8 min readPharmacogenomics and Personalized Medicine: Just a Technology Bubble or an Opportunity for Investment?

The pharmaceutical industry is facing some key challenges such as the increase in drug development cost, the decrease in the number of drugs being approved, and scrutiny from regulatory authorities to name a few.  Patients themselves are demanding more effective and safer drugs. Thus the field of pharmacogenomics presents a convincing alternative to guide drug development and therapy. Pharmacogenomics deals with the influence of genetic variations on drug response in patients by correlating gene expression with a drug’s efficacy. Pharmacogenomics research refers to the use of DNA methodologies to develop reliable biomarkers to predict drug response, side effects, dosage, susceptibility and disease condition. Personalized medicine refers to individualized pharmacotherapy – offering appropriate treatment to the right person as needed. The trend is changing from developing “blockbuster” drugs to more personalized medicine, which could alter the competitive landscape in the pharmaceutical industry.

Personalized medicine: Medical Emergency?

Recent reports of mishaps taking place due to improper drug metabolism, even when taken at optimal dose, has forced companies to consider individualized medicine more of a necessity than a mere research project. A few examples include the death of a nine year old boy in 1999 due to improper metabolism of Prozac due to a genetic defect in the CYP2D6 gene, and the death of an infant in 2006 due to breast feeding of the mother who had been given codeine, which eventually metabolized into morphine. Every year several hundreds of patients either do not benefit from the treatment they are provided or develop adverse reactions to it. These are compelling reasons enough to pursue personalized medicine as a future directive.

Pharmacogenomic testing- Principles

Genetic research is generally being done in two main areas in the pharmaceutical:

  • Patient Genetics (Pharmacogenetics)
    The goal of research in patient genetics is to generate an understanding that will aid in making safe and more effective drugs for the specific individuals for whom they are prescribed. Variations in ADME genes (including transporters) and drug targets (and associated genes) may result in the absence of protein or the production of protein with altered or no activity. There are several described cases of genetic variation in ADME genes, mainly accounting for the variation in plasma drug concentration in patients following a fixed dose, as well as cases of genetic variation in the target genes affecting clinical outcomes. Among the polymorphic drug metabolizing enzymes most extensively investigated are the cytochrome P450s (CYPs). The clinical significance of these variations depends primarily on the contribution of the specific pathway to the overall metabolism of the drug and the therapeutic index of the drug, as well as the activity of its metabolites.
  • Disease Genetics
    The goal of the research in disease genetics is to understand the contribution of genes and underlying biological pathways to chronic diseases in order to create therapies that are better tailored to the diseases under study. One of the familiar examples of disease genetics applied to medical practice is the APOE genotype and the clinical response to tacrine treatment in Alzheimer’s disease.

Several genetic research studies in these two areas are currently part of clinical trials in pharmaceutical companies to address pharmacokinetics, efficacy and safety issues. In most cases, genetic research studies are exploratory in nature, to proactively or retroactively test hypotheses or to generate new hypotheses. Pharmacogenetics is also incorporated early in the drug discovery pipeline to ensure that discovery efforts are directed at developing drugs against the most common target variants and against targets that display a manageable degree of genetic variation.

Current Applications
Pharmacogenomics research is based on the ‘genotype to phenotype’ principle i.e. correlation of the genetic information and clinical information. Thus it finds practical applications in:

  • Understanding and validating drug target/ metabolic pathways
  • Identification of optimal dosage
  • Improving drug safety and understanding adverse side effects
  • Identification of patients benefiting from personalised medicine

 


Figure 2: Applications of pharmacogenomics in the drug development process.

Challenges

Scientific complexities
The lack of effective translational medicine is a major challenge for the practical application of pharmacogenomics. Scientific advances in genetic testing, automation and microarray technologies have made sure that there is no shortage of data from pharmacogenomics research. Pharmaceutical companies are investing heavily in data management, mining and analysis tools. However, as more and more data are generated, there is an increase in the gap between the bedside and the bench.

The correlation of genetic information with clinical information is becoming difficult, due to the inherent biological complexity – the effects of several genes and statistical considerations. Data from pharmacogenomics research in most cases are not replicated across clinical trials, owing to the biological complexity as there are too many genetic associations. The Serious Adverse Event (SAE) consortium aims to facilitate the understanding of genetic basis of adverse reactions.

