Clinical trials in the genomic era: effects of protective genotypes on sample size and duration of trial

Rare genetic variants and treatment response: sample size and analysis issues

Incorporating information about common genetic variants may help improve the design and analysis of clinical trials. For example, if genes impact response to treatment, one can pregenotype potential participants to screen out genetically determined nonresponders and substantially reduce the sample size and duration of a trial. Genetic associations with response to treatment are generally much larger than those observed for development of common diseases, as highlighted here by findings from genome-wide association studies. With the development and decreasing cost of next generation sequencing, more extensive genetic information - including rare variants - is becoming available on individuals treated with drugs and other therapies. We can use this information to evaluate whether rare variants impact treatment response. The sparseness of rare variants, however, raises issues of how the resulting data should be best analyzed. As shown here, simply evaluating the association between each rare variant and treatment response one-at-a-time will require enormous sample sizes. Combining the rare variants together can substantially reduce the required sample sizes, but require a number of assumptions about the similarity among the rare variants' effects on treatment response. We have developed an empirical approach for aggregating and analyzing rare variants that limit such assumptions and work well under a range of scenarios. Such analyses provide a valuable opportunity to more fully decipher the genomic basis of response to treatment.

Genotype-based risk and pharmacogenetic sampling in clinical trials

A number of recent genome-wide association (GWA) studies have identified unequivocal statistical associations between inherited genetic variations, mostly single-nucleotide polymorphisms (SNPs), and common complex diseases such as diabetes, cardiovascular disease, and obesity. Genotyping individuals for these variations has the potential to help redefine how pharmacologic agents undergo clinical development. By identifying carriers of known genomic variants that contribute to susceptibility, a high-risk population can be defined, as well as individuals with potential for a better response to a drug. We evaluated the potential utility that selecting individuals for a trial on the basis of genotypes identified in contemporary GWA studies would have had on recently described clinical trials. We pursued this by constraining both the risks of a disease outcome associated with particular genotypes and overall drug responses to those actually observed in genetic association and clinical trial studies, respectively. We pursued these evaluations in the context of clinical trials investigating drugs for macular degeneration, obesity, heart disease, type II diabetes, prostate cancer, and Alzheimer's disease. We show that the increase in incidence of outcomes in trials restricted to individuals with specific genotypic profiles can result in substantial reductions in requisite sample sizes for such trials. In addition, we also derive realistic bounds for samples sizes for clinical trials investigating pharmacogenetic effects that leverage genetic variations identified in recent association studies.

A pharmacogeneticist's look at drug effects and the drug development process: an overview

This paper describes the functional roles of the closely related pharmacogenetic and pharmacogenomic sciences in medicine. Firstly, they provide means for a better understanding of the function of drugs, and particularly of the differences of drug action between individuals and also between racially categorised populations. Secondly, they are repeatedly used during the long process of new drug development; the developer needs several patient contacts. The development starts with target identification and ends with an official permission for medical use of a drug.

Disease-specific target selection: a critical first step down the right road

Relevance of a drug target for a disease is often inferred with strong belief but fragile evidence. Here, a program for early identification of human disease-specific drug targets using high-throughput genetic associations is described. Large numbers of well-characterized patients (>1000) and matched controls are screened for genetic associations using several thousand (>7000) single nucleotide polymorphisms from more than 1500 genes. The genes were selected because they are members of target classes for which there are precedents for high-throughput chemical screening technology. This review summarizes the methods and intensive data analyses leading to target gene identification for type 2 diabetes mellitus, including the statistical permutation methodology used to correct for many variables.

On the efficiency of targeted clinical trials

The development of genomics-based technologies is demonstrating that many common diseases are heterogeneous collections of molecularly distinct entities. Molecularly targeted therapeutics is often effective only for some subsets patients with a conventionally defined disease. We consider the problem of design of phase III randomized clinical trials for the evaluation of a molecularly targeted treatment when there is an assay predictive of which patients will be more responsive to the experimental treatment than to the control regimen. We compare the conventional randomized clinical trial design to a design based on randomizing only patients predicted to preferentially benefit from the new treatment. Trial designs are compared based on the required number of randomized patients and the expected number of patients screened for randomization eligibility. Relative efficiency depends upon the distribution of treatment effect across patient subsets, prevalence of the subset of patients who respond preferentially to the experimental treatment, and assay performance.

Genome-based pharmacogenetics and the pharmaceutical industry

Pharmacogenetic capabilities have changed markedly since The SNP Consortium made a dense single-nucleotide polymorphism (SNP) map freely available in 2001. For more than 40 years, pharmacokinetics and pharmacodynamics of drug-metabolizing molecules were the focus of practical applications. Today, it is possible to use SNP-mapping technologies to create a genetic profile of each individual that can be used to identify patterns of susceptibility genes for common diseases as well as genetic risk/efficacy factors that are related to the effects of drugs.

