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Biomarkers in Personalised Medicine

Precompetitive Partnerships

Biomarkers still hold promise as industry faces challenging barriers in bringing new products to market, and while this promise has not yet been fully realised, the scientific and clinical rationale remains persuasive.

Precompetitive collaborative research initiatives like the Biomarkers Consortium, which includes public and private participation, share the cost and risk associated with biomarker discovery, development and qualification. Multistakeholder partnerships leverage individual stakeholder resources, while maintaining profitable scientific and monetary returns on investment. The precompetitive consortium model provides a new and important business model for drug discovery and development as well as for biomarker research.

It is clear that past models of drug development no longer support large scale research and development (R&D) efforts, and biomarker research is not likely to succeed under this schema (1-4). The progression of medical practice towards a more personalised medicine has altered drug development by providing new opportunities for developing targeted treatments and stratifying patients to maximise the benefit of treatments while decreasing safety risks.With that opportunity, however, comes the need for better tools, clinical trial designs and analytics.

The initial enthusiasm surrounding biomarkers for a wide range of purposes, such as to screen patients for disease susceptibility, identify novel drug targets, stratify molecular sub-populations of patients in order to predict drug efficacy and toxicity, has faded over the past several years (5-7).The decreasing enthusiasm derives from a growing sense that biomarkers have failed to deliver on their promise to the drug development industry. While the challenges cannot be overlooked, a new research paradigm may capture the promise and deliver the benefits of biomarker-driven development and clinical decision-making. One such emerging mechanism is the precompetitive consortium model.

Defining Precompetitive Collaborations

Precompetitive activities have been defined in several ways:“pertaining to the time during research and development in which there is collaboration but no competition” (8) or “open collaborations between companies that usually are intellectual property (IP) competitors” (9) or “early stages of research that benefit all [stakeholders]” (10).Webster’s Dictionary defines the term precompetitive research and development as “non-competitive, cooperative research and development which leads the way to full scale competitive development in the future by addressing key requirements of new technology for the low-cost realisation of IBC [Independent Business Concern] equipments and services” (10).

Regardless of the precise definition employed, the general thinking is the same – to work collaboratively to expedite the generation of resources (for example, tools, data and specimens) that each stakeholder can use to drive the success of that organisation’s commercial products. In the setting of biomarker science, stakeholders may include any of the following: academia, industry, non-profit foundations and associations, professional societies, advocacy groups and so on.

For the drug development industry, the competitive space is focused on the marketing of proprietary therapeutic agents with regulatory approval. As such, precompetitive opportunity is likely to centre on the ability to share the cost and risk of upstream research surrounding disease pathogenesis and progression to reveal targets for therapeutic intervention or discover markers for toxicity. Another opportunity for precompetitive pharmaceutical industry efforts could focus on the identification and validation of meaningful surrogate endpoints that could be employed during the clinical trials process.Of course, intellectual property considerations associated with the precompetitive effort must be carefully managed so as to not create a barrier for downstream commercialisation.

The framing of the precompetitive space can vary significantly across stakeholder groups, and varies even within a given stakeholder group. In general, the concept refers to the area of discovery and development necessary as a prerequisite or background to drive the success of that organisation’s commercial products.The development, attainment of regulatory approval, and marketing of proprietary therapeutics all fall squarely within the competitive space for the pharmaceutical industry. The precompetitive space, therefore, potentially includes any of the stages of the development pipeline preceding this, including basic research into disease biology revealing the molecular pathway(s) of disease as well as biomarkers for essentially any purpose, except perhaps for use as companion diagnostics within the framework of coordinated regulatory approval. Both patients and regulatory bodies are demanding the availability of valid and qualified biomarkers, so engaging in collaborative efforts to share the costs and risks provides a pathway for development that can leverage the strengths and resources of many stakeholder entities while decreasing cost and risk of failure on the part of each participating entity.

As Jackie Hunter, CEO of Pharmivation LTD and previously Head of Science Environment Development at GlaxoSmithKline explains,“[It] seems counterintuitive that companies would want to share data and potentially give away competitive advantages. But this presupposes that the possession of such data does indeed imply a competitive advantage, and that a closed operating model is financially sustainable” (11).