Commercial feasibility issues
Critics of personalised medicine often suggest that interest in research for a given pharmacogenomics study would decrease because it would only serve niche market. A personalised approach would reduce new patient trials for some therapies. However, reduction in initial sales will be compensated by greater compliance, leading to higher product use (depending on the market size). Frost & Sullivan believes that the commercial feasibility of personalised medicine is not what is gained or lost by moving forward, but what is at stake by not moving forward.

Regulatory challenges
FDA is the first agency to put in place a regulatory framework for pharmacogenomics research. This includes submission of pharmacogenomics data and development of drugs and diagnostics for the same. Despite these efforts, co-development of drugs and linked diagnostics is difficult because of the regulatory and time constraints. This emphasises the need to reach a decision point at the end of Phase- II clinical trials about the development of diagnostics – which is very difficult, given the limitations on sample size.

Drug developers are also seeking guidance from regulatory authorities on:

  • The duration and process of collecting DNA/RNA samples in clinical trials
  • Dose adjustment and information printing on labels
  • Methodology of analyzing pharmacogenomics research data
  • Infrastructure requirement for pharmacogenomics testing labs

The Pharmacogenetics Working Party, formed by The European Medicines Agency (EMEA), has issued guidelines for its briefing meetings and for biobanking. The EMEA and the FDA have jointly initiated a procedure for the submission for pharmacogenomics data. Drug manufacturers are hoping that incentives such as fast-track approvals resulting in innovative drug development will be offered by regulatory agencies for compounds that are characterised via pharmacogenomics approaches.

Market Overview

What is driving the pharmaceutical industry to personalised medicine?

The factors that drive the pharmaceutical industry from the ‘blockbuster’ model to the personalised medicine model are:

  • The need for innovation and increased productivity
  • Competitive pressures
  • Huge technological advancement in genomics
  • The demands from patients for more effective and safer drugs

Despite industry-wide efforts to reduce drug development times, the average time to bring a new molecular entity (NME) to the market is still 13 years. At the same time, R&D investment has almost doubled since the early 90’s. Another key challenge is the decreasing novelty in pharmaceutical pipeline in the market. Hence, pharmacogenomics seems to offer opportunities to drive innovation and improve the productivity of the pharmaceutical industry.

 

Figure 3: Illustration depicting the future advancements in pharmacogenomics.

Despite the significant level of uncertainty that would make it an uninteresting investment opportunity, companies have been compelled to invest as it is clear that competitors are making relevant progress. Several companies have signed co-development agreements and are beginning to invest in building an internal pharmacogenomics infrastructure. For example, Johnson &  Johnson has signed over 700 such deals as revealed from the deals database. The desire to meet patients’ unmet medical needs, the necessity for product differentiation to gain market share and reimbursement in increasingly crowded markets in several therapeutic areas are forcing companies to invest in pharmacogenomics research.

Genetic testing and pharmacogenomics services
Genetic testing has been made easy with the increase in availability of reagents and pharmacogenetics services. Diagnostic laboratories are marketing pharmacogenomics services to physicians and in some cases, patients also.

The FDA has approved several pharmacogenomics tests that have allowed physicians and patients to make more personalised treatment decisions. The VysisPathVysionHER-2 DNA Probe kit from Vysis, Inc (now a part of Abbott Molecular Inc.) was probably the first personalised diagnostic kit to be marketed. The kit is used to detect and quantify the HER-2 gene in breast cancer patients.

A few more examples include:

  • Roche Molecular Systems’s Amplichip, approved by FDA in January 2005, detects polymorphisms in two CYP enzymes. These enzymes are involved in the metabolism of over a quarter of all the drugs marketed. Test results are used to determine dosage in patients.
  • Genzyme’s invader UGT1A1 molecular assay was approved by FDA in August 2005. This technology is able to detect polymorphisms in UGT1A1, and subsequently dosing decisions can be made for patients taking irinotecan or other drugs metabolized by UGT1A1.
  • Visible Genetics’ TRUEGENE HIV-1 genotyping kit uses sequencing technology to identify variation in HIV sequences, which could allow physicians to determine which drug would treat the HIV infection effectively.
  • The Cell Search Technology from Veridex, one of Johnson & Johnson’s diagnostic companies, has been approved by the FDA, in January 2004, in cases of metastatic breast cancer to predict progression-free survival and overall survival in patients.
  • In February 2007, the FDA approved the first microarray-based test, called the MammaPrint test, to determine the likelihood of breast cancer returning within 5–10 years after a woman’s initial cancer.

Increase in the number of pharmacogenomics consortia
Several pharmacogenomics task forces and consortia comprising of various companies, academic researchers and government agencies such as the FDA and EMEA, have been recently formed.

