Pharmacovigilance and Drug Safety

There are two broad types of post-authorisation or ‘Phase IV’ study: clinical trials and pharmacoepidemiological studies. In general, clinical trials involve interventions in the management of the patients’ disease and pharmacoepidemiology studies are non-interventional. ‘Interventional’ means that there is some systematic allocation of patients to specific treatment which may not be what they would have received normally, or there might be investigations or procedures carried out that, again, are not part of routine practice. ‘Non-interventional’ studies involve the patient receiving a medicine as routine treatment, in accordance with the SPC and without any special investigations: in other words, the study is completely observational.

The company marketing a product may set up post-authorisation clinical trials for purposes of obtaining information on use in particular patient populations (e.g. the elderly, or liver-impaired) or for obtaining other data on the way that the product is used.

Post-authorisation studies that are set up specifically to evaluate product safety are referred to in as “post-authorisation safety studies” or PASS. These studies are described in the risk management plan at the time of application for marketing authorisation and become post-marketing commitments for the company. They may also be required to be set up, if regulatory authorities consider that there is a need for additional safety information after marketing.

Signal detection based on spontaneous reporting involves looking for any new patterns or seemingly significant new findings in the safety database. It may be one or more reports showing particularly strong evidence of a previously unknown adverse reaction for that drug, or involving adverse events that are usually caused by drugs, such as aplastic anaemia or toxic epidermal necrolysis. More often, it is a matter of looking for patterns or clusters of reports that stand out from the background. These clusters may be identified by looking at data tables, or – for large databases, such as those held by regulatory authorities or by a company with product with many cases reported – using computerised methods involving statistical disproportion. Examples include the Proportional Reporting Ratio, Bayesian Combination Propagation Neural Network used by the WHO Uppsala Monitoring Centre and the Modified Gamma Poisson Shrinker method used by FDA and MHRA.

Having identified potential tentative signals it is necessary to evaluate them and to consider whether they are real or not. Often, an apparent signal can result just from the disease that the drug is treating – so if a drug is used in patients for the treatment of high blood pressure, it would not be surprising to find reports of high blood pressure itself, and also kidney disease, stroke and heart failure, because these are either contributory or complications of high blood pressure. This is often a difficult process: evaluating signals involves looking at the individual case reports and assessing the strength of causation of the drug in each case. Other sources of safety data are usually also checked at this time – for example, the data from clinical trials and toxicology studies.

It may then be appropriate and necessary to set up a study specifically investigating a particular signal or safety concern. Other possible actions could be to institute a review of the benefits and risks of the product; to suspend or revoke the marketing authorisation; to propose a change to the product information (SPC, labelling); to issue a warning to health professionals in the form of a Dear Health Professional communication; or perhaps just to keep the issue under review. At some point, it may become apparent that the signal was not real, and the issue can be shelved.