Translational medicine is the integrated application of innovative pharmacology tools, biomarkers, clinical methods, clinical technologies and study designs to improve disease understanding, confidence in human drug targets and increase confidence in drug candidates, understand the therapeutic index in humans, enhance cost-effective decision making in exploratory development and increase phase II success. Translational research is one of the most important activities of translational medicine as it supports predictions about probable drug activities across species and is especially important when compounds with unprecedented drug targets are brought to humans for the first time. Translational research has the potential to deliver many practical benefits for patients and justify the extensive investments placed by the private and public sector in biomedical research. Translational research encompasses a complexity of scientific, financial, ethical, regulatory, legislative and practical hurdles that need to be addressed at several levels to make the process efficient. Several have resisted the idea of supporting translational research because of its high costs and the fear that it may re-direct funds from other biomedical disciplines. Resistance also comes from those more familiar with traditional clinical research methods. In this review, we argue that translational research should be seen as enabled by ongoing efforts in basic and clinical research and not competing with them. Translational research provides the knowledge necessary to draw important conclusions from clinical testing regarding disease and the viability of novel drug mechanisms. Advancing translational research requires education and new sources of funding. This could be achieved through public and congressional education by a joint coalition of patients' advocacy groups, academia, drug regulatory agencies and industry.

TRANSLATIONAL RESEARCH CATALYSES OLD SUBSTRATES

We have previously summarized the fundamental concepts that define translational research as a discipline [1] (Table 1). It should be recognized that none of the goals encompassed by this definition are unique to translational research, since medical sciences have thrived in the past on the same premises under the umbrella of definitions such as pre-clinical research, clinical research, disease-targeted research, evidence-based research, etc. As biomedical research has become more complex, specialized and fragmented, the interests and necessary skills of laboratory researchers have diverged from those of clinical researchers, and the success of the clinician scientist, the individual with a foot in both camps, has become more challenging. This has opened up the demand for researchers with a different skill set, expertise in translational research. Thus the need to bridge this gap called upon several stakeholders to join forces under a unifying concept aimed at identifying ways to better translate basic biomedical achievements into practical benefit. Some feel that the term ‘translational research’ has been invented to re-direct funds and resources from other disciplines without providing any true conceptual novelty. Indeed, translational research is not claiming originality in all areas covered by biomedical research. Translational researchers may not invent new clinical technologies or make the important new discoveries about disease, but they will be able to apply these in a new kind of clinical research that tests hypotheses derived from knowledge gained in the laboratory and from animal models and use biomarkers that can be applied in the laboratory and across species. The traditional goals of biomedical research function as a substrate for the catalytic activity of translational research that, like an enzyme, is aimed at enhancing the efficiency rather than modifying the process. The secret to this catalytic reaction rests in the ability to integrate disciplines of increasing complexity by allowing a dialogue among the stakeholders, by identifying the hurdles that hamper this interaction and propose creative solutions.

Table 1
Goals and areas defining translational research

Adapted from Mankoff, S. P., Brander, C., Ferrone, S. and Marincola, F. M. (2004), J. Transl. Med. 2, 14, published by BioMed Central Ltd.

Goals
The establishment of guidelines for drug development of for the identification and validation of clinically relevant biomarkers.
Experimental non-human and non-clinical studies conducted with the intent of developing principles for discovery or new therapeutic strategies.
Clinical investigations which provide the biological foundation for the development of improved therapies.
Any clinical trial initiated in accordance with the above goals.
Basic science studies which define the biological effects of therapeutics in humans.
Goals
The establishment of guidelines for drug development of for the identification and validation of clinically relevant biomarkers.
Experimental non-human and non-clinical studies conducted with the intent of developing principles for discovery or new therapeutic strategies.
Clinical investigations which provide the biological foundation for the development of improved therapies.
Any clinical trial initiated in accordance with the above goals.
Basic science studies which define the biological effects of therapeutics in humans.

