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This month, IBC's annual Drug Discovery Technology conference celebrates its ten-year anniversary. Back in 1995, the conference launched in the midst of a wave of exciting technological developments — advances in combinatorial chemistry and genomics, and the beginning of an era of automation and miniaturization that revolutionized early-stage drug discovery. The programme for 2005 is somewhat different, with much of the conference devoted to managing the transition from discovery into clinical trials. In the early 1990s, most drugs failed in clinical trials because of poor pharmacokinetics. Now, most attrition occurs later in costly large-scale trials because of lack of efficacy.

Clearly, one part of the problem is poorly predictive animal models, particularly for some disease areas and drug classes with a novel mechanism of action, a topic we continue to cover in our ongoing 'Model Organisms' series. But arguably the best 'models' for drug discovery are human subjects and as the need to have proof of concept or mechanism for a drug before moving on to larger, more costly clinical trials has never been greater, more big-pharma companies are now embarking on programmes in experimental or translational medicine.

On page 631, Bruce Littman and Stephen Williams describe how experimental medicine, defined in this context as the use of innovative measurements, models and study designs to establish proof of concept and/or mechanism for a drug in human subjects, is reshaping the R&D process at Pfizer, and advocate humans as the 'ultimate model organism'. However, such a 'model' is only useful if the measurements it provides are accurate, sensitive, specific and, above all, meaningful. But what is meaningful to some (for example, big pharma) is not necessarily meaningful to others (regulators, for instance). And with some exceptions — positron emission tomography, for example — there are very few tools or biomarkers that currently fit these criteria and are validated or mature enough to be adopted by big pharma and/or accepted by regulatory authorities.

As with the development of a drug, the identification and validation of tools and biomarkers takes time, costs money and has an element of risk. This means that for big pharma there is little scope or incentive for undertaking this type of exploratory research if one can use an existing biomarker or form a strategic collaboration instead.

Academia and small biotechnology firms have long provided tools that big pharma scales up for its own use, particularly for areas in which technology has been a rate-limiting step. Why not extend this collaboration to clinical development? In addition to working together in clinical research, a topic addressed by Garret FitzGerald in an upcoming Perspective article, collaboration on technology development is crucial if big pharma is to implement biomarkers and other tools in experimental medicine.

This view is certainly shared by those involved in the Alzheimer's Disease Neuroimaging Initiative (ADNI), a public–private consortium set up to tackle the issue of validation of neurological imaging tools. The ADNI is an exemplar of what can be done through a combination of government and industrial funding, and the sharing of data and methods between different research communities (see p616 in News and Analysis). However, although this shows a willingness to cooperate, a recent US Supreme Court ruling that broadens the definition of 'safe harbour' has created uncertainty for research tool companies, which many lawyers worry could lead to less investment, less research and, ultimately, fewer new research tools for big-pharma companies (see News and Analysis, July 2005). Littman and Williams acknowledge that biomarker technology development will be incremental and will require long-term collaboration between academia, small biotechs and big pharma — something for the pharmaceutical industry and the lower courts to keep in mind.

But there is reason to see the ADNI as an encouraging sign of things to come. Academia and the pharmaceutical industry increasingly recognize the need to work together on translational research, and the NIH Roadmap initiative and the FDA's eagerness to assist with discussion about biomarkers and other measurements outlined in its Critical Path report provide an unprecedented opportunity to do just this. It seems there really is no better time than now to turn the potential of translational research into reality.