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Effort is being expended in investigating efficiency measures (i.e., doing trials right) through achievement of accrual and endpoint goals for clinical trials. It is time to assess the impact of such trials on meeting the critical needs of cancer patients by establishing effectiveness measures (i.e., doing the right trials). Clin Cancer Res; 18(1); 3–5. ©2011 AACR.

e18638 Background: The SOA is a key part of any clinical trial as it highlights activities to be performed during trial execution. Such a schedule provides a roadmap and calendar of tests, measurements, and evaluations. Normally, such a schedule is created after a protocol has been mostly created. Our aim is to demonstrate that the SOA can have a broader usage: that of a quality improvement (QI) tool used during protocol creation, thus helping to ensure a high-quality protocol at the design. When creating a protocol conflicting uses of the Protocol contribute to operational tension. For example, Trial Operations, which wishes to minimize the complexity of the trial, may debate with Clinical Science, who wish to collect the greatest amount of scientific tests and data. The more complex a set of requirements in the protocol, there is a corresponding drop in available sites able to meet those needs. Additionally potential sites may comment about being burdened with tests that are unnecessary to the core protocol aims, thus creating unnecessary delays in the trial. All these issues may be addressed by using the SOA as a QI tool. Methods: This research was completed at a major, international pharmaceutical organization for a Phase III oncology clinical trial. A team was created composed of: Clinical Scientist Lead , Stats/Data Lead, Trial Operations Led, Medical Monitor, Medical Leader, and Lean Expert. Methodologically, this was led by the Lean Expert and each team member was sent an electronic version of a draft SOA for review. They inserted questions and comments that were visible to the entire team. After this, an SOA issues log was created in an SOA tracking system. This system categorized and ranked issues for discussion by the entire team during the creation process of both the SOA and the protocol. The process used a “House of Quality” framework, allowing for the aggregation of protocol requirements so that they could be addressed in total, rather than individually. Results: The process was successful in 3 critical dimensions. From a time metric, the SOA was produced 3 to 6 months faster, enabling numerous efficiencies such as providing the development team with information both faster and at the time the team was creating the final protocol. Second, from an economic standpoint, the labor efficiency of the trial was improved as it required 33% less individuals to produce the SOA and protocol resulting in a protocol at record speed. Finally, protocol quality was increased as in this method the team worked jointly together, nearly simultaneously, to complete both the SOA and the protocol. This reduced the number of Protocol Amendments by 50%. Conclusions: Using this method, there was an increase in quality, a reduction in cost, and a faster time to the sites. This reduced the commercialization timeline by 3-6 months which is a significant cost savings. But most importantly, this allows for better treatment faster to be in the hands of oncologists to treat patients.

e18639 Background: With the ever-increasing complexity of protocols and their required approvals, there is a need to improve the time and reduce the effort required to create a Phase III protocol. The objective of this research was to reduce from months to weeks the time to create a Phase III protocol at a large global pharmaceutical organization, while maintaining or improving the quality and scientific merit of the protocol. Methods: The method required two phases: process redesign and process execution/performance. For the first phase, a continuous improvement methodology (Lean), was utilized. In a multi-team-based approach, the first stage (process-prep) focused on the development of the initial draft protocol. The second stage used the concept of a Sprint, a process to complete all protocol changes and approvals within a rapid time span, while simultaneously guaranteeing protocol quality. A set of policies, procedures, and information technology tools were developed to facilitate both efforts. The Process-prep stage was team-based, where a streamlined Clinical Study Team and a sub-group, the Protocol Working Group, identified all the key tasks, activities and their associated completion dates, and created an 80% complete draft protocol. The Sprint was a one-week, intensive effort by all those responsible for creation of the protocol, and for its final approval. Working virtually and internationally allowed for a continuous 24-hour effort during the Sprint. One key element of success was the use of a visualization tool for the creation, adaptation, and finalization of the protocol’s schedule of assessments (SOA) which both assured that all assessments were required by the protocol and that there was concordance between the protocol and the SOA. Results: Quantitative results were significant: a completed protocol was created with a 50% reduction of time compared to the last protocol written by the molecule group, reduction of avoidable amendments, reducing missed errors and potentially decreasing the number of protocol amendments and the near elimination of process loops and email-chains. Qualitatively, team members were trained on useful process tools and methods, while also increasing their comfort level in active participation in remote meetings. This resulted in faster time to create any amendments that may be required in the future for the protocol. Conclusions: It is possible to employ efficiency and effectiveness methods, such as Lean and Sprint, that have been used successfully in other industries in the pharmaceutical research & development process. While using such concepts requires a great deal of initial planning, the rewards of using them are significant. Likewise, the extensive use of interdisciplinary remote teams will be of increasing importance in a post-COVID environment of clinical research.