Animal models are an important source of information about the pharmacology of compounds and the relationship of novel drug targets to downstream outcomes (efficacy and safety). There are very few animal disease models that universally predict efficacy of drugs in humans regardless of the drug's mechanism of action. However, there are many disease models that have been found to predict efficacy of drugs with precedented mechanisms. Arthritis models are a good example. Rat adjuvant arthritis and carrageen-induced inflammation models are very good predictors of the response of humans with rheumatoid arthritis to cyclo-oxygenase inhibitors [NSAIDs (non-steroidal anti-inflammatory drugs)] and can be used to predict efficacious human doses of these drugs. However, these models also respond to mechanisms that have no efficacy in rheumatoid arthritis, such as LTB4 (leukotriene B4) receptor antagonists. Nevertheless, these models are good pharmacology models for LTB4 receptor antagonists, just not a useful disease model. They can be used to determine the amount of LTB4 antagonism that is needed to result in downstream outcomes, and this information can be translated to humans using biomarkers of LTB4 receptor blockade. Likewise, rodent tumour xenograft models are used to measure the activity of compounds for cancer, but activity in these models for many mechanisms does not predict efficacy in humans with cancer. Again, they are useful in determining the amount of activity a drug must have to translate into downstream outcomes. Thus animal models are valuable because they are good pharmacology models. We can use them to determine whether a novel mechanism of action will translate into downstream outcomes and translate biomarkers from these animal models to humans to measure the pharmacology in man. They become predictive of disease efficacy in humans only for specific drug mechanisms once efficacy in humans is confirmed.

DEFINITION

The question of how to define translational research remains unresolved and controversial. This is partly due to the fact that different stakeholders look at distinct aspects of this issue. For academia, translational research represents a general desire to test novel ideas generated from basic investigation with the hope of turning them into useful clinical applications. For academic purposes, translational research also responds to the need of identifying novel scientific hypotheses relevant to human pathology through direct observation of humans and their diseases [2]. For people more directly involved in clinical practice (physicians, clinical laboratory professionals and patients), translational research responds to the need to accelerate the capture of benefits of research, closing the gap between ‘what we know and what we practise’ [3]. This means the transfer of diagnostic and therapeutic advances proven effective in large well-conducted trials to daily medical practice [4]. For the commercial sector, translational research refers more to a process aimed at expediting the development of known entities particularly in early phases and/or identifying ways to make early go/no go decisions when the cost of product development is still relatively contained. These concepts are not mutually exclusive and can overlap, although naturally there are often differences in priorities between translational researchers with different goals and different definitions of success. In spite of these practical differences, a generalized definition of translational research could be proposed that should unify the expectations of all involved including the ultimate beneficiaries: the patients. We, therefore, propose a simplified definition of translational research as follows: translational research (or translational medicine) represents a discipline that increases the efficiency of determining the relevance of novel discoveries in the biological sciences to human disease and helps clinical researchers identify, through direct human observation, alternative hypotheses relevant to human disease. A further goal is to accelerate the rational transfer of new insights and knowledge into clinical practice for improving patients' outcomes and public health [5]. To be successful, translational researchers need to identify scientific, financial, ethical, regulatory, legislative and operational hurdles and provide creative solutions to facilitate this process.

