opioids). Drugs with low therapeutic indices are more difficult to prescribe and hazardous for patients but they are still preferred if there are no alternative drugs with similar efficacy (e.g. anti-cancer drugs). The doses of such drugs have to be titrated carefully for individual patients to maximize benefits but avoid adverse effects. This is done by monitoring drug effects, either clinically or using regular blood tests (often known as ‘therapeutic drug monitoring’).

Figure. Dose–response curves for the beneficial and adverse effects of a drug. Prescribers will aim to prescribe doses that maximize benefits and minimize harms, which is easier for drugs where the ratio between the dose causing harm and that causing benefit (the ’therapeutic index’) is high.

Receptors are named on the basis of their major endogenous agonist (e.g. adrenergic, serotoninergic, opioid). They are then usually ‘sub-­‐typed’ on the basis of their selectivity for agonists or antagonists. Agonist selectivity is determined by the ratio of EC50 of the dose– response curve at the two different receptor subtypes. For example, β-­‐adrenoceptors can be sub-­‐typed into β1 and β2, on the basis of their responsiveness to the endogenous agonist, noradrenaline. The concentration required to cause bronchodilatation (via β2 adrenoceptors) is ten times higher than that required to cause tachycardia (via β1 adrenoceptors). Receptor sub-­‐ types can also be distinguished by the relative effectiveness of drugs that antagonize the effects of their full agonist, measured as the relative shift of the agonist dose–response curves achieved by a single dose of antagonist affecting responses mediated through the two receptors. It is important for prescribers to remember that selectivity for a receptor subtype is only a relative concept (i.e. selectivity does not equate with specificity). Agonist or antagonist drugs that are considered to be ‘selective’ for one receptor subtype can still produce significant effects at other subtypes if a high enough dose is given. This is particularly important if one receptor subtype activates the beneficial effects while another activates the adverse effects. For instance, ‘cardioselective’ β-­‐adrenoceptor blocking drugs have anti-­‐anginal effects on the heart (β1) but may cause bronchospasm in the lung (β2) and are absolutely contraindicated for asthmatic patients. Selectivity is useful in clinical practice only when the ratio of the impact of the drug at the two receptor sites is 100 or more. When selectivity is lower, it is difficult to predict drug doses that will exploit the difference in subtype activity.

When the relation between drug dose (X-axis) and drug response (Y-axis) is plotted on a base 10 logarithmic scale, this produces a sigmoidal dose–response curve (Fig A). This representation is more useful than a linear plot because it expands the dose scale in the region where drug response is changing rapidly and compresses the scale at higher doses where large changes have little effect on response. Clinical responses that might be plotted in this way include change in heart rate, blood pressure, gastric pH or blood glucose, as well as more subtle phenomena such as enzyme activity, accumulation of an intracellular second messenger, membrane potential, secretion of a hormone, or contraction of a muscle.

Progressive increases in drug dose produce increasing drug effects, but these occur over a relatively narrow part of the overall concentration range; further increases in drug dose (or concentration) beyond this range produce little extra effect. The clinical implication of this relationship is that simply increasing drug dose may not result in any further beneficial effects for patients and may cause adverse effects. The maximum response on the curve is referred to as the Emax and the dose (or concentration) producing half this value (Emax/2) is the ED50 (or EC50). The effective dose range can be considered as spanning the straight-line segment of the log dose–response curve (corresponding to 20–80% of Emax). The maximum tolerated dose is the highest dose of a drug that can be administered without the development of dose-related adverse effects.

The addition of a competitive antagonist to an agonist will lead to a shift in the agonist dose–response curve to the right because higher agonist concentrations are now required to achieve a given percentage receptor occupancy (and therefore effect) (Fig B). Dose–response curves of the agonist constructed in the presence of increasing doses of a competitive antagonist are progressively shifted to the right. Nevertheless, the effect of a reversible competitive antagonist can always be overcome by giving the agonist at a sufficiently high concentration (i.e. it is surmountable). Many clinically useful drugs are competitive antagonists (e.g. atenolol, naloxone, atropine, cimetidine). Non-competitive antagonists inhibit the effect of an agonist in ways other than direct competition for receptor binding with the agonist (e.g. by affecting the secondary messenger system). This makes it impossible to achieve maximum response even at very high agonist concentration. At a given concentration, non-competitive antagonists not only shift the agonist dose–response curve to the right but also decrease the Emax (Fig C). Irreversible antagonists can be considered as a particular form of non-competitive antagonist characterized by antagonism that persists, even after the antagonist has been removed. Common examples are aspirin and omeprazole. This form of antagonism disappears only when new proteins or enzyme are synthesized. This explains why aspirin is effective, even when taken intermittently, as prophylaxis against cardiovascular events.

The dose-response relationship to the same drug varies between individuals because of various factors, such as differences in receptor number and structure, receptor-coupling mechanisms and physiological changes resulting from differences in genetics, age and health. For example, the effect of the loop diuretic, furosemide, is often significantly reduced at a given dose in patients with renal impairment. A further source of variability is that the same dose of drug does not achieve the same tissue drug concentrations in all individuals because of differences in handling (e.g. metabolism, excretion). In reality, it is this pharmacokinetic variation that explains most of inter-individual variation in drug response seen in clinical practice.

Figure. Dose–response curves. A. Basic features. B. The effect of co-administering an agonist with a competitive antagonist. C. The effect of administering an agonist with a non-competitive antagonist. (Note that, in reality, it is ligand concentration (and resulting receptor occupation) that affects response. When discussing 'the dose– response curve' it is often assumed that the drug dose and ligand concentration are closely linked. This is likely to be the case during an in vitro pharmacological experiment but the relation between an ingested drug dose and relevant tissue concentration in a human can be more complex.)

Affinity of ligands is a function of both the rate of association and the rate of dissociation of the ligand–receptor complex; the former depends on the 'goodness of fit' at a molecular level, whereas the latter depends on how tightly the ligand is bound (the strength of the chemical bond). Systems requiring rapid fine modulation (e.g. nerve synapses) must have agonists with a low receptor affinity because those with high receptor affinity would produce unnecessarily prolonged responses. During stimulation, agonist concentration near the receptor must be relatively high, but the agonist is then cleared rapidly by active transport. In contrast, growth factors are typically peptides with very high affinity for their receptors, and achieve their effects at concentrations that are difficult to detect in vivo. Some drug–receptor interactions are so strong that they are effectively irreversible. A good example is aspirin, which irreversibly inhibits its target, the enzyme cyclooxygenase.