The Impact Of Pharmacogenetics On Clinical Drug Development

Historically, fewer than 10% of new chemical entities (NCEs) entering preclinical development are approved for clinical use, often because of unacceptable toxicity in animal studies or Phase I human trials or insufficient efficacy (Kleyn and

Table 43.4. Comparison of different types of ''genetic testing''.

Application

Disease genetics

Pharmacogenetics/medicine response tests

What is being tested

Potential benefits

Potential risks

*Rare Mendelian (monogenic) diseases, ''causal'' genes *Complex common diseases (multifactorial), susceptibility genes

Prediction of occurrence, diagnosis of disease; insights into disease mechanisms and development of new medicines

Informational risk to patient and family, with related ethical, legal and social issues (employment, insurance, etc.)

*Genes related to drug metabolism or action

*SNP PrintsSM related to drug safety or efficacy

Optimal individual response to medicine

Low informational risk; data provided will relate only to individual response to specific medicines

Vesell, 1998). The cost of bringing a new drug to market is approximately $500 million; the costs of ADRs and treatment failures, discussed earlier, are staggering. The application of pharmacogenetic research and knowledge could result in streamlining and improving the clinical development process in several ways:

* by initial toxicogenomic screening of compounds to detect selective metabolism, disposition or action related to known polymorphic enzymes, transporters or targets,

* by enabling fewer subjects to be recruited into clinical trials, and

* by enhancing the efficacy and safety profiles of medicines in targeted populations.

Many pharmaceutical companies now routinely screen NCEs to see if they are metabolized selectively by known polymorphic enzymes, and development is discontinued or altered to include additional pharmacokinetic studies for many of those that are because of the potentially increased risk of serious ADRs or lack of efficacy in subpopulations of patients (Zuhlsdorf, 1998). The development and use of MRTs may serve to "rescue" some of these NCEs: if a cost-effective, valid and accessible predictive test is available to screen patients before the drug is prescribed, along with evidence-based guidelines for dose adjustments or drug avoidance, then many valuable medicines that in the past would have been abandoned may make it to market. The same may be true for approved medicines and even for some that have been withdrawn from market. For example, terfenadine (Seldane®) caused ADRs in patients who had a specific CYP2D6 gene polymorphism and also were taking erythromycin— they were unable to metabolize terfenadine in this situation, which caused toxic accumulation of the drug in the body. The FDA worked with the pharmaceutical manufacturer to distribute appropriate warnings about the possible risks of its use with concomitant medicines, but the company and FDA decided that the drug's risk-benefit ratio did not justify its continued use. If a screening test to identify patients at risk for this problem had been available, it might have been possible to keep the drug on the market while protecting some of those most likely to experience toxicity from it (Bhan-dari et al., 1999).

Discussion of the potential impact of pharma-cogenetics on clinical trial design is beyond the scope of this chapter, but it is clear that many pharmaceutical companies recognize its importance and are planning to initiate pharmacogenetic studies in the near future (Ball and Borman, 1997). Lichter and McNamara (1995) suggested one approach for incorporating pharmacogenetics into clinical trials:

* Perform preclinical identification of metabolic pathways and population screening for common DNA sequence variants of the relevant enzymes, transporters, receptors and target genes (and their homologues), as discussed above.

* Consider the ethnicity of study populations based on known differences in the frequency of specific polymorphisms.

* During Phase I trials, type subjects for the genes known to control the drug's metabolic path-way(s) to allow possible correlation of ADRs with genotype, and use this information as a basis for subject selection in Phase II and III studies.

* During Phase II trials, type any identified relevant polymorphisms in the entire study group. Also type the gene product and related targets in all subjects, allowing assessment of allele frequencies in the population and in responders vs. non-responders. Use these data as a basis for subject selection in Phase III trials.

* If useful genetic markers of efficacy or ADRs are identified during Phase II, the Phase III group could be expanded to include a cohort prescreened to include likely responders and those at low risk of ADRs.

This approach is limited by its reliance on identified candidate genes (genes selected on the basis of existing knowledge or an informed guess) and molecular pharmacology to identify drug-receptor interaction and down-stream signaling pathways, and unexpected associations (either causal or resulting from LD) may not be recognized.

Another approach that is being used already by some pharmaceutical companies and holds even greater promise as technological advances increase the accuracy, feasibility and cost-effectiveness of high-throughput whole-genome scanning, will involve collecting a single blood sample for DNA analysis from all consenting participants in selected Phase II and III clinical trials (after approval by the appropriate ethics review boards and provision of specific informed consent by subjects). This sample may be used to identify the occurrence of known polymorphisms affecting drug response, to evaluate candidate genes suspected of being involved in the disease or drug response and to assess patterns of SNP or haplotype occurrence related to efficacy or ADRs, allowing the creation of a SNP PrintSM to screen potential subjects or patients (post-approval) for their likely response to the drug or determine heterogeneity of the disease in patients with similar phenotypes (Roses, 2000b).

Regulatory agencies might be concerned, appropriately, that the smaller numbers of patients in these streamlined clinical trials would be insufficient to detect rare ADRs (<1: 1000) and that patients who did not receive or "pass" the recommended MRT for the drug would nevertheless receive it and be at increased risk of harm. However, rare ADRs are not likely to be detected even in the relatively large clinical trials that are conducted now; it certainly is not feasible to enroll the approximately 65 000 patients that would be required to be 95% confident of detecting three or more cases of an ADR with an incidence of 1 : 10 000 (Lewis, 1981). The major, albeit rare, ADRs associated with dexfenfluramine, zomepirac, benoxaprofen, troglitazone and terfenadine were not detected until after they reached the market. Extensive pre-approval safety testing in even larger populations is a possible solution, although, as noted above, it will be impractical to identify very rare ADRs in clinical trial study populations, and the increased cost and delayed time to market is likely to create significant financial barriers from the perspective of the pharmaceutical companies (and ultimately consumers and payers, to whom the cost will be passed along) (Roses, 2000a).

One solution to this problem would be an extensive, regulated post-approval surveillance system that incorporates the collection of pharma-cogenetic data. Roses (2000b) proposes that hundreds of thousands of patients receiving a medicine would have filter paper blood spots taken (perhaps from the original blood sample used for the MRT) and stored in a central location. As rare and/or serious ADRs are reported and characterized, DNA from affected patients could be compared with that of control patients, allowing ongoing refinement of the MRT. There is increasing pressure to improve the inconsistent and largely unregulated current system of post-marketing surveillance, and many authors agree on the need to incorporate pharma-cogenetic data in some form into a revised system (Edwards and Aronson, 2000; Nelson, 2000).

Another approach is one that would put increasing control of medical data in the hands of those most directly affected by it—consumers. In this scenario, an individual could choose to have a one-time blood sample taken for DNA analysis and stored at a tightly secured central repository. As research into disease-related genes, genetic risk factors and genetic associations with medicine responses progressed, the consumer or a designated representative (such as a health care provider) could request that the sample be analyzed using relevant MRTs (including SNP PrintsSM) and other markers. This "bank" could serve as a central repository for the samples themselves and as a central database of information including well-established knowledge, current research and even opportunities for clinical trial subjects with specific conditions or genotypes. It could trigger genetic "alerts" to consumers who chose to provide a medical and family history as new research results potentially relevant to them became available. A host of ethical, legal and social issues would need to be addressed as part of this venture, but it presents one option for an efficient, centralized and consumer-controlled bank of health-related genetic expertise and information.

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