Opinion

VIEWPOINT

Sachin H. Jain, MD, MBA Merck and Company, Boston, Massachusetts, Harvard Medical School, Boston, Massachusetts, and Boston Veterans Affairs Medical Center, Boston, Massachusetts. Michael Rosenblatt, MD Merck and Company, Boston, Massachusetts. Jon Duke, MD, MS Regenstrief Institute, Indiana University School of Medicine, Indianapolis.

Corresponding Author: Sachin H. Jain, MD, MBA, 65 E India Row, 33B, Boston, MA 02110 (shjain@post .harvard.edu).

Is Big Data the New Frontier for Academic-Industry Collaboration? Academic-industry research collaborations have long been a source of controversy in medicine. Advocates suggestthatcollaborationscanfocusacademicresearcherson important clinical and translational research problems and providethemwithfinancialandcapability-enhancingtechnicalresources.1 Criticsmaintainthatindustryengagement distracts from, or distorts, the teaching and research missions of academia.2 Although regulatory and compliance frameworks have been established to govern these relationships,controversycontinuestosurroundeffortstoenhance industry and academia collaborations. With the increasing use of electronic medical records in clinical practice, a new potential source for partnerships has emerged: electronic clinical data. Academicindustry collaborations involving the use of such data provide opportunities to study the value and comparative effectiveness, safety, and efficacy of medications, vaccines, and health care delivery models.3 As interest in such collaborations increases, so does the need for thoughtful consideration of issues associated with them. The rationale for academic-industry partnerships around electronic clinical data stems from scientific, clinical, and economic need. After regulatory approval, pharmaceuticalanddevicecompanieshavelessdatathanother stakeholders regarding the use of their own products in clinical settings. Governments, health plans, and academic medical centers can query their own data to understand real-world patterns of disease and treatment, and the economicvalueofproductstopatientsandthehealthcaredelivery system.4 Evaluations of electronic clinical data could enable the study of products in patients whose lives and conditions often differ from patients enrolled in the clinical trials that first demonstrated the product’s use. Access to, and analysis of, such data are essential for companies thataimandareoftenrequiredtoevaluateandenhancethe safety and efficacy of their products—as well as to identify unmetmedicalneedsthatwarrantfutureresearch.Beyond access to data, a partnership with academia also provides collaborationwithhealthinformationscientistswhounderstand the databases and have specialized skills. Academic medical centers are investing heavily in electronic clinical systems to enhance patient care, billing, and meet regulatory requirements; but they also require additional resources to develop and maintain the infrastructure to integrate these systems with clinical management, population health, and research initiatives. Partnership with industry may enable collaborative development of capabilities, could bring focus on some critically important questions in health care, and could provide resources in an environment in which funding for informatics-related research is limited. In 2012, the Regenstrief Institute, an informatics and health care research organization affiliated with the Indi-

ana University School of Medicine, entered into a 5-year partnershipwithMerck,theglobalpharmaceuticalandvaccines company. The relationship, now 2 years old, has launchedmorethan50projectsthatrelyondatafrommore than 11 million patients in the Indiana Network for Patient Care (INPC), a health information exchange. With several high-level priorities identified, projects are solicited separately from Regenstrief and Merck scientists. Researchers with common interests are matched with co-investigators from the partner organization. Projects are subject to review by a steering committee that is composed of leaders from both organizations. Projects judged to have the highest merit and relevance to both Regenstrief and Merck are selectedforexecution.Examplesofrepresentativeprojects are listed in the Box, but can be broadly characterized as (1) new methodologies for observational research, (2) analysis of actual clinical data from practice settings, (3) novel applications of health information technology, (4) clinical interventions, and (5) education. Although it is too early to assess the scientific and clinical outcomes of the partnership because many of the first group of projects are ongoing and the first joint manuscripts are being published, important lessons have already been learned about the structure and organization of the partnership that have broad relevance to academic-industry data collaborations. Onekeyareaoflearninghasbeenaroundbridgingthe organizational differences between academia and industry,includingprojectplanningandfundingcycles,required approvals, and team communication. Academics who rely ongrantsforresearchoftenthink12to18monthsaheadregardingfunding.Industryactivitiesrequireagileadjustment to new priorities and often rapid initiation and completion of time-sensitive projects. This problem was solved by establishing a core set of academic researchers—including medicalinformaticians,biostatisticians,anddataanalysts— capable of conducting a variety of projects and funding them at a stable level for 12-month cycles. These researchers were then joined by domain experts and industry scientists as the projects became more defined. Projectsinvolvingpatientdataarecarefullyvetted,includinginstitutionalreviewboardapprovalontheacademic side and extensive internal protocol review on the industry side. To facilitate both organizations’ review processes, a common protocol document was developed. All patient data were deidentified and only Regenstrief researchers involved directly in the data analysis would have access to these deidentified data (all other team members see only aggregate results); Regenstrief maintains a data core composed of train data analysts who serve as a firewall between the data and Merck and Regenstrief investigators. Individual-level data, even deidentified, do not pass to the industry partner. This “arm’s length” arrangement is criti-

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Opinion Viewpoint

Sample Projects From the Merck-Regenstrief Partnership Methods for Observational Research

Melanoma phenotype algorithma development and validation Surveillance of acute myocardial infarction associated with antidiabetic agents Calibrating evidence of drug risk by estimating database bias Clinical Data Analysis

