Table 1.
Examples of potential research projects in adverse drug reactions (ADRs)
| Heading | Examples |
|---|---|
| Pharmacology/toxicology | 1.Constructing a database of published dose-response curves in ADRs (in vitro and in vivo): |
| •in order to analyse their characteristics (e.g. maximal efficacy, slope) | |
| •the use of in vitro data to predict in vivo outcomes | |
| 2.Defining the time-courses of ADRs | |
| 3.Defining susceptibility factors in patients | |
| 4.Developing and using biomarkers of adverse effects | |
| 5.Effects of overdose and methods of management [1 + 2 + 3 → DoTS classification of adverse drug reactions [1]] | |
| Regulation | How drug regulatory decisions should be made |
| •licensing decisions | |
| •withdrawing drugs after llicensing | |
| Naming medicines | |
| Marketing | How information about ADRs is disseminated |
| •Summaries of Product Characteristics (SPCs) | |
| •advertising | |
| Communication & education | Methods of communicating with health-care professionals [2] and the public: |
| •the nature of risk | |
| •perceptions of risks [3] | |
| •the actual risks and their relevance to clinical practice | |
| •the nature of the balance of benefit and harm | |
| Study design | Reporting methods Which types of design are best for eliciting particular types of ADR (e.g. cohort studies, case-control studies, n-of-1 studies, RCTs) |
| Analysis | Teleoanalysis – how best to combine information from many different types of evidence (RCTs, observational studies, case series, anecdotes) When different types of evidence are relevant Data mining techniques [4] |
| Terminology & classification | Developing classification systems [5] Dictionaries – using standard terminology [6] |
| Publication | Developing CONSORT-like statements [7] |
| Review | The use of anecdotes and spontaneous reports [8] Systematic review (including narrative review, meta-analysis, and teleoanalysis) Methods of searching for published information [9] Indexing databases |