Influence of unrecognized molecular heterogeneity on randomized clinical trials

PURPOSE

In solid tumor oncology, decisions regarding treatment and eligibility for trials are governed by histologic diagnosis. Despite this reliance on histology and the assumption that histology defines the disease, underlying molecular heterogeneity likely differentiates among patients' outcomes.

PATIENTS AND METHODS

To illustrate how unrecognized molecular heterogeneity might obscure a truly effective new therapy for cancer, we analyzed the planning assumptions and results of a hypothetical randomized controlled trial of chemoradiotherapy for a cancer found to be drug sensitive in preliminary phase II studies.

RESULTS

Randomized controlled trials of effective cancer therapies can be falsely negative if therapeutic benefit is overestimated during study design because of enrichment of phase II trials for treatment-sensitive subtypes, a beneficial effect in responding patients is diluted by large numbers of nonresponding patients, or a beneficial effect in responders is reversed by a negative effect in nonresponders.

CONCLUSION

Molecular heterogeneity, if it confers different risks to patients and is unaccounted for in the design of a randomized study, can result in a clinical trial that is underpowered and fails to detect a truly effective new therapy for cancer.

Pharmacogenomics: the inherited basis for interindividual differences in drug response

It is well recognized that most medications exhibit wide interpatient variability in their efficacy and toxicity. For many medications, these interindividual differences are due in part to polymorphisms in genes encoding drug metabolizing enzymes, drug transporters, and/or drug targets (e.g., receptors, enzymes). Pharmacogenomics is a burgeoning field aimed at elucidating the genetic basis for differences in drug efficacy and toxicity, and it uses genome-wide approaches to identify the network of genes that govern an individual's response to drug therapy. For some genetic polymorphisms (e.g., thiopurine S-methyltransferase), monogenic traits have a marked effect on pharmacokinetics (e.g., drug metabolism), such that individuals who inherit an enzyme deficiency must be treated with markedly different doses of the affected medications (e.g., 5%-10% of the standard thiopurine dose). Likewise, polymorphisms in drug targets (e.g., beta adrenergic receptor) can alter the sensitivity of patients to treatment (e.g., beta-agonists), changing the pharmacodynamics of drug response. Recognizing that most drug effects are determined by the interplay of several gene products that govern the pharmacokinetics and pharmacodynamics of medications, pharmacogenomics research aims to elucidate these polygenic determinants of drug effects. The ultimate goal is to provide new strategies for optimizing drug therapy based on each patient's genetic determinants of drug efficacy and toxicity. This chapter provides an overview of the current pharmacogenomics literature and offers insights for the potential impact of this field on the safe and effective use of medications.

Pharmacogenomics: unlocking the human genome for better drug therapy

There is great heterogeneity in the way humans respond to medications, often requiring empirical strategies to find the appropriate drug therapy for each patient (the "art" of medicine). Over the past 50 years, there has been great progress in understanding the molecular basis of drug action and in elucidating genetic determinants of disease pathogenesis and drug response. Pharmacogenomics is the burgeoning field of investigation that aims to further elucidate the inherited nature of interindividual differences in drug disposition and effects, with the ultimate goal of providing a stronger scientific basis for selecting the optimal drug therapy and dosages for each patient. These genetic insights should also lead to mechanism-based approaches to the discovery and development of new medications. This review highlights the current status of work in this field and addresses strategies that hold promise for future advances in pharmacogenomics.

Opportunities and strategies for introducing pharmacogenetics into early drug development

Following the publication of the first draft of the human genome, this is a good time to re-analyse the potential contribution of genomics to drug development. Pharma, biotech and academia are already queuing up to deliver novel data impinging on every aspect of medicine and we can foresee a five-year scenario in which every new drug with a known mode of action will have a target gene sequence in the public domain. As such, current development strategies must ultimately be capable of anticipating and addressing genetic issues. This article attempts to position recent developments in genomics from an industrial perspective.

Pharmacogenetics and the practice of medicine

"If it were not for the great variability among individuals medicine might as well be a science and not an art." The thoughts of Sir William Osler in 1892 reflect the view of medicine over the past 100 years. The role of physicians in making the necessary judgements about the medicines that they prescribe is often referred to as an art, reflecting the lack of objective data available to make decisions that are tailored to individual patients. Just over a hundred years later we are on the verge of being able to identify inherited differences between individuals which can predict each patient's response to a medicine. This ability will have far-reaching benefits in the discovery, development and delivery of medicines. Sir William Osler, if he were alive today, would be re-considering his view of medicine as an art not a science.