Adherence in respiratory disorders Usage, benefits, and adverse effects of diuretics in heart failure Longitudinal modeling of heart failure progression Outcomes of bisphosphonate treatment in adherent patients Renal impairment in osteoporosis Disparities in osteoporosis treatment Diagnosis of atypical subtrochanteric fractures Health Information Technology

Natural language processing core pipeline for clinical documents Electronic patient-reported outcomes (ePRO) capture platform Clinical Interventions

Adherence protocol for adults with mild cognitive impairment Human papillomavirus vaccination: an investigation of physician reminders and recommendation scripts Hypoglycemia risk calculator for use in clinical practice a

In studies of real-world data, there is a need to validate the phenotypes represented in the clinical data; the appropriate choice of phenotype is critical in ensuring the accuracy of observational data analysis.

cal for preserving the institutional and patient trust. Publications will be developed collaboratively by the academic and industry partner; both sides preserve autonomy to publish any results and any conflicts that arise are managed by the joint steering committee. Communicatingacrossorganizationsiscriticalforcollaborativeproject planning and execution. Differences in size and complexity can lead to challenges in this regard. Within this partnership, 3 levels of engagement were established: a steering committee that meets quarterly to focus on overall strategy, an operations committee that meets weekly to track projects and address emerging issues, and the project teams that meet at least biweekly. This structure has facilitated communication, both ground-up and top-down, supporting rapid response to researcher concerns and effective dissemination of high-level strategies. Having multiple tiers of engagement working in confluence is proving essential to maintaining a successful partnership. Overtime,organizationalneedswillevolve.TheMerck-Regenstrief partnershipinitiallyanticipatedtherewouldbe3typesofprojects:those ARTICLE INFORMATION

REFERENCES

Published Online: April 3, 2014. doi:10.1001/jama.2014.1845.

1. Dooley L, Kirk D; University-industry collaboration. Grafting the entrepreneurial paradigm onto academic structures. Eur J Innov Manage. 2007;10(3):316-332. doi:10.1108 /14601060710776734.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Duke reports coleading a large collaboration with Merck. No other disclosures were reported. Disclaimer: This Viewpoint represents the views of the authors and not necessarily the official positions of the institutions with which they are affiliated. 2172

of (1) primary interest to the research institution, (2) primary interest to the company, and (3) joint interest. These categories were chosen basedonthebeliefthattherightmixofprojectsacrosscategorieswould createasustainedcommitmenttothecollaboration.Thecategorieshave gradually coalesced into a focus on projects of joint interest. As negotiationaboutalignmentaroundprojectsandthemesemerged,itbecame clear that there was a great deal of common interest around key methodological and epidemiological questions. For instance, many of Regenstrief's methodological research interests were agnostic to the therapeutic and pipeline priorities of Merck. For example, Regenstrief is building and enhancing natural language processing capabilities. Although Merck was interested in these capabilities as a means of identifying specific patient cohorts, Regenstrief was agnostic to the specific use-case. As a result, there was an unexpected confluence of interests despite the different motivations driving them. Another key lesson relates to a focus on capability-building. When the partnership was announced, individuals on both sides of the relationship questioned the need for a multiyear relationship. What can be achieved through sustained partnership that cannot be achieved through“one-off”sponsoredprojectsonanas-neededbasis?Tobesure, therearefinancialandtransactionalsavingsassociatedwithamultiyear arrangement, as well as lower barriers to collaborations. A substantial benefitfromalong-termpartnershipisthatitenablesinvestmentincapabilities with longer time horizons. An example is the linkage of electronicmedicalrecordandbonemineraldensitydata.Feworganizations havelargerepositoriesofstructuredbonedensitydata;thosedatausuallyexistinseparatesystemsandareoftensimplytextreports.Because Merck is conducting research on a new osteoporosis therapy, it is also making investments in linking bone density data to the INPC. The foundational capabilities that have been created are of great interest to investigatorsonbothsidesoftherelationshipandmayhaveresearchvalue to both for years to come as new therapies are introduced. As the focus on novel uses of data in health care intensifies, there willbeanincreasingneedforacademic-industryrelationshipsthatmaximize the benefits achieved from appropriately using these data. Neither industry nor academia can navigate this terrain alone—nor should they. Working together, governments, health plans, academic delivery systems, electronic medical record vendors, and private sector companieshavethepotentialtoanalyzedatatoimprovecareandenhancethe sophistication of this research. Over time, these collaborations can extend beyond clinical practice information to include genomic, behavioral,andenvironmentaldata.However,thesetypesofrelationshipscertainly will involve both new opportunities and risks. Rigorous controls on how the data are used and by whom, careful and considered alignment of interests, and focused investments in long-term capabilitybuilding are important starting points for this new and expanding frontier of collaboration. priorities for research and initial research agenda. JAMA. 2012;307(15):1583-1584. 4. Psaty BM, Meslin EM, Breckenridge A. A lifecycle approach to the evaluation of FDA approval methods and regulatory actions. JAMA. 2012;307 (23):2491-2492.

2. Bekelman JE, Li Y, Gross CP. Scope and impact of financial conflicts of interest in biomedical research. JAMA. 2003;289(4):454-465. 3. Selby JV, Beal AC, Frank L. The Patient-Centered Outcomes Research Institute (PCORI) national

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Is big data the new frontier for academic-industry collaboration?

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