LACK OF SUFFICIENT FUNDING

As discussed above, lack of funding pertains mainly to academia. In 2003, approx. US$94 billion was spent on biomedical research [21]. Contrary to common belief, the majority of the spending was sustained by the private sector with the inclusion of pharmaceutical companies, biotechnology start-ups and firms developing medical devices, which accounted for approx. 60% of the total research and development spending (approx. US$ 55 billion). Federal, state and other public agencies contributed less than 40%, with approx. 3% contributed by private non-for-profit enterprises. These proportions have remained constant for the last two decades. The NIH (National Institutes of Health) contributed the biggest proportion of public support for biomedical research (approx. 28% of the total spending); however, the NIH supports predominantly basic research, whereas the 58% contributed by industry more closely relates to translational research, because it seeks the development and testing of biomedical products. Thus the overwhelming amount of resources spent in support of translational research comes from the private sector, whereas only a small proportion (less than 1%, as discussed later) is contributed by the public sector [21]. Because the goals and priorities of industry are different from publicly funded academic discovery, the extensive private resources cannot compensate for the lack of public support for some types of translational research. For instance, population studies for the understanding of disease patterns that may identify novel relevant targets of therapy are not supported by the commercial sector, because the breath of this kind of research is too broad and the expected returns too slow [24]. In addition, even in the area of drug development, translational research for orphan diseases receives relatively little support from both the private and public sectors, because they do not affect a substantial portion of the population supporting the costs of research and because of the limited market for therapeutic products. Publicly sponsored academic research is generally more openly interested in innovation whereas, for financial reasons, the private sector is constrained to conservative choices efficiently narrowing research prospects to those likely to identify successful agents through proof-of-principle studies at the preclinical-to-clinical interface and/or early phase go/no go decisions. It is unclear how these discrepancies can be bridged, but the guiding principle should be that commercial and academic research are not competitors, they are interdependent and complementary and their interactions should be encouraged. This is especially true when one considers the educational mission of academic medical centres. Industry has an unmet need for researchers with the academic background and clinical training necessary to become skilled at translational research. Pharmaceutical companies have the incentive and the financial resources to do translational research, but often lack the human resources with the right skills. This represents one opportunity for the academic sector to benefit from investments in translational research if they can also be used to train translational research clinicians.

The NIH has recognized the need to improve the efficiency with which innovative thinking emerging from the basic sciences could be tested for its clinical applicability unburdened by excessive financial considerations. The NIH Road Map represents a good example of this interest (http://nihroadmap.nih.gov). However, it should be recognized that this initiative has mainly a conceptual value, since the amount of resources allocated for it are minuscule compared with the overall NIH budget. For instance, in 2004, US$28 million were allocated to support translational aspects of research through the Road Map, which represents a little more than 0.1% of the whole NIH budget. With a decreased NIH budget (−2% projected for the 2007 fiscal year adjusted for inflation [25]), it is unrealistic for the foreseeable future to expect that such allocation, predicated on voluntary yearly contributions from 27 NIH Institutes and Centres, will significantly increase [25]. It should be emphasized that incremental funding for translational research must be sought beyond the current NIH budget, because translational research should not compete with basic sciences which have been the foundation of American leadership in natural sciences. Besides, the interpretation of translational research results heavily depends upon novel scientific insights that can only be achieved by a bidirectional dialogue with bench scientists [2]. At present, there are no good options to improve the allocation of public resources to translational research. The following strategies could be considered: (i) optimize academia–industry partnership, where academia delivers trained researchers skilled in translational research and industry helps to sponsor those programmes; (ii) consider alternative sources; (iii) decrease the cost of clinical investigation by decreasing unnecessary burdens and increasing its effectiveness; and (iv) increase public support for biomedical research spending. We will discuss later the need to increase public support for biomedical research, as this pertains to broader aspects of translational research, and we will focus here on two solutions specifically addressing insufficient funding. ALTERNATIVE SOURCES OF FUNDING Optimize academia–industry partnership As discussed above, the commercial sector has significant resources and incentives to translate emerging biological concepts into products at a scale beyond the capabilities of the public sector. The funding and, most importantly, the infrastructure necessary to move a drug through the initial proof-of-principle (preclinical testing followed by phase I/II trials) to the approval for marketability is huge, reaching approx. US$ 1 billion. Thus there is no reason to utilize public funding for product development. Indeed, it may be almost impossible for academics to procure sufficient competitive grants to bring a drug or a test to the clinic in compliance with all the testing necessary to meet regulatory requirements. Seeking financial resources from industry by academic institutions beyond those publicly provided through venture capital and educational programmes could generate financial and ethical conflicts of interest and may limit product development further [11]. Thus there are many reasons why academia in isolation should not focus on the type of translational research associated with drug development. Large biopharmaceutical companies are, instead, equipped with staff and resources to address and meet the administrative and regulatory requirements necessary to develop, test and bring a product to market. Few academic institutions are capable of providing a core infrastructure with appropriate and professional regulatory support. When they do, it is often limited and provided on a voluntary basis (i.e. institutional review boards). In addition, facilities necessary to meet the standards for clinical product preparation are not always available or compliant with changing regulatory requirements. Thus taxpayers' money should be saved for the continued enhancement of biological understanding relevant to human disease. However, participation in drug development by translational research experts in academia in partnership with the private sector is attractive to both sides. The cost of product development can be transferred to the private enterprise by providing incentives for academic and private partnership, while industry benefits from the translational research expertise of academia [11].

