Pharmacokinetic studies in Brussels711

The attrition of drug candidates during the long process of drug discovery and development is the issue that is faced by the pharmaceutical industry today. The cost and timelines are adversely affected creating loss to the companies and huge impact on the quality of life at large. If the drug development program that will fail can be identified very early in the drug discovery and abandoned, the overall drug development costs will significantly decrease. In order to achieve this it is important to understand the root causes of attrition that have led to drug development failure in the past. A major reason for this attrition is the safety issues that arise during the animal toxicity testing. The PK profile of the compound is an important factor to determine the safety during the early stages of drug development. PK studies now help in determining the success of the drug with ability to accurately predict the drug properties and also curtail the costs of research.

Pharmacokinetics has evolved over the past two decades to become an integral part of the drug development process  especially in identifying a drug’s biological properties. PK provides the mathematical basis for understanding the absorption, biodistribution, metabolism of the drug and elimination of it from the body. These four processes are usually called as ADME These factors become critical in the case of assessing risk in a new chemical entity often abbreviated as NCEs. The undesired PK characteristics include low bioavailability due to high extraction or poor absorption characteristics, short elimination half-life leading to short duration of action and excessive variability due to genetic or environmental factors. Many tools have been developed for predicting drug absorption, drug clearance and drug-drug interaction. Along with this PK parameters from animals to man have also been introduced. As we see the resultant PK screening results can be used in the selecting a lead compound with desired bioavailability profile. This information can be used in furthering the drug discovery programs.

There has been a rise in consideration of suitability of the PK profile of the drug candidate. This has led to the decrease in the early termination of the programs due to pharmacokinetic failings. This in turn has highlighted the other causes for compounds being considered unsuitable for drug development. Such reasons include inadequate safety and efficacy.  Both of these aspects can be partially addressed by extending the prediction of pharmacokinetic behaviour to include the pharmacodynamic profile of the drug candidate. Preclinical PD studies and the safety and efficacy biomarkers provide depth of data and help in assessment of safety of the drug candidates.

Drawing inferences from the correlation between the Pharacokinetics and Pharmacokinetics is an important tool that is emerging. Additionally, PK/PD modeling can help increase the translation of in vitro compound potency to the in vivo setting, reduce the number of in vivo animal studies, and improve translation of findings from preclinical species into the clinical setting. Rational study design is based on the assumption of a causal relationship between exposure to a medication and its therapeutic activity. Such relationships are usually very complex. Therefore it is important to design robust preclinical studies that will provide information to build mechanistically relevant PK/PD mathematical models. Based on the data from these models, we can further refine the basic models of study. Pharmacokinetic studies in Brussels  The ultimate output is a powerful predictive tool based on an in-depth understanding of the requirements for efficacy.

A well designed PK/PD study offers a rational approach to efficient and informative drug development and can help the project team to understand the mechanism of action of a drug and select the optimal compound. Applying PK/PD modelling in early discovery and development programs can minimize animal usage, shorten the development time, estimate the therapeutic index, and predict the dose ranges in early clinical testing. PK-PD models help in the aggregation of data from various studies and help in deeper understanding of relationship between drug and the disease. As the result of the above said reasons, PK and PD are becoming more and more important in the drug R and D.