Translational Medicine 2.0: From Clinical Diagnosis–Based to Molecular-Targeted Therapies in the Era of Globalization

S Albani1,2, J Colomb1,2 and B Prakken1,3

Translational medicine encompasses the itinerary from the conception of an idea to its implementation in the diagnosis, prognosis, and treatment of human diseases. It cannot be identified as a stand-alone field; rather, it comprises a fragmented patchwork of activities, competencies, and knowledge distributed along diverse and often disparate disciplines. In standard practice, the success of a translational project is often less dependent on the validity of the original idea than on the outcome of the combination of several stochastic events.

Fragmentation, inefficiency, and the lack of a cohesive and coherent process are the most significant hurdles that hinder the rate of success even of promising new technologies. Geographic boundaries have been just as tenuous, particularly so in this age of globalization. The solution to fragmentation relies on a unified vision that is recognized and implemented globally.

We must develop knowledge and tools based on an understanding of the process as a whole, foster the ability to chart and manage development plans, and most important, coalesce into a group with diverse professional competencies.


A multidimensional problem

The paradox of expanding knowledge. The ever-expanding pool of knowledge garnered from basic science has not efficiently translated into clinical products because of substantial disconnects that we and others have discussed elsewhere.1–4 This situation has worsened in recent years; it is similar to the evolution from Web 1.0 to Web 2.0 in digital communications. In the case of translational medicine, the speed of development has not been met by a corresponding change in the culture. Swift advances in basic science have stimulated a strong drive for specialization without the sufficient integration of high and low throughput in biomedical research. In the transition from candidate to lead drug, several bottlenecks are encountered along the increasing gradient of complexity, which ranges from molecules to cells to, ultimately, living organisms. The application of “omics” has also led to “disease fragmentation.” The availability of massive amounts of data could lead to the stratification of subcategories of patients who are diverse biologically but are still categorized under the same—now obsolete—clinical diagnosis. The outcome of this process is evident in clinical practice. For instance, the advent of biologics for the treatment of arthritis has provided effective tools for disease control. A sizable percentage of the patient population does not respond to one agent but may respond to another. This variation is due to genetic, epigenetic, and biologic differences, but, thus far, none of these considerations has been used to justify preference for such increasingly sophisticated therapies. Hence, the development of these treatments must be accompanied by corresponding sophistication applied to appropriate tools to classify patients and even predict responses to therapies.

Moreover, the application of new highthroughput technology to relatively simple clinical questions appears ineffective in some cases. As an example, a recent study predicting body length using a 54-loci genomic profile appeared inferior to a method that dates from the Victorian era (1886)—namely, using the average of the height of both parents.5

Thus, more data do not necessarily translate into more tangible, applicable outcomes, or even additional knowledge.


The quagmire of business and government. The industry pipeline has dried up considerably. Fewer—and progressively more complex—leads are generated from basic research, and the intricacies touched on above make it increasingly difficult to decide which leads have promise. Furthermore, specialization confounds decisionmaking processes in industry. Meanwhile,a lack of resources for manufacturing and toxicity studies limits the possibility of performing phase I studies in academia in order to identify new leads. Small biotech companies are hindered by private investment funds’ increasingly stringent requirements for product maturity.

Over the years, national and multinational laws have established a large set of protocols and rules to protect patients. These regulations have in some cases overshot their goal and led to a bloated bureaucracy, with its related costs. Legislation is often different, if not contradictory, from country to country, leading to further splintering, especially in the case of multinational research projects and product approval processes. Also, neither regulatory bodies nor regulations are adapted to the specific challenges of the novel targeted therapies currently under development. Moreover, regulators and industry alike have not reacted appropriately to the need to identify, validate, and use biomarkers to stratify patients by means other than traditional clinical diagnoses, and therefore therapeutic and developmental strategies have not been shaped accordingly.