Another area for academic–industry collaboration is the education of experts in translational research. One example of this is the Clinical Investigator Training Program at Harvard and Massachusetts Institute of Technology sponsored by Pfizer and Merck (http://www.hms.harvard.edu/gradprograms/citp.html). In this example, industry experts help train fellows enrolled in the programme and contribute financial resources to pay fellows' salaries and for programme infrastructure. The fellows work on translational research projects under the mentorship of the Harvard and Massachusetts Institute of Technology faculty and receive a Masters degree in clinical research from Harvard after completing the 2-year classroom curriculum and their research projects. In this type of programme, industry is contributing directly to translational research activities and also training future independent researchers.

DECREASING THE COST OF TRANSLATIONAL RESEARCH BY INCREASING ITS EFFICIENCY

Identifying and validating surrogate markers for early go/no go decisions

The rate at which potential therapeutic targets are identified by modern biotechnology has increased the competition in industry for resources to test the efficacy of multiple drugs and mechanisms for the treatment of the same condition. Many new drug candidates target reduction in the progression of chronic diseases that require long and expensive clinical trials. The biggest cost of bringing a new drug to market is incurred in late-phase clinical trials [33]. This makes the need for identification of relevant biomarkers that can predict treatment safety, efficacy and differentiation before investing in large clinical trials all the greater. For this reason, surrogate biomarkers that substitute for standard clinical end points, such as X-ray measurements of joint damage, functional status, survival, disease-free survival and/or symptom-free interval, are of increasing interest [35], therefore, dramatically shortening the time necessary for critical go/no go decisions in early phase development [3335]. This is particularly relevant because the diseases that most impact U.S. health care spending are chronic and clinical benefit may take several years to decades to be judged in clinical terms [28,29]. Ultimately, the identification and validation of useful biomarkers will serve two purposes: (i) to allow researches to make informed early decisions on the likelihood that a novel idea may turn into a useful and profitable product and, therefore, decrease the cost of late phase testing of an ineffective agent; and (ii) to be used as surrogate for treatment approval by regulatory agencies, therefore, decreasing the lag between product development and marketability. In addition to surrogate end points in phase II studies, biomarkers are also critical earlier in development if they can be used as pharmacodynamic end points that confirm the activity of compounds at safe doses and for PK/PD (pharmacokinetic/pharmacodynamic) modelling for dose and dose regimen selection. Failure to achieve efficacy in phase II with a compound that has its intended pharmacology can disprove the efficacy hypothesis for unprecedented drug targets.

Since biomarkers inform programme and compound go/no go decisions, and serve to help optimize biological dose in terms of safety and efficacy [7], criteria are needed to identify clinically useful markers, to assess the best methodology for clinical evaluation and to establish criteria to appraise the incremental value offered over standard prognostic factors [36]. Single or combined biomarkers can also inform patient stratification by identifying probable responders to therapy [35], a goal exemplified by the National Cancer Institute-sponsored PACCT (Program for the Assessment of Clinical Cancer Tests) [37].

The biological relevance of a biomarker may be distinct from its clinical relevance. The goal of active-specific immunization against cancer is to expand the T-cell repertoire in favour of cancer-specific T-cells (a biological end point). In fact, active-specific immunization is one of the great success stories of the application of modern biotechnology to the identification of novel therapeutic targets [38]. The induction of cancer-specific T-cells detectable in the circulation may not in itself be sufficient to induce cancer regression (a therapeutic end point). Thus, although the treatment is perfectly effective for its intended purpose, additional steps are necessary to achieve the desired therapeutic goal [39]. This is a critical point because often the promise held by a therapeutic modality is standard to high (therapeutic end point), leading to premature dismissal by decreasing funding for further development rather than continuing its sponsorship with the purpose of identifying biological factors that may link a successful biological end point to therapeutic success [40].