The PhRMA Biomarker Consortium, the Predictive Safety Testing Consortium, was formed under the guidance of the Critical Path Institute. The Serious Adverse Event Consortium, involving pharmaceutical companies, the FDA and the scientific community was created to overcome challenges in biomarker identification and pharmacogenomics research.

The Industry Pharmacogenomics Working Group (PWG) is an association of 18 pharmaceutical companies engaged in both drug development and pharmacogenomics research. This group has published papers on topics such as terminology, informed consent forms for genetic research and the return of genetic data to patients. The Personalized Medicine Coalition (PMC) is a non-profit group that works educate patients on the advantages of personalised medicine. PMC members include payers, patient welfare groups, healthcare services providers, governmental agencies, drug and diagnostic manufacturers and academic institutions working together to educate the public about the issues that will shape how personalized medicine develops.

These recent activities and formations continue to illustrate the prominent role pharmacogenomics will play in moving drug development and therapy from a population-based to an individualized paradigm.

Recommendations
An ideal application of pharmacogenomics is to integrate it into clinical and nonclinical studies in order to provide value to pharmaceutical R&D by supplementing the information from these studies. The goal is to provide safer and more efficient medicines, combined with diagnostics, in order to meet the needs of patients.

An integrated, scientific-based approach is recommended, beginning at the non-clinical stage and continuing throughout clinical development phase, late phase and post-marketing studies. Data generated in late-phase development and in the postmarketing phases should be fed back into the discovery process to improve preclinical screening and the development of backup compounds. A decision on whether to continue clinical development with or without diagnostics should ideally be made at the end of Phase II.

Frost & Sullivan has a few key recommendations for companies setting up the pharmacogenomics infrastructure:

  • Develop stringent and regulated procedures to enable routine collection of samples in clinical trials. Informed consent forms and protocols which meet ethical and regulatory standards have to be developed.
  • Develop laboratory capabilities for adequate storage of biomolecules (DNA,RNA and proteins), tissues, biopsies and proper labeling of the same.

    Develop information handling capabilities for data management and mining for analysis and report generation.

  • Develop a pharmacogenomics strategy as part of a clinical development plan involving a multifunctional team – scientists, clinical pharmacologists, physicians, statistics/bioinformatics specialists, commercial/marketing experts, and regulatory affairs and diagnostic consultants. Such a diverse team would assess the feasibility and add value to the research in the clinical program.
  • Include pharmacogenomics as early as possible in the overall development program and examine the feasibility of linkage of the drug to a companion diagnostic as early as possible. Whenever a candidate gene approach is performed, evaluate its genome-wide effect.
  • Genetic variability analysis should be performed as soon as a marker is identified. Potential benefits of early analysis include avoiding targets with unmanageable variability and selecting the variant(s) that are most prevalent in human populations, thus improving the likelihood of success in clinical trials.
  • Early stage pharmacogenomics work is crucial. Pharmacogenomics initiatives will not have an impact on currently marketed products with more imminent patent expiry. This knowledge highlights the point that advanced and continued planning can be utilized to optimize the commercial impact of pharmacogenomics activities. As noted above, there are many potential commercial implications from pharmacogenomics approaches. One obvious opportunity to limit risk is to begin implementation of this work as early as possible in a product’s life cycle. To do so would facilitate rapid, more efficient development, with potentially quicker discontinuation of some development programs and salvaging of other compounds.

Conclusion
The challenges to drug development, commercialization, and reimbursement are increasing. Pharmacogenomics provides a novel area for product differentiation, competitive advantage, and enhancement of R&D productivity; and the pharmaceutical industry is learning how to best apply it in its R&D programs. Recent initiatives, such as the formation of several pharmacogenomics-focused consortia, new regulatory guidance documents, the introduction of legislative bills and high-profile safety concerns continue to illustrate the prominent role pharmacogenomics will play in moving drug development and therapy from a population-based to an individualized paradigm. Genetic markers will play a major role despite the challenges of identifying valid associations and of inherent biological complexity. Our capacity to experience future progress is limited only by our skepticism about partnering with other agencies, groups, and even competitors, in the coming decades.

Frost & Sullivan anticipates that fear of the loss of blockbusters, concerns about potential regulatory risks to drug development programs, and skepticism about the true value that pharmacogenomics will bring to the pharmaceutical industry are likely to fade away as organizations continue to gain experience in this field, and as the regulatory framework for this research continues to grow. Hence, research in pharmacogenomics deserves support and investments from all concerned parties, an earlier start would ensure higher returns.

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