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Jill Wechsler is Pharmaceutical Technology Europe's Washington Editor, email@example.com.
The US Food and Drug Administration is working with manufacturers to establish new policies for incorporating genomic information into the regulatory process and simultaneously encourage pharmacogenomic research.
In April, scientists worldwide celebrated the 50th anniversary of the discovery of the double helix by announcing the successful completion of the Human Genome Project (HGP). As they unveiled the nearly finished version of the human genome sequence, leaders of this landmark project outlined plans for tackling the next stage: translating genomic research into medical treatments to improve public health. This will involve identifying variations in DNA sequences that contribute to disease and defining how the proteins produced by each gene control cellular operation.
Turning the genomics vision into reality
HGP accomplished a great deal beyond producing a 99.9% accurate sequence. It mapped the genome of comparative organisms (rat and mouse) and developed new technologies that will facilitate further exploration and development. The project identified more than 1400 disease genes and studied the ethical, legal and social issues raised by expanded knowledge regarding human genetic make-up. The next stage of utilizing genome-based discoveries in product development will involve pharmaceutical manufacturers more directly and will require the US Food and Drug Administration (FDA) and other government agencies to address pertinent regulatory and legal issues.
In marking the completion of HGP's stated task, Francis Collins, director of the National Human Genome Research Institute (NHGRI) at the National Institutes of Health (NIH), declared it was time to move from large-scale DNA sequencing to more specific research projects. Collins and other HGP leaders outlined new research and development (R&D) opportunities in a recent article.1 This blueprint for future genomics research describes the resources and technological developments critical to developing "powerful new therapeutic approaches to disease" (see sidebar "Turning the genomics vision into reality").
An ongoing issue is the need to balance timely access to new discoveries with protection of intellectual property (IP). Without an understanding of how complex patent and licensing policies influence private sector investment in new technologies, many diagnostic and therapeutic advances based on genomics may never reach the clinical setting where they can benefit patients (see sidebar "Patent protection and public access to data").
Patent protection and public access to data
A major concern for manufacturers is that gathering more genomic data will affect policies governing the testing and approval of new drugs and medical products. Industry is already investing more resources in pharmacogenomics (PG) to better understand how and why individuals respond differently to pharmaceuticals, a key issue in identifying candidate compounds and in testing them for safety and efficacy. This information promises to streamline animal and human studies by
Such analyses have the potential to revolutionize drug development processes and lead to the production of more effective, less toxic drugs more quickly and efficiently, commented Janet Woodcock, director of FDA's Center for Drug Evaluation and Research (CDER), during the April meeting of FDA's Science Board. However, FDA officials are concerned that companies are not presenting PG analysis to the agency because of fears that it may lead to requests for even more data and tests, and further delay new product approvals. Woodcock wants to clarify FDA regulatory policies to encourage PG analysis and to gain access to information that could advance scientific discovery.
In a sense, this concern among manufacturers that innovative research will complicate product regulation is similar to the "don't use" and "don't tell" attitude hindering industry adoption of new manufacturing technologies. Manufacturers worry that installing new online methods to control pharmaceutical production and drug quality will raise additional questions from plant inspectors and FDA staffers who review chemistry, manufacturing and controls data. To overcome these obstacles, FDA has launched the Process Analytical Technology (PAT) initiative, which aims to encourage manufacturers to install more efficient production systems, which are able to reduce costs and better ensure product quality.
Similarly, Woodcock seeks to develop several PG guidances to clarify agency approaches for using PG information. The aim is to overcome industry reluctance to disclose data from exploratory PG studies used by researchers to identify target compounds and to evaluate cellular and animal responses to drug candidates. The guidances will address
The first step will be to develop "concept papers" regarding these topics, followed by draft and final guidances, which FDA hopes to issue by the end of 2004.
One of the main goals is to distinguish between PG data that may affect product regulation and should be submitted to FDA, and data that will not be required in filings for investigational new drugs (INDs) and new drug applications (NDAs). One "threshold" for submission might be genomic information that represents a valid biomarker with known predictive characteristics. FDA is likely to request that certain PG information be filed in applications, such as
Alternatively, FDA wants to define a "research information package" that manufacturers would share with FDA, but would not have any impact on application review. Such data would be discussed separately by a new Interdisciplinary Pharmacogenomic Review Group (IPGRG), composed of representatives from all FDA Centers. Data collected for "research use" that would not affect regulatory and approval decisions might include
Woodcock anticipates plenty of public discussion of PG issues through the guidance development process, beginning with a public workshop this autumn. Manufacturers are already expressing concerns regarding new FDA rules in this area. Brian Spear, director of pharmacogenomics at Abbott Laboratories, told the Science Board that most pharmaceutical companies are exploring how PG analysis may help design clinical trials and interpret study data. Gene expression studies can predict toxicity of candidate compounds and identify biomarkers for toxicity and drug response. Analysing patient genotypes may help define study populations and avoid overloading trials with inappropriate patients. Although such approaches may reduce potential patient injury and make studies safer, they may also be challenged as attempts to merely improve study results. A prime objective is to establish superior methods for validating conclusions derived from modern microarray and genomic analysis, which industry fears could be misinterpreted by regulatory officials.
Spear supported FDA's idea of establishing a central PG review group of experts to review PG studies separate from the review process, but emphasized the need for clearer definitions of "pharmacogenomic data" and "research exemption." Without a more explicit policy, manufacturers will worry that FDA and other regulatory authorities could expand requirements later for what studies and data analysis they require for product registration. And whereas clarification of research approaches may appear useful, increased standardization also carries the risk of encouraging both regulators and manufacturers to favour certain procedures, which may inhibit innovation in the long run.
Another manufacturing concern is that PG data could be used to narrow product marketing opportunities. A genetic study showing, for example, that 30% of patients could fail to respond to a certain treatment may lead to restrictive product labelling, even if the drug appears safe and effective for a general population. Or, data indicating that certain patients respond to a treatment might lead to required diagnostic testing of participants in clinical trials and of potential patients. In the end, industry willingness to underwrite more PG studies may prompt FDA to require genetic analysis as a regular component of drug development programmes.
These are difficult issues, and FDA is building its internal capacity and expertise for analysing and understanding genomic data, explained Frank Sistare, acting director of CDER's Office of Testing and Research. CDER has established an internal Non-clinical Pharmacogenomics subcommittee and is expanding reviewer training in this area. The panel will help develop standards for submission, review and integration of PG data, and will also work with other government agencies and international scientists to further develop these initiatives. FDA is seeking input from advisory committees and experts concerning ways to better understand and assess relevant information as genomics discoveries evolve.
The task of clarifying FDA regulatory policies related to PG is an important challenge for FDA commissioner Mark McClellan. A key strategy for improving public health is to make more new cost-effective therapies available to those patients who can benefit most from them, McClellan told industry leaders during the March annual meeting of the Pharmaceutical Research and Manufacturers of America. To this end, FDA is undertaking a "concerted effort" to use PG information effectively, he said, but needs more help from industry to better understand the issues and make FDA's regulatory process more efficient.
McClellan made similar remarks during the April Science Board meeting, calling for action to integrate genomics information into product development and medical practice. He acknowledged that drug developers fear that data from molecular genomics doesn't "fit" the regulatory process and may "raise red flags" with reviewers. But he urged industry to share results with FDA so that these issues can be discussed openly and collaboratively.
1. F. Collins et al., "A Vision for the Future of Genomics Research," Nature 422(6934), 835–847 (2003).
2. F. Collins, M. Morgan and A. Patrinos, "The Human Genome Project: Lessons from Large-Scale Biology," Science 300(5617), 286–290 (2003).