Unraveling the conundrum. In the middle of all this stands the investigator trying to navigate the itinerary of translational medicine. The problem here is first and foremost one of knowledge. It is impractical and arguably impossible for an individual to be an expert in all aspects. To overcome these challenges, awareness of the general process in its entirety, particularly in an international setting, is necessary and dramatically lacking. This is not a novel problem: 30 years ago the clinical (read “translational”) researcher was already called “an endangered species.”1–4,6


A cost we can no longer afford. The list of failed translational research projects is vastly longer than that of successful developments. The setback for patient care is obvious, but failed projects also contribute to the dramatic increase in novel product development costs. In 2003, an extensive analysis by the Clinical Research Roundtable (CRR) at the Institute of Medicine pointed out the serious disconnect between “the promise of basic science and the delivery of better health,”7 which underscores the constant and in large part unchanging topography of the challenges. In that report, this massive translational block was referred to as a “national crisis and a call to action,” and it has yet to be fully and effectively addressed.


A global solution to fragmentation and regionalism

Development of knowledge specific to the translational process as a whole as well as to its components may contribute to the most effective solution, at both the individual and the institutional levels. First, knowledge must be made more accessible and applicable for those traversing the translational medicine itinerary. Next, industry, academia, and government need to adapt their customs and regulations on the basis of these new insights. Interfaces must be created to bridge fields; national and supranational inconsistencies and discrepancies need to be resolved. The active shaping of a global perspective in place of regionalisms will contribute to the smoothing of these disparities. Often, changes at a macro level are initiated and guided by individual champions.


Leverage knowledge and empower the individual. A novel professional figure is necessary to promote growth and facilitate cohesion within the translational research field (Table 1). This figure, typically at an early stage of his or her career, should not only be provided with the necessary theoretical notions but, first and foremost, also be exposed to the whole field of translational medicine in the context of a nurturing but realistic environment. Hence, the ideal training programs are those in which opportunities to develop theoretical awareness of the problems are blended with simulations of real-life situations and that may even offer opportunities to be mentored by experts in situ. From the start, an international setting will raise awareness of the complexity and diversity of the field and provide the necessary understanding of the need for globally effective rules, protocols, and approaches. Although this may seem to be a “generalist” approach in an era of increasing specialization, it is actually akin to the role of a music conductor. The conductor typically has neither written the music nor played each instrument, but he or she understands the movement of all the instruments together and dictates how the final piece is rendered.

Thus, trained translational researchers can help reshape the philosophy, attitudes, and procedures of the institutions where they will “seed.” They will also guide individual scientists in overcoming many of the hurdles. Their knowledge of the process will enable them to craft development plans for individual projects that are realistic, rational, and cohesive. Furthermore, trained translational scientists would be able to facilitate constructive communication between separate institutions—for example, between academia and industry, or even between different departments within the same institution. However, an effective training program is only one approach in a situation that requires a comprehensive and diverse set of solutions.


Table 1    Tools of the trade: scientists

Version 2.0: characteristics and skill sets Methods
– Evaluating productivity and scientific impact
– Knowledge of the field
– Sound research (bench work)
– Study design
– “Translational mindset”
– Engage venture capital sources, industry, small biotech firms
– Plan effectively (long-range)
– Critical-thinking skills to overcome challenges
– Protocol development
– Communication skills (various audiences and media)
– Networking and building effective teams
– Access to experts for development and protection
– Strategies and importance of intellectual property and patents
– Funding sources
– Knowledge of regulatory bodies and requirements
– Knowledge of patient and animal rights, understanding of university and regulatory body rules for protocol development and support, at regional and international levels
– Risk/benefit analysis
– Evaluate and assess viability of standard operating procedures and ability to strategically plan to optimize resources
– Training, through hands-on international fellowships and internships as well as specifically designed didactic and integrative seminars
– Multinational mentoring structures to support and develop young investigators (career planning)
– Providing at an institutional level interdisciplinary–transnational interaction and encouraging/rewarding such interactions
– Formation of translational medical research interfaces and access to them


Develop tools. Tools for translational researchers are lacking in academia. Substantial support, such as aid in conceiving and implementing a development plan, is rare.

