Pharmacokinetic-pharmacodynamic modelling of oxprenolol in man using continuous non-invasive blood pressure monitoring

In silico optimization of pharmacokinetic properties and receptor binding affinity simultaneously: a 'parallel progression approach to drug design' applied to β-blockers

The present work exploits the potential of in silico approaches for minimizing attrition of leads in the later stages of drug development. We propose a theoretical approach, wherein 'parallel' information is generated to simultaneously optimize the pharmacokinetics (PK) and pharmacodynamics (PD) of lead candidates. β-blockers, though in use for many years, have suboptimal PKs; hence are an ideal test series for the 'parallel progression approach'. This approach utilizes molecular modeling tools viz. hologram quantitative structure activity relationships, homology modeling, docking, predictive metabolism, and toxicity models. Validated models have been developed for PK parameters such as volume of distribution (log Vd) and clearance (log Cl), which together influence the half-life (t1/2) of a drug. Simultaneously, models for PD in terms of inhibition constant pKi have been developed. Thus, PK and PD properties of β-blockers were concurrently analyzed and after iterative cycling, modifications were proposed that lead to compounds with optimized PK and PD. We report some of the resultant re-engineered β-blockers with improved half-lives and pKi values comparable with marketed β-blockers. These were further analyzed by the docking studies to evaluate their binding poses. Finally, metabolic and toxicological assessment of these molecules was done through in silico methods. The strategy proposed herein has potential universal applicability, and can be used in any drug discovery scenario; provided that the data used is consistent in terms of experimental conditions, endpoints, and methods employed. Thus the 'parallel progression approach' helps to simultaneously fine-tune various properties of the drug and would be an invaluable tool during the drug development process.

The role of population pharmacokinetics in drug development in light of the Food and Drug Administration's 'Guidance for Industry: population pharmacokinetics'

Population pharmacokinetics (PPK) has evolved from a discipline primarily applied to therapeutic drug monitoring to one that plays a significant role in clinical pharmacology in general and drug development in particular. In February 1999 the US Food and Drug Administration issued a 'Guidance for Industry: Population Pharmacokinetics' that sets out the mechanisms and philosophy of PPK and outlines its role in drug development. The application of PPK to the drug development process plays an important role in the efficient development of safe and effective drugs. PPK knowledge is essential for mapping the response surface, explaining subgroup differences, developing and evaluating competing dose administration strategies, and as an aid in designing future studies. The mapping of the response surface is done to maximise the benefit-risk ratio, so that the impact of the input profile and dose magnitude on beneficial and harmful pharmacological effects can be understood and applied to individual patients. PPK combined with simulation methods provides a tool for estimating the expected range of concentrations from competing dose administration strategies. Once extracted, this knowledge can be applied to labelling or used to assess various future study designs. PPK should be implemented across all phases of drug development. For preclinical studies, PPK can be applied to allometric scaling and toxicokinetic analyses, and is useful for determining 'first time in man' doses and explaining toxicological results. Phase I studies provide initial understanding of the structural model and the effect of possible covariates, and may later be used to evaluate PPK differences between patients and healthy individuals. Phase II studies provide the greatest opportunity to map the response surface. With these PPK models it is possible to gain an improved understanding of the role of the dose on the response surface and of the range of expected responses. In phase III and IV studies, PPK is implemented to further refine the PPK model and to explain unexpected responses. Planning for the implementation of PPK across all phases of drug development is necessary, as well as planning for individual PPK studies. Planning should include: defining important questions, identifying covariates and drug-drug interactions that need to be investigated, and identifying the applications and intended use of the model(s). The plan for each project must have a strategy for data management, data collection, data quality assurance, staff training for data collection, data analysis and model validation.

Impact of pharmacodynamic variability on drug delivery(1)

Modern pharmaceutical delivery systems are intended to produce plasma drug concentration versus time profiles that result in optimum therapeutic efficacy and a minimum of drug concentration-dependent adverse effects. To accomplish this requires that the drug delivery rate and temporal profile be based on the pharmacokinetic and pharmacodynamic characteristics of the specific medicinal agent. Pharmacokinetic and pharmacodynamic parameters are subject to considerable interindividual variability. Whereas the importance of pharmacokinetic variability is generally recognized, the significance of pharmacodynamic variability (i.e., variability in the relationship between effect intensity and drug concentration) is not as widely appreciated. Pharmacodynamic variability is typically quite large, reproducible, and often substantially exceeds the relative magnitude of pharmacokinetic variability. This article consists of a review of how to assess pharmacodynamic variability, clinical examples of pharmacodynamic variability of drugs with a wide range of indications, and an outline of mechanisms of pharmacodynamic variability.

The effect of oxprenolol dosage time on its pharmacokinetics and haemodynamic effects during exercise in man

We have studied the effect of dosage time of oxprenolol (Trasicor) on its pharmacokinetics and pharmacodynamics in six healthy volunteers. The drug effects measured were heart rate and systolic blood pressure during exercise. Oxprenolol was taken orally at 08.00 h, 14.00 h, 20.00 h, and 02.00 h in randomized order, with 1 week between successive doses. There were differences in the pharmacokinetics of oxprenolol for the ratio between the apparent volume of distribution and systemic availability (P = 0.04) and for elimination half-life (P = 0.006). Both were lowest after administration at 14.00 h (163 (77) l and 1.2 (0.6) h; mean (SD)) and highest after administration at 02.00 h (229 (100) l, and 1.7 (0.6) h). The systolic blood pressure during exercise before oxprenolol did not vary with dosage time, but heart rate during exercise before intake was lowest before dosage time 08.00 h and highest before dosage time 20.00 h (P = 0.03). The time-course of heart rate during exercise after oxprenolol was described by a model that incorporated the factors drug concentration and spontaneous diurnal variation. EC50 and Emax did not vary between dosage times. The spontaneous diurnal variation in heart rate during exercise was unaffected by oxprenolol, leading to an apparently greater effect of oxprenolol during the night than during the day.