Validation of relevant surrogated biomarkers suffers several hurdles, such as underpowered studies, heterogeneous practices in measurement methodology, sample collection and processing, and incompatible data management systems. All of these problems could be solved by refinement and standardization of assays, evaluation of biological variability, quality control procedures, clinical methods of measurement such as imaging methods, and re-organization of data collections [37]. The importance of identifying biomarkers is, therefore, critical and central to translational research because, ultimately, it may turn out to be the most effective way to reduce the cost of clinical experimentations while, most importantly, saving patients from ineffective and unnecessary treatments promptly redirecting them to treatments with higher likelihood of success.

Opportunities for target identification and for the study of therapeutic mechanisms in the clinic

Modern technology offers unprecedented opportunities in the clinical sciences [41]. High-throughput technologies enable researchers to study human disease in its globality, accounting for genetic variability of individual patients and the epigenetic instability of their diseases. Samples obtained through venipuncture, fine needle aspiration, cut needle biopsies and cytological smears can be studied using DNA- and RNA-amplification techniques and high-sensitivity proteomic tools. Extensive analysis of an individual polymorphism could complement information related to the disease process at the genetic, functional and post-translational level. Genome-wide analysis is easy and requires only small samples for the preparation of genomic DNA. As these new frontiers in science emerge, a unified science curriculum that fully incorporates mathematics education and quantitative thinking has been proposed to prepare the 21st century scientists for the challenge of the study of systems biology [42].

Although it is relatively easy to analyse genomic DNA [43], collection of material for functional genomic studies requires more planning of the optimal time frame for sample collection (before, during or after treatment) and is limited by the amount of material realistically obtainable from patients. Analysis of tissues affected by the disease process and targeted by therapy is difficult because it requires repeated biopsies. Yet, less invasive methods, such as serial fine needle aspirates, can be used to predict response [44] or to study mechanisms of action [45] using high-fidelity RNA-amplification methods [46]. But such strategies are rarely employed. Transcriptional analysis should be complemented by documentation of epigenetic adaptations or genetic alterations. Comparative genome hybridization covers large genomic areas to detect deletion or amplification, while CpG island methylation arrays can investigate epigenetic regulation of gene expression if material for DNA extraction from affected tissues is saved during a clinical trial [47].

Protein analysis completes the picture, as protein function is modulated through post-translational changes and protein–protein interaction. For instance, the introduction of protein arrays dramatically expanded our understanding of alterations induced by the systemic administration of high-dose IL-2 (interleukin-2) to cancer patients [48]. Prospective collection of serum samples during therapy may help to identify patterns responsible for treatment toxicity and/or effectiveness. Application of standard practice for protein preservation using protease inhibitors and storage into appropriate aliquots are simple steps to ensure the usability of prospective collections.

High-throughput technologies have revolutionized the ability to understand human pathology by computing thousands of factors simultaneously, limiting the inherent barriers to controlling variables in human disease. However, samples collected retrospectively are often unusable for analysis, as RNA degrades quickly after tissues or fluids are removed from the organism. The opportunity to take specific steps to preserve the ex vivo profile is often lost unless researchers know early that the sample in question would be useful for a particular clinical study. Prospective collections are possible but require full co-operation between scientists and clinicians. Good examples of broad-based efforts are starting to emerge [49]. Legislative and regulatory limitations, such as material transfer restrictions and HIPAA (Health Insurance Portability and Accountability Act), severely limit the utilization, interpretation and correlation of biological data with clinical data [33]. The unintended consequences of such legislation should be addressed rather than passively accepted by the scientific community.

