The formalin test for nociception, which is predominantly used with rats and mice, involves moderate, continuous pain generated by injured tissue. In this way it differs from most traditional tests of nociception which rely upon brief stimuli of threshold intensity. In this article we describe the main features of the formalin test, including the characteristics of the stimulus and how changes in nociceptive behaviour may be measured and interpreted. The response to formalin shows an early and a late phase. The early phase seems to be caused predominantly by C-fibre activation due to the peripheral stimulus, while the late phase appears to be dependent on the combination of an inflammatory reaction in the peripheral tissue and functional changes in the dorsal horn of the spinal cord. These functional changes seem to be initiated by the C-fibre barrage during the early phase. In mice, the behavioural response in the late phase depends on the ambient temperature. We argue that the peripheral tissue temperature as well as other factors influencing the peripheral inflammation may affect the response, possibly confounding the results obtained with the test. Furthermore, we discuss the methods of recording the response and the value of observing more than one aspect of behaviour. Scoring of several behavioural variables provides a means of assessing motor or sensorimotor function as possible causes for changes in behaviour. In conclusion, the formalin test is a valuable addition to the battery of methods available to study nociception.

Rodent models of chronic pain may elucidate pathophysiological mechanisms and identify potential drug targets, but whether they predict clinical efficacy of novel compounds is controversial. Several potential analgesics have failed in clinical trials, in spite of strong animal modelling support for efficacy, but there are also examples of successful modelling. Significant differences in how methods are implemented and results are reported means that a literature-based comparison between preclinical data and clinical trials will not reveal whether a particular model is generally predictive. Limited reports on negative outcomes prevents reliable estimate of specificity of any model. Animal models tend to be validated with standard analgesics and may be biased towards tractable pain mechanisms. But preclinical publications rarely contain drug exposure data, and drugs are usually given in high doses and as a single administration, which may lead to drug distribution and exposure deviating significantly from clinical conditions. The greatest challenge for predictive modelling is, however, the heterogeneity of the target patient populations, in terms of both symptoms and pharmacology, probably reflecting differences in pathophysiology. In well-controlled clinical trials, a majority of patients shows less than 50% reduction in pain. A model that responds well to current analgesics should therefore predict efficacy only in a subset of patients within a diagnostic group. It follows that successful translation requires several models for each indication, reflecting critical pathophysiological processes, combined with data linking exposure levels with effect on target.

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