We previously introduced the concept of a novel infrastructure with the ability to guide a translational researcher in moving a project forward—the translational medicine research interfaces (TMRIs). TMRIs would be transparent support infrastructures that bring together activities, departments, and units that are relevant to translational medicine within a given institution or region. The role of TMRIs would be to facilitate, identify, and develop medical advances from conception to clinical testing, with an emphasis on multidisciplinary approaches. TMRIs could engage all major stakeholders in policy development, help to revitalize old but still pertinent protocols, and develop new approaches in cases where old protocols are not applicable. On the academic side, TMRIs could be essential to overcoming chronic problems of “lost in translation.” Obvious examples include intellectual property (IP) development and protection, engaging scientists in developing their ideas beyond their comfort zones, providing guidance for policy development, and helping to realign priorities to serve both the institution and the individual. Regional TMRIs could also provide the critical mass needed to overcome current difficulties in raising capital for start-ups.

TMRIs would play a role that is substantially different from National Institutes of Health–funded initiatives in the United States such as the Clinical and Translational Science Awards (CTSAs), which are focused mainly on replacing General Clinical Research Center grants and provide much-needed support for clinical research and related activities. In the CTSA program, resources allocated toward nurturing an idea into a tangible lead often make up a small fraction of the whole. TMRIs are complementary and propaedeutic to the biotechnology incubators that are sprouting throughout the world. Indeed, these interfaces are meant to scout promising ideas and technologies as well as to chart and implement the successful transition of these technologies into a product pipeline that may feed incubators or individual startups, or even directly into pharmaceutical companies.


Table 2    Tools of the trade: forming a better future

Version 2.0: reshaping regulatory bodies and funding agencies Methods
The regulatory fields
– Inconsistencies reduced across international borders
– Protocols designed and optimized for efficacy over tradition
– Major stakeholders engaged up to the highest levels of decision making in all critical fields
– Rules for safety and clinical trial design examined and improved, especially for biomarker development and therapies stratified according to patient
– Government, academia, and industry interface to maximize potential and minimize loss
– Preclinical development is prioritized and funded
– “Grassroots” approach to creating change, starting with individuals from different regions and disciplines
– Shift in culture/attitude
– Formation of translational medical research interfaces at regional and transnationallevels
– Consensus conferences
– Government, industry, and venture capital earmark funding for preclinical work on promising ideas Involve translational scientists in model design of trials to exploit current knowledge, biomarkers
– Encourage regulators to be more active in guiding researchers to develop scientific plans
– Involve basic scientists in the development of intellectual property
– Compare, validate, and standardize protocols while involving scientists, regulators, and industry in the process


Evolve approaches, procedures, and attitudes. It is of great importance to smooth the transition of in silico and in vitro research to the bedside. New approaches in translating both the descriptive and functional “omics” data into real and tangible biomarkers that can be used as diagnostic and/or prognostic markers and as surrogate outcome measures in clinical trials are needed. This requires the development of a new culture within regulatory agencies (e.g., the US Food and Drug Administration and the European Medicines Agency) and industry (Table 2). A new culture would focus on novel translational pharmacokinetic/ pharmacodynamic (PK /PD) modeling that can couple in silico, in vitro, and in vivo preclinical data with relevant experimental models to advance the drug discovery process.2,8 This should facilitate the integration of findings derived from preclinical work into clinical application. The need for new experimental approaches for scaling PK/PD models derived from animal work to more accurately predict complex human responses must also be emphasized. In this respect, it is critical to combine future clinical studies with tailormade biomarker studies and to constructively evaluate the use of experimental models. For example, the use of humanized mouse models in immunological applications is arguably superior to performing toxicity studies in nonhuman primates. Another example may be provided by epigenetic studies, in which lack of response to a given treatment may be explained, and even predicted, by stratifying patients with functional genomic and immunomic characteristics rather than traditional clinical parameters.

In addition, an attitude shift is provided by initiatives such as the Critical Path, in which data on large cohorts of patients for drugs already in use or in the pipeline are revisited with more appropriate tools (e.g., novel technologies and knowledge), with the objective of facilitating a refocused and more effective use of therapies available or in development.9 Combined, the technological evolution and “second look” data analyses are inducing a fundamental shift in the way regulatory agencies and governments tackle the challenges of vast and fragmented knowledge. This applies in particular to the development and validation process for biomarkers and patient stratification as well as to the development and implementation of novel rules for product development and release of a new drug application.


The authors declared no conflict of interest.

© 2010 ASCPT

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