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(Created page with ' The biggest problem that is plaguing the pharmaceutical industry is the attrition of drug candidates over the process of drug discovery and development. The increased cost of th…')

Current revision as of 13:20, 9 January 2019

The biggest problem that is plaguing the pharmaceutical industry is the attrition of drug candidates over the process of drug discovery and development. The increased cost of the research and the delay in timelines will mean that the costs of drugs will increase and can affect the public health. An early termination of a candidate without the expected qualities will help in reduction of the overall cost of drug R and D. This approach has been proven effective by multiple studies. An understanding of the reasons that contributed to the drug development failures is important for determining which drug candidate will fail. A significant cause of attrition is due to safety issues arising as a result of animal toxicity testing. Pharmacokinetic profile of the compound is important factor in the assessment of the safety of these compounds. Today, Pharmacokinetic studies determine the success or failure of a drug with emphasis on cost, speed and accuracy.
Over the last few years, Pharmacokinetics has emerged as an integral part of drug development, especially when 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 processes are together abbreviated 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. Hence, In vivo pharmacokinetic (PK) screening can be instrumental in the selection of lead compounds with desirable bioavailability profiles for further investigation in drug development programs.
This increased consideration of the suitability of the pharmacokinetic profile has led to a reduction in the early termination of programmes due to pharmacokinetic failings. In turn this has shifted the focus on other compounds being considered unsuitable for drug development. Safety and Efficacy are such reasons.  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 pharmacodynamics studies and the identification of appropriate safety and efficacy biomarkers provide avenues to increase the confidence in rationale and safety of new drug molecules.
Characterizing the relationship between the pharmacokinetics (PK, concentration vs. time) and pharmacodynamics (PD, effect vs. time) is an important tool in the discovery and development of new drugs. Also, the PK/PD modelling can help in increasing the conversion rates from in vitro to in vivo to further these findings in preclinical and clinical settings. The studies are designed with the basic assumptions of understanding relationship between the exposure of the medication and associated therapeutic activ Pharmacokinetics ity. It is observed that such relationships are very complex. We see that such relationships are really complex. So, it is important that we design preclinical models that will provide information about mechanistically relevant PK/PD models. As data becomes available, initial models can be refined through an iterative process. A predictive tool that can have an in-depth understanding about the efficacy requirements is the ultimate output that we get from this exercise. 
A well designed PK/PD will offer logical approach to understand the mechanism of action of drug and select the most optimal approach. Allocation of PK/PD modelling in the development programs ca help in minimization of in vivo models in the later phase and predict the dosage ranges for early clinical testing. Integration of data from different studies in a sequential manner is made possible with the PK-PD models. As the result of the above said reasons, PK and PD are becoming more and more important in the drug R and D.
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