Providing the appropriate infrastructure

The current organization in which academic research is performed is not suited to the efficient conduct of translational research, as different disciplines are separate from each other administratively, physically and culturally [15]. Thus the present academic system represents a ‘professional bureaucracy’ that relies on the standardization of skills [50], providing a common infrastructure to respond to unified needs, but does not promote interaction across disciplines. The need for such interaction in translational research is better met by a ‘project structure’ (termed an ‘ad-hocracy’) that draws upon the talents of experts representing different specialties to create smoothly functioning creative teams [50]. Translational research units should not be assembled according to similarity of scientific background, but around a mission-based goal. This congregation of talents can only be achieved by unifying not only goals on a voluntary basis through the commonly accepted concept of ‘collaboration’, but rather through a solid structure in which each team member belongs to the same unit at the physical and administrative level and, most importantly, is rewarded according to the same review process. This should increase the cost effectiveness of designing and running clinical trials from the primary conception, the pre-clinical and/or experimental proof-of-principle, the trial design, through the regulatory approval process, the clinical testing and data collection, management and analysis.

Rewarding translational researchers

Translation research requires different skills applied to a unified goal [11]. Translational researchers need special training in the complexity of novel technologies and they need to be sensitized to the complications of designing and conducting scientifically valid clinical trials while understanding the ethical limitations of research when dealing with human subjects. Considerations include the identification of informative control populations that are not denied appropriate treatment, understanding the demographics of a disease and the alternative therapies that may influence trial design, and understanding the ethical dilemma imposed by repeated sampling of lesions for research purposes. There are few dually trained clinician scientists because their training requires 3–5 more years than the training of physicians in clinical practice and that of basic researchers [9,51,52]. In addition, medical school debts range around US\$ 100000 and cannot be promptly repaid during the incremental years required for research training. As noted above, there are opportunities for industry–academic collaboration in this area with important benefits to both parties.

The incentive to perform clinical research is also limited. Basic science studies are often valued more than clinical research in the promotion scale, ultimately providing little incentive to chose a career in translational research. In particular, scientific achievement is judged more on the basis of basic experimental testing of hypotheses rather than on hypothesis-generating terms (Figure 1). This paradigm does not apply to translational efforts as, in most cases, hypotheses generated from experimental models do not apply to human disease, due to the biased selection of a model in which experimental variance is minimized by limiting the genetic diversity of animals and their diseases. Bench-to-bedside efforts predominantly test the relevance to human pathology of hypotheses derived through experimentation and pre-clinical proof-of-principle. However, as experimental variance cannot be limited in human beings, such exercises often prove futile while novel hypotheses need to be generated through direct observation of human disease throughout their natural course or during therapy. However, hypothesis-generating studies are often and, unfortunately, classified as ‘descriptive’ and are not given the weight that they deserve in redefining the boundaries of biomedical research within the limits of human relevance [2]. This, in turn, discourages this line of research due to the difficulties encountered in publishing human-derived observations in high-impact journals. Finally, the present system of career advancement in science rewards the individual independent investigator, inadvertently discouraging team projects. This creates a conflict between the reward structure of academic institutions and the results that are actually expected of translational researchers [16]. Career structures need to be re-organized, credit for achievements should be shared among scientists and clinicians and, more grants should value teams of investigators. The NIH Road Map is attempting to foster this principle, but much still needs to be done to change the framework of rewarding systems in the academic environment.

How hypothesis testing is irrelevant to translational research

Figure 1
How hypothesis testing is irrelevant to translational research

Hypothesis testing has been utilized by scientists to verify the validity of a given hypothesis. The process involves minimization of the experimental variables (ideally to one) by homogenizing the experimental model through control of the genetic make up of test animals and standardization of their diseases. This strategy has proven extremely effective in the conduct of proof-of-principle studies to support or disqualify a given hypothesis. Unfortunately, this strategy is not intended and cannot identify novel hypothesis or predict their relevance to systems other than the one studied such as, in the present case, human pathology. This explains why when novel therapeutics are tested for their relevance in humans they almost infallibly fail. Novel technologies based on high-throughput genomic and proteomic assays allow an effective search for novel hypotheses relevant to human disease by taking a global view of the phenomena associated with a disease and its response to therapy. This approach turns the experimental heterogeneity associated with the uncontrollable genetic variability of humans and their diseases in its own favour, sorting common patterns necessary for the occurrence of a biological phenomenon from irrelevant ones. Hypotheses thus generated can then be taken back to the bench for testing according to standard experimental models. Unfortunately, this aspect of biomedical research has not received the appropriate recognition by the current biomedical establishment and this lack of appreciation represents one of the major hurdles faced by scientists interested in clinical sciences.

