Pharmacogenetics In Clinical Research And Drug Development

The belief that pharmacogenetics will make a significant contribution to improving patient health care is widely held by both drug regulatory authorities and government bodies. Furthermore, there is a growing body of data to support the feasibility and reality of this view. This data is derived from research conducted both by academic groups and also from clinical studies conducted by pharmaceutical companies. Many of these findings are described in later chapters of this book, but some examples also are given below.

The need for more disease understanding and greater clarity and understanding of optimal patient drug treatment options is recognized by the NIMH and currently incorporated as part of the NIMH Treatment Research Initiative. This program includes 3 large "real-life" clinical trials studying the effectiveness of drugs for unipolar depression (STAR*D: Sequence Treatment Alternatives to Relieve Depression; http://www.edc.gsph.pitt.edu/stard), schizophrenia (CATIE: Clinical Antipsychotic Trials of Intervention effectiveness; www.catie.unc.edu) and bipolar disorder (STEP-BD: Systematic Treatment

Enhancement Program for Bipolar Disorder; www.stepbd.org) (Rush et al. 2003; CATIE, 2003). These clinical studies aim to determine the most appropriate treatment strategies for patients with mood and psychotic disorders. The findings from these studies have the potential to have a major impact on prescribing recommendations for their respective indication. The first data from the STAR*D program is expected in the next 2-3 years. All studies are collecting blood for DNA analysis and investigation of genetic markers. Within Europe, a number of additional large studies are being conducted that aim both to understand the aetiology of depression as well as identifying predictors of drug response; for example the GENDEP and NEWMOOD studies. The findings from these studies will serve to build our knowledge and provide data to better understand the role of pharmacogenetics and how to apply this as part of treatment strategies across the spectrum of psychiatry disorders, including mood disorders, psychosis, substance abuse and dementia.

From the Regulatory side, the FDA in North America (http://www.fda.-gov/cder/guidance/ 5900dft.doc) and other regulatory bodies, including the MHLW in Japan, have published draft guidelines (for example the FDA's VDGS: Voluntary Data Submission Guidelines) to provide guidance to pharmaceutical companies on how pharmacogenetic data will be used as part of regulatory decisions and to encourage the inclusion of pharmacogenetic data as part of drug development. It should be noted that such pharmacogenetic data may be used to support more efficient and successful clinical development strategies, without necessarily resulting in label restrictions based on genotype. Rather, data can be applied to ensure that novel, more effective medicines reach the patient as quickly as possible (Roses 2004). An example of this for psychiatry is the use of pharmacogenetics to dissect out placebo response, or perhaps more correctly, non-specific drug response, a major confounder in clinical studies not only for depression and anxiety, but also for other psychiatry disorders (Macedo et al. 2003). A number of studies now report an association between the common functional 44-base-pair insertion/deletion polymorphism in the promoter region of the serotonin gene transporter and both SSRI response and also placebo response (Smits et al. 2004; Smeraldi et al. 1998). The long (l) allele results in a gene with approximately twice the transcriptional efficiencies of the short (s) allele, and a consequent approximately 50% difference in serotonin uptake. Such data offers the potential to enrol subjects into clinical studies that will have a reduced placebo response and thus increase the opportunity to determine a placebo-drug treatment separation and to detect a more robust efficacy response signal for the investigational compound. Prospective studies and studies investigating the role of this variant across different mechanism classes is required, however, to more fully evaluate these initial findings.

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