Defining precompetitive opportunities within the realm of what is precompetitive for diagnostics and/or medical device industries differs fundamentally from what is precompetitive for the pharmaceutical industry due to differences in the underlying business models. Biomarkers, along with the reagents, platforms and analytics underlying their use,may be quite central to the competitive business model for both the diagnostic and device industries in that all of these can be developed as specific products. At the same time, for the pharmaceutical industry biomarkers simply are generalised and fundamental tools to develop, gain registration for, or market therapeutics and drugs.Thus, the creation of precompetitive opportunities provides different challenges to test developers than for drug developers. However, irrespective of the industry and underlying business model, the determination of relevant precompetitive opportunities for any company depends on identifying mechanisms for discovering or developing fundamental base knowledge and outcomes that can drive a net positive return on investment for the company’s competitive products.

Keys to the success of precompetitive partnership or consortium activities include: the appropriate identification of the scope of the activity; suitable contributing partners with complementary or additive skills, data and/or resource sets; and operating principles and rules which can lead to scientific success, reduction in time or cost or risk, and generation of the data required for regulatory approval. Increasing costs, low success rates, increasing regulatory complexity, and the long return on investment (ROI) timelines increasingly cause pharmaceutical companies to externalise fundamental components of research and development, thus decreasing the ability of individual companies to qualify biomarkers alone.

Identifying Precompetitive Opportunities

As stated above, the nature and limits of the precompetitive realm depend significantly on the business and partnering strategies being engaged by each partnering stakeholder, including clear definition of the company’s competitive focus, as well as a reasonable assessment of the risks and benefits of participation. Any collaboration that delivers products or knowledge with potential to facilitate regulatory approval and market success should, therefore, be viable precompetitive areas of interest for that company.The shared interests and business models among a consortium of pharmaceutical companies or among a consortium of diagnostic companies makes the process of defining the precompetitive space relatively straightforward.However, for companies with both drug development and diagnostic development divisions it also presents additional challenges in defining what can be precompetitive.

Open innovation – where critical innovation strategies are sought from outside entities through a process in which the dilemma or goal is made known – is another approach to reducing early phase costs and risks.Open innovation is being pioneered by organisations such as Pharmivation LTD which are leading efforts to give industry strategies for recognising and engaging precompetitive opportunities with external collaborators.The Consortium Quebecois sur la Decouverte du Medicament (CQDM) is another example of an open innovation effort led by several major pharmaceutical companies (including AstraZeneca,Merck and Pfizer as founding partners) in collaboration with both the Canadian Government and academia to find precompetitive opportunities for enabling drug discovery. CQDM collaboration is providing improved access to external innovations, a greater than 10-fold leveraging of R&D investment expenditures, better links between the academic and biotechnology sectors, and more open channels for communication with government agencies for the pharmaceutical industry partners.

Broad information sharing initiatives that risk exposure of valuable IP give business-minded organisations reason for scepticism. However,Vargas et al (9), addresses the following concerns from the perspective of the pharmaceutical industry: standardisation of methods; information technology issues and alignment (for example, data element definitions, database ontologies and architecture); logistics and project management complexity; mission and scope management; handling of publicly available data; and, of course, IP issues. Additional concerns include fear of losing control of the collaboration, inability to divert sufficient resources away from ongoing operations, and lack of support from the highest levels of the organisation.Vargas et al explain that all of these issues can be mitigated through thoughtful planning and vigilant management, but IP issues deserve further treatment and examination here.

Open sharing of information is a critical component for the success of precompetitive collaborations. As IP represents one of the (if not the most) significant assets for both pharmaceutical companies and diagnostic companies, thoughtful preparation for clear IP protection of all contributing parties is likewise critical. The Critical Path Institute (C-Path) – a non-profit collaboration between the US Food and Drug Administration (FDA), industry and academia focused on accelerating drug discovery and development – addresses this by developing a formal agreement to engage a process and set of principles for resolving IP issues that emerge for each consortium it oversees (12). The thought here is that IP issues will always emerge, and a priori agreements facilitate their clear and graceful management.

