A forecasting approach to accelerate drug development

Pharmacokinetic/pharmacodynamic studies in drug product development

In the quest of ways for rationalizing and accelerating drug product development, integrated pharmacokinetic/pharmacodynamic (PK/PD) concepts provide a highly promising tool. PK/PD modeling concepts can be applied in all stages of preclinical and clinical drug development, and their benefits are multifold. At the preclinical stage, potential applications might comprise the evaluation of in vivo potency and intrinsic activity, the identification of bio-/surrogate markers, as well as dosage form and regimen selection and optimization. At the clinical stage, analytical PK/PD applications include characterization of the dose-concentration-effect/toxicity relationship, evaluation of food, age and gender effects, drug/drug and drug/disease interactions, tolerance development, and inter- and intraindividual variability in response. Predictive PK/PD applications can also involve extrapolation from preclinical data, simulation of drug responses, as well as clinical trial forecasting. Rigorous implementation of the PK/PD concepts in drug product development provides a rationale, scientifically based framework for efficient decision making regarding the selection of potential drug candidates, for maximum information gain from the performed experiments and studies, and for conducting fewer, more focused clinical trials with improved efficiency and cost effectiveness. Thus, PK/PD concepts are believed to play a pivotal role in streamlining the drug development process of the future.

Computer-assisted drug development (CADD): an emerging technology for designing first-time-in-man and proof-of-concept studies from preclinical experiments

Computer-assisted drug development (CADD) is an emerging technology for accelerating drug development based on the integration of mathematical modelling and simulation. This methodology provides a knowledge-based decisional tool on alternative development strategies based on the evaluation of potential risks on drug safety, and the definition of experimental design of new trials with expected power and probability of success. An example of CADD implementation is presented to design the first-time-in-man (FTIM) and the proof-of-concept (PoC) study of a new CNS compound. The final objective of the example presented is not necessarily to supply a success story of a correct prediction of human data from animal studies but to define a credible strategy suitable to design FTIM and PoC studies using preclinical data without the support of any human in vivo information. Rhesus monkey and human PK were initially estimated using allometric scaling on data collected in dogs, cynomolgus monkeys and rats. A PK/PD model was derived from a study conducted in rodent and validated by comparing the model predicted response to the one observed in a PET experiment conducted in rhesus monkey. The final PK/PD model, incorporating potential variability and uncertainty on scaled human prediction together with a receptor affinity adjustment derived from in vitro binding studies, was used to design the first-time-in-man and the proof-of-concept study.

Economic evaluations during early (phase II) drug development: a role for clinical trial simulations?

Faced with increasing demands on demonstrating cost effectiveness, pharmaceutical companies are required to conduct pharmacoeconomic evaluations throughout the drug development programme. At present, there is particular emphasis in the literature on burden-of-illness studies and on economic evaluations conducted alongside phase III clinical trials but not on those conducted during phase II clinical trials. This article describes modelling techniques, namely clinical trial simulations (CTS), which are gaining popularity in the clinical research community, but which might also prove to be beneficial during the conduct of these early pharmacoeconomic evaluations. The basic concepts and structure of CTS are described by using published examples of simulations of antipsychotic and anticancer drugs. With the use of an illustrative example of a hypothetical cholinesterase inhibitor for Alzheimer's disease, an integrated CTS-based pharmacoeconomic evaluation is presented. The results demonstrate how the modelling may be of value in 'go/no-go' decisions during the drug development programme.