Pharmacology Population - Assignment Example

 POPULATION PHARMACOKINETICS Introduction In the manufacturing of drugs, there is often emphasis on which diseases the drug can treat without looking much into who would take the drug and the effect of the drug on the person based on specific patient characteristics (Jagdale, Patil, Kuchekar and Chabukswar, 2011). This situation is what makes population pharmacokinetics (pk) very important. This is because population pk seeks to study sources of drugs and their correlates of variability in patients who are the target populations for the drug (Greenberg, 2000). Contribution of population-pharmacokinetics to drug development There have a number of studies that have helped in identifying the contributions and benefits of population pk to the drug development process. In a study by Bartelink, Rademaker, Schobben, et al. (2006), population pk was found to be a very important approach through which not just pharmacokinetic information is obtained from sparse data sets but also pharmacodynamic information obtained from this same sparse data set. Leeder (2004) also observed that there stages in the drug development process where very large population may be needed but with only a few observations per patient so as to determine the exact and unique differences with drug behaviour in each patient based on special characteristics. To achieve this, population pk is employed or used to obtain information at both the phase II and phase III clinical trials among patients. It is not surprising that Ernest, Elder, Martini, et al. (2007) identified population pk as a practice associated with several pharmaceutical companies in the course of their drug development process. Certainly, population pk comes as a single most reliable mechanism by which dosage determination to drugs can be done due to the size of the population used in the sparse data sets, each of whom is observed for very specific outcomes based on their demographic and pathophysiology characteristics. Also writing on the contribution of population pk to drug development, Roosmarijn et al. (2011) found that there are instances when intensive blood sampling can be attained. Meanwhile, Hsieh and Korfmacher (2006) noted that where intensive blood sampling is possible, there is the benefit of replicating the outcomes with particular blood samples for a larger population size. This means that where intensive blood sampling is not possible an alternative is needed to ensure that almost all populations are catered for. Typical situations in drug development where intensive blood sampling has not been attainable include drug development processes for children, cancer and AIDS patients (Baaske, Wienken, Reineck, Duhr and Braun, 2010). There is a typical example with a study by the US Food and Drug Administration for AIDS patients where instead of using intensive blood sampling in the drug development process, pharmacokinetic screening was rather employed at the phase II and phase III of the study (Greenberg, 2000). In a similar study by the Medicines and Healthcare Products Regulatory Agency in UK where the target population was cancer patients, using pharmacokinetic screening did not only proof useful in attaining important clinical information but also was seen to be a generally cost effective approach to get such information pertaining to both pharmacokinetic and pharmacodynamic variability in treated patients (Ruiz-Garcia, Bermejo, Moss and Casabo, 2008). One other major contribution of population pk to drug development is the ability to base on outcomes with population pk studies to customise pharmacotherapy. In a study by Raymond and Brasseur (2005), it was found that there are several factors that make this outcome with customised pharmacology possible. In the first place, population pk requires that multiple samples from one person are not used. In effect, variability in drug concentrations is achieved for very specific patient populations (Bonate, 2005). This way, it is possible to assign differences in pharmacokinetics to specific patient characteristics and hence customisation of pharmacotherapy. In the second instance, it is seen that when population pk is used, it is possible to emphasise on subgroups of populations. In effect, instead of generalising the outcomes of population pk studies, very specific assignment of pharmacotherapy is done based on pharmacokinetic variations in the subgroups (Tucker, 2012). What is more, instead of using healthy volunteers, population pk requires the use of actual patients taking a drug (Jager, Albert, Preuss and Ashauer, 2011). This way, it is possible to gain decision-oriented results based on patient characteristics. A typical example of population pk that was used in achieving customise pharmacotherapy was in the preparation of metformin, where the safe use of