Academic institutions, not surprisingly, appear to be enthusiastic supporters of precompetitive collaboration. One reason is that through consortia may come additional sources for funding academic research. Increasing collaboration with industry also has benefits for academic investigators, providing a means to keep abreast of commercial trends and activities that may provide technology transfer opportunities. A few examples of academic participation in precompetitive consortia include:The Wellcome Trust Case Control Consortium, where academic and industry scientists search for chemical probes for epigenetics; numerous consortia supported by the Gates Foundation, related to neglected and tropical diseases, HIV, and vaccine development, for example; the Biomarkers Consortium for biomarker research; and CQDM, for drug development.This subject of industryacademia collaboration is thoroughly treated by Melese et al with suggested strategies to improve their likelihood and productivity (13). 



Table 1 provides a high-level summary of the primary interests of the major stakeholders regarding the evolution of medical practice towards the personalised medicine paradigm and the subsequent need for robust and qualified biomarkers. It is critical in strategic terms to understand the primary concerns of the various stakeholders in crafting a collaborative initiative that thoughtfully aligns the interests of all parties.

Additional Precompetitive Biomarker

Initiatives One illustrative project involving the FDA and the European Medicines Agency (EMA) is a joint effort to consider the use of (preclinical) renal toxicity markers proposed by the Predictive Safety Testing Consortium (PSTC).The PSTC was initiated by the C-Path and involves the participation of 16 pharmaceutical companies to propose and establish qualification requirements for both regulatory bodies with regards to novel safety biomarkers.The PSTC is breaking new ground with both the FDA and EMA with respect to both regulatory process and approaches to biomarker qualification, which should subsequently yield a smoother process for future similar initiatives.The PSTC submitted a single (preclinical) biomarker data application to both regulatory agencies comprised of data generated by PSTC member organisations and the consortium, and then met jointly with scientists from both the FDA and EMA to discuss the details of the submission and to address any scientific questions posed by the regulators. Each regulatory agency then reviewed the application and made independent decisions on the use of the new biomarkers.The FDA assembled a Biomarker Qualification Task Force that has already delivered a response to this submission and is expected to continue beyond this project to assist in similar applications expected to follow.This streamlined pathway will be of benefit to coming efforts to extend this work to clinical markers of renal safety and toxicity as well as for other biomarker efforts in various therapeutic areas or organs.

The importance of broad, data-driven, and consensual agreement on the part of investigators and sponsors of biomarker submissions of the nature, use and value of specific biomarkers is recognised by both sponsors and regulators. From the US perspective, the FDA is a founding member and active participant in several precompetitive biomarker efforts, including the aforementioned C-Path and the Biomarkers Consortium (BC). The NIH and FDA are also partners with Pharmaceutical Research and Manufacturers of America (PhRMA) in the BC,which is a large-scale precompetitive initiative aimed at advancing biomarker research and qualification.The BC provides additional demonstrations of successful biomarker development including a completed project addressing the use of adiponectin as biomarker of glycemic control in diabetes mellitus (14); the recent launch of I-SPY2, an adaptive clinical trial for breast cancer that both utilises and seeks to qualify biomarkers to stratify patient for drug testing (15); and the development of a project aimed at validating clinical biomarkers for kidney safety testing of new drugs. Examples of European biomarker initiatives include the Innovative Medicines Initiative (IMI), the European Personalized Medicine Association (EPEMED) and the Pistoia Alliance. Collectively, these three projects represent the emerging appreciation of precompetitive research models by industry.

Conclusion

In summary, harnessing the full potential of biomarkers to deliver personalised medicine will require the leveraging of private industry, academic institutions, and relevant government agency resources – along with an innovative approach. Industry needs to understand the relevant precompetitive space(s) and leverage resources with appropriate partners in order to exploit the potential of biomarkers for the rapid, efficient, and economical delivery of products to patients while improving the development bottom line.Government agencies must appreciate and address the legitimate concerns from industry in engaging collaborative projects with open sharing of valuable intellectual property. Accrued experience with consortia that have succeeded in shepherding biomarkers through regulatory qualification for use provides justification for further precompetitive collaborative efforts.