Background: A low proportion of adults with cancer are recruited to clinical trials. Cancer Council Victoria provides funding to clinical trial sites through its statewide Cancer Trials Management Scheme (CTMS). Historically, there appeared to be a relationship between budget-allocated funding and the number of patients recruited. A randomized controlled trial was conducted to test whether additional funding in 2013 would increase trial recruitment. Methods: A total of 18 trial centers ("sites") received usual CTMS funds, whereas 16 intervention sites received usual funds plus additional funds, proportional to recruitment in 2011; additional payments to sites in the intervention group ranged from $6,750 to $234,000 AUD (≈$6,750-$234,000 USD at the time). This represented an average 11.8% (interquartile range [IQR], 8.0%, 12.3%) increase in sites' budgets. Sites were required to use the funds with the aim of increasing recruitment. The study end point was the number of new participants recruited to trials in 2013. An online survey assessed strategies used to increase recruitment. Results: The median number of new trial recruits per site in 2013 was 21 (IQR, 5-39) in the control arm and 12.5 (IQR, 3.5-44.5) in the intervention arm. The ratio of new trial recruitment numbers at the intervention sites compared with control sites in 2013, adjusting for respective 2012 numbers and institution type, was 0.99 (95% CI, 0.69, 1.43; P=.96). The survey revealed most intervention sites used funding to increase staffing. Conclusions: Additional funding at a site level did not lead to a contemporaneous increase in trial recruitment.

Clinical trials are essential for developing new and effective treatments and improving patient quality of life; however, many trials cannot answer their primary research questions because they fall short of their recruitment goals. This article reports the results of formative research conducted in two populations, the public and primary care physicians, to identify messages that may raise awareness and increase interest in clinical trials and be used in a national communication campaign. Results suggested that participants were primarily motivated to participate in clinical trials out of a self-interest to help themselves first. Messages illustrated that current treatments were tested via clinical trials, helped normalize trials as routine practices, and reduced concerns over trying something new first. Participants wanted messages that portray trials as state-of-the-art choices that offer some hope, show people like themselves, and are described in a clear, concise manner with actionable steps for them to take. The study revealed some differences in message salience, with healthy audiences exhibiting lower levels of interest. Our results suggest that targeted messages are needed, and that communication with primary health-care providers is an important and necessary component in raising patient awareness of the importance of clinical trials.

Purpose Measuring the efficiency of resource allocation for the conduct of scientific projects in medical research is difficult due to, among other factors, the heterogeneity of resources supplied (e.g., dollars or FTEs) and outcomes expected (e.g., grants, publications). While this is an issue in medical science, it has been approached successfully in other fields by using data envelopment analysis (DEA). DEA has a number of advantages over other techniques as it simultaneously uses multiple heterogeneous inputs and outputs to determine which projects are performing most efficiently, referred to as being at the efficiency frontier, when compared to others in the data set. Method This research uses DEA for the evaluation of supported translational science projects by the Oregon Clinical and Translational Research Institute (OCTRI), a NCATS Clinical & Translational Science Award (CTSA) recipient. Results These results suggest that the primary determinate of overall project efficiency at OCTRI is the amount of funding, with smaller amounts of funding providing more efficiency than larger funding amounts. Conclusion These results, and the use of DEA, highlight both the success of using this technique in helping determine medical research efficiency and those factors to consider when distributing funds for new projects at CTSAs.

