Integration of PKPD relationships into benefit–risk analysis. (29th July 2015)

• Record Type: Journal Article
• Authors: Bellanti, Francesco; van Wijk, Rob C.; Danhof, Meindert; Della Pasqua, Oscar
• Is Part Of: British journal of clinical pharmacology. Volume 80:Number 5(2015:Nov.)
• Page Start: 979
• Page End: 991
• Publication Date: 2015-07-29
• Subjects: benefit–risk assessment -- European Medicines Agency -- multi criteria decision analysis -- not‐in‐trial simulations -- paediatric drug development -- pharmacokinetic–pharmacodynamic modelling; Pharmacology -- Periodicals; Drugs -- Periodicals; 615.1
• DOI: 10.1111/bcp.12674
• Languages: English
• ISSNs: 0306-5251

Abstract

Abstract : Aim: Despite the continuous endeavour to achieve high standards in medical care through effectiveness measures, a quantitative framework for the assessment of the benefit–risk balance of new medicines is lacking prior to regulatory approval. The aim of this short review is to summarise the approaches currently available for benefit–risk assessment. In addition, we propose the use of pharmacokinetic–pharmacodynamic (PKPD) modelling as the pharmacological basis for evidence synthesis and evaluation of novel therapeutic agents. Methods: A comprehensive literature search has been performed using MESH terms in PubMed, in which articles describing benefit–risk assessment and modelling and simulation were identified. In parallel, a critical review of multi‐criteria decision analysis (MCDA) is presented as a tool for characterising a drug's safety and efficacy profile. Results: A definition of benefits and risks has been proposed by the European Medicines Agency (EMA), in which qualitative and quantitative elements are included. However, in spite of the value of MCDA as a quantitative method, decisions about benefit–risk balance continue to rely on subjective expert opinion. By contrast, a model‐informed approach offers the opportunity for a more comprehensive evaluation of benefit–risk balance before extensive evidence is generated in clinical practice. Conclusions: Benefit–risk balance should be an integral part of the risk management plan and as such considered before marketing authorisation. Modelling and simulation can be incorporated into MCDA to support the evidence synthesis as well evidence generation taking into account the underlying correlations between favourable and unfavourable effects. In addition, it represents a valuable tool for the optimization of protocol design in effectiveness trials.