Figure 1
How hypothesis testing is irrelevant to translational research

Hypothesis testing has been utilized by scientists to verify the validity of a given hypothesis. The process involves minimization of the experimental variables (ideally to one) by homogenizing the experimental model through control of the genetic make up of test animals and standardization of their diseases. This strategy has proven extremely effective in the conduct of proof-of-principle studies to support or disqualify a given hypothesis. Unfortunately, this strategy is not intended and cannot identify novel hypothesis or predict their relevance to systems other than the one studied such as, in the present case, human pathology. This explains why when novel therapeutics are tested for their relevance in humans they almost infallibly fail. Novel technologies based on high-throughput genomic and proteomic assays allow an effective search for novel hypotheses relevant to human disease by taking a global view of the phenomena associated with a disease and its response to therapy. This approach turns the experimental heterogeneity associated with the uncontrollable genetic variability of humans and their diseases in its own favour, sorting common patterns necessary for the occurrence of a biological phenomenon from irrelevant ones. Hypotheses thus generated can then be taken back to the bench for testing according to standard experimental models. Unfortunately, this aspect of biomedical research has not received the appropriate recognition by the current biomedical establishment and this lack of appreciation represents one of the major hurdles faced by scientists interested in clinical sciences.

Several initiatives are focusing on the development of scientific training programmes for clinicians [24,41,42,51,52]. The purpose of these initiatives is not to increase the number of individuals who are fully trained in multiple disciplines, but who know enough about the fields of others so that they can communicate effectively. Definitely more needs to be done in this regard.

INCREASING PUBLIC SUPPORT FOR BIOMEDICAL RESEARCH SPENDING: A PROPOSAL FOR AN ASSOCIATION FOR TRANSLATIONAL MEDICINE INCLUSIVE OF ACADEMIA, INDUSTRY AND PATIENTS' ADVOCATES

In the discussion above, we summarized several of the key problems faced by translational medicine. Several of these problems cannot be readily solved without the participation and support of the public [18]. In many ways, it could be said that biomedical scientists themselves have been part of the problem by isolating themselves from public discourse. In addition, the biomedical community has not been effective in advocating the need for further investment in biomedical sciences. This resulted in a reshuffling by the current administration of funds for research and development to promote physical sciences and engineering at the cost of biomedical research [53].

Public understanding and appreciation of biomedical sciences, and their intellectual, financial and practical potential, will be key to solving most of the problems discussed above. Surveys suggest that public attitudes and perceptions about health-related research are positive [54]; however, this optimism does not seem to translate into sufficient public pressure on legislators to significantly affect budgetary allocations [25].

On the occasion of the 2nd Annual Meeting for Translational Medicine (http://www.healthtech.com/2006/ddd/index.asp) held recently in Philadelphia on 28 February–1 March 2006, a proposal was made to form an Association for Translational Medicine inclusive of academia, industry and patients' advocacy groups. This suggestion was followed by enthusiastic positive feedback from individuals associated with all of these constituencies who understand the importance of representing the issues related to translational research from a unified viewpoint. Such an association would provide: (i) an open collaborative membership association and forum for translational research professionals, supporters and sponsors, including academic, industry, advocacy and government organizations, (ii) a virtual community encouraging translational research collaboration, dialogue and partnerships which will benefit all constituents, (iii) a process for organized focused advocacy, (iv) education for new investigators and seasoned researchers, (v) a process to enhance translational research and medicine by leveraging translational research innovations and scientific findings, (vi) a vehicle to promote and publicize member contributions to society by offering active support, (vii) guidelines for translational research standards, applications and implementation, and (viii) professional meetings and publications.

Although organizations exist that represent individual aspects of translational research, they often clash with each other. Discussion over divergent opinions and priorities should be facilitated internally among all the stakeholders to present a unified front to the public, legislators and regulatory agencies as we all share the ultimate goal of helping patients in the near future.

Abbreviations

• FDA

•
• LTB4

leukotriene B4

•
• NCE

new chemical entity

•
• NIH

National Institutes of Health

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