We report on the thoughts of a large group of scholars in the field of operations and supply chain management (O/SCM) regarding current and future issues facing our profession. Broad issues raised and addressed include a perceived lack of relevance in our research, calls from business school deans for faculty to increasingly fund their own research, greater demand for use of large data sets and methodological rigor, along with higher expectations for publishing. We invited four scholars who discussed these issues during an Academy of Management conference session in 2014, to present their perspectives within this essay. We then distributed the perspectives of each of these authors to O/SCM scholars globally so that they could add support, counterpoints, and extensions. Collectively, they raise important points regarding a need for greater innovation and creativity in O/SCM research, the challenges and opportunities of increased complexity and “big data,” the value of working in other research domains and collaborating with others, the promise of new technology, and the importance of improving how we communicate our value to business school colleagues. Finally, our contributors provide recommendations on how we may address these issues and continue to adapt and move our profession forward.

Combination therapy has proven to be an effective strategy for treating many of the world's most intractable diseases. A growing number of investigators in academia, industry, regulatory agencies, foundations and advocacy organizations are interested in pursuing a combination approach to treating Alzheimer's disease. A meeting co-hosted by the Accelerate Cure/Treatments for Alzheimer's Disease Coalition, the Critical Path Institute and the Alzheimer's Association addressed challenges in designing clinical trials to test multiple treatments in combination and outlined a roadmap for making such trials a reality.

Many challenges to clinical trial accrual exist, resulting in studies with inadequate enrollment and potentially delaying answers to important scientific and clinical questions.The National Cancer Institute (NCI) and the American Society of Clinical Oncology (ASCO) cosponsored the Cancer Trial Accrual Symposium: Science and Solutions on April 29-30, 2010 to examine the state of accrual science related to patient/community, physician/provider, and site/organizational influences, and identify new interventions to facilitate clinical trial enrollment. The symposium featured breakout sessions, plenary sessions, and a poster session including 100 abstracts. Among the 358 attendees were clinical investigators, researchers of accrual strategies, research administrators, nurses, research coordinators, patient advocates, and educators. A bibliography of the accrual literature in these three major areas was provided to participants in advance of the meeting. After the symposium, the literature in these areas was revisited to determine if the symposium recommendations remained relevant within the context of the current literature.Few rigorously conducted studies have tested interventions to address challenges to clinical trials accrual. Attendees developed recommendations for improving accrual and identified priority areas for future accrual research at the patient/community, physician/provider, and site/organizational levels. Current literature continues to support the symposium recommendations.A combination of approaches addressing both the multifactorial nature of accrual challenges and the characteristics of the target population may be needed to improve accrual to cancer clinical trials. Recommendations for best practices and for future research developed from the symposium are provided.

Assessing the value of clinical and translational research funding on accelerating the translation of scientific knowledge is a fundamental issue faced by the National Institutes of Health (NIH) and its Clinical and Translational Awards (CTSAs). To address this issue, the authors propose a model for measuring the return on investment (ROI) of one key CTSA program, the clinical research unit (CRU). By estimating the economic and social inputs and outputs of this program, this model produces multiple levels of ROI: investigator, program, and institutional estimates. A methodology, or evaluation protocol, is proposed to assess the value of this CTSA function, with specific objectives, methods, descriptions of the data to be collected, and how data are to be filtered, analyzed, and evaluated. This article provides an approach CTSAs could use to assess the economic and social returns on NIH and institutional investments in these critical activities.

Clinical research management (CRM) is a critical resource for the management of clinical trials and it requires proper evaluation. This article advances a model of evaluation that has three local levels, plus one global level, for evaluating the value of CRM. The primary level for evaluation is that of the study or processes level. The managerial or aggregate level concerns management of the portfolio of