drug in patients with renal impairment was found (Jagdale, Patil, Kuchekar and Chabukswar, 2011). Limitations to population pk The contributions discussed above notwithstanding, there are some limitations that have been associated with the use of population pk. In the first place, even though there are different software that have been used for pharmacokinetics modelling including NONMEM and Phoenix NLME, there are many who believe that most of these software are not user-friendly and that there is yet to be a breakthrough with the discovery of user-friendly software (Samara and Granneman, 1997). The issue of analysis control by imagination has also been identified as a major limitation (Roosmarijn et al., 2011). Such forms of analysis control by imagination arise mainly due to the size of population involved in population pk. The fact that more experimentally credible features such as blood sampling has not been used have been used is another reason for using imagination (Baaske et al., 2010). There have also been those who have questioned the rapidness of population pk especially when time is of major concern with the drug development process. Using the case of the recent outbreak of Ebola as an example, it would be found that the mortality rate associated with the disease required a very rapid way of determining the outcome of drugs in patients. When population pk is used in such situations, the fact that they are less rapid will possibly delay the process. Conclusion Based on the various evidence and findings given above, it can be concluded that population pk plays very significant and contributing role in pharmacology. This is because it is through population pk that populations of patients are differentiated based on their unique characteristics. Some of the characteristics that have been the area of focus for most works of population pk especially in the area of anti retroviral drugs in HIV patients include body weight, therapeutic features and pathophysiology. By having a vivid understanding of the unique characteristics of patients, it is possible to identify how various drug concentrations will impact on these patients. In effect, the right measure of pathophysiology factors that gives an expected change in patients is known in determining dosage of drugs. References Baaske P, Wienken CJ, Reineck P, Duhr S and Braun D (2010). "Optical Thermophoresis quantifies Buffer dependence of Aptamer Binding". Angewandte Chemie International Edition, Vol. 49 No. 12, pp. 1–5. Bartelink I.H., Rademaker C.M., Schobben A.F., et al. (2006). Guidelines on paediatric dosing on the basis of developmental physiology and pharmacokinetic considerations. Clinical Pharmacokinetics, Vol. 45 No. 11, pp. 1077–1097. Bonate P.L. (2005). "Recommended reading in population pharmacokinetic pharmacodynamics". The AAPS Journal, Vol. 7 No. 2, pp. 363–73. Ernest T.B., Elder D.P., Martini LG, et al. (2007). Developing paediatric medicines: identifying the needs and recognizing the challenges. Journal of Pharmacology and Pharmacotherapeutics, Vol. 59 No. 8:1043–1055. Greenberg M. D. (2000). AIDS, experimental drug approval, and the FDA new drug screening process. Legislation and public policy, vol. 3 No. 2, pp. 295-303 Hsieh Y. and Korfmacher W.A. (2006). "Increasing speed and throughput when using HPLC-MS/MS systems for drug metabolism and pharmacokinetic screening". Current Drug Metabolism Vol. 7 No. 5, pp. 479–89. Jagdale S.C., Patil S.A., Kuchekar B.S. and Chabukswar (2011). Preparation and Characterization of Metformin Hydrochloride — Compritol 888 ATO Solid Dispersion. Journal of Young Pharmacists. Vol. 3 No. 3, pp. 197–204 Jager T., Albert C., Preuss T.G. and Ashauer R. (2011). "General unified threshold model of survival--a toxicokinetic-toxicodynamic framework for ecotoxicology". Environmental Science & Technology, Vol. 45 No. 7, pp. 2529–40. Leeder J.S. (2004). Translating pharmacogenetics and pharmacogenomics into drug development for clinical pediatrics and beyond. Drug Discovery Today. Vol. 9 No. 13, pp. 567–573. Raymond A. and Brasseur D. (2005). Development of medicines for children in Europe: ethical implications. Paediatric Respiratory Reviews, Vol. 6 No. 1, pp. 45–51. Roosmarijn F. W. et al. (2011). The role of population PK–PD modelling in paediatric clinical research. European Journal of Clinical Pharmacology. 67, pp. 5-16. Ruiz-Garcia A., Bermejo M., Moss A. and Casabo V.G. (2008). "Pharmacokinetics in drug discovery". Journal of Pharmaceutical Sciences, Vol. 97 No. 2, pp. 654–90. Samara E. and Granneman R. (1997). Role of population pharmacokinetics in drug development. A pharmaceutical industry perspective. Clinical Pharmacokinetics, Vol. 32 No. 4, pp. 294-312 Tucker G.T. (2012). "Research priorities in pharmacokinetics". British Journal of Clinical Pharmacology, Vol. 73 No. 6, pp. 924–6. Read More