References

  1. Cuatrecasas P, Drug discovery in jeopardy, The Journal of Clinical Investigation, 116(11): pp2,837-2,842, 2006
  2. Biomarkers in Drug Development: A Handbook of Practice, Application, and Strategy, ed Bleavins MR et al, Hoboken, NJ: John Wiley & Sons, Inc, 2010
  3. Carden CP et al, From darkness to light with biomarkers in early clinical trials of cancer drugs, Clin Pharmacol Ther 85(2): pp131-133, 2009
  4. DiMasi JA and Grabowski HG, Economics of new oncology drug development, J Clin Oncol 25(2): pp209-216, 2007
  5. Hughes V, Markers of dispute, Nat Med 15(12): pp1,339-1,343, 2009
  6. Diamandis EP, Cancer biomarkers: can we turn recent failures into success? J Natl Cancer Inst 102(19): pp1,462- 1,467, 2010
  7. Salluh JI and Bozza PT, Biomarkers of sepsis: lost in translation? Crit Care Med 36(7): pp2,192-2,194, 2008
  8. Dictionary.com, 21st Century Lexicon, www.dictionary.reference.com/browse/precompetitive
  9. Vargas G et al, Arguments against precompetitive collaboration, Clin Pharmacol Ther 87(5): pp527-529, 2010
  10. Wagner JA et al, The Biomarkers Consortium: practice and pitfalls of open-source precompetitive collaboration, Clin Pharmacol Ther 87(5): pp539-542, 2010
  11. Hunter J, Open-Source Pharmaceuticals? Project Syndicate, 2010
  12. Woosley RL, Myers RT and Goodsaid F, The Critical Path Institute’s approach to precompetitive sharing and advancing regulatory science, Clin Pharmacol Ther 87(5): pp530-533, 2010
  13. Melese T et al, Open innovation networks between academia and industry: an imperative for breakthrough therapies, Nat Med 15(5): pp502-507, 2009
  14. Wagner JA et al, Utility of Adiponectin as a Biomarker Predictive of Glycemic Efficacy Is Demonstrated by Collaborative Pooling of Data From Clinical Trials Conducted by Multiple Sponsors, Clinical Pharmacology & Therapeutics 86: pp619-625, 2009
  15. ISPY2 Press Release, http://www.biomarkersconsortium.org/images/stories/docs/ispypress031710.pdf

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Shawnmarie Mayrand-Chung earned a PhD in Biochemistry (Immunology) from Dartmouth Medical School in 1998, and received her JD from New York Law School in 2003. Shawnmarie worked in the field of patent law from 1998 to 2006, and joined the National Institutes of Health Program on Private-Public Partnerships in 2007. In her role as NIH Director for the Biomarkers Consortium, she deals directly with the NIH directors and scientists on all aspects of the Consortium, as well as working closely with the Foundation for NIH in her role as Senior Advisor to the Biomarkers Consortium.

Anthony J Dickherber is currently an AAAS Science and Technology Policy Fellow with the National Institute of Health. Prior to this, he was a postdoctoral researcher with the Nanotechnology Research Center at the Georgia Institute of Technology, assisting in the design of arrayable ion-trapping structures for quantum-bit computing. Anthony worked on microelectronic acoustic biosensor technology as a part of his doctoral thesis work while also completing a Sam Nunn Security Program Fellowship and directing the Biotechnology Policy Forum at Georgia Tech. Anthony also spent four years as a telecommunications researcher while at the Georgia Tech Research Institute.

Barbara Mittleman is the Director of the National Institutes of Health Public-Private Partnership Program. In this capacity she works to develop a wide range of partnerships between the NIH and industry, foundations, academic institutions and other entities both in the US and abroad. Barbara is an internist and rheumatologist, and trained at the University of Pittsburgh for medical school, residency and fellowship. She came to the NIH in 1991 to pursue a post-doctoral laboratory research training in cellular immunology and autoimmunity. Her current research interests include biomarkers, particularly for systemic lupus erythematosus (SLE), health disparities and bioethics.

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Shawnmarie Mayrand-Chung
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Anthony J Dickherber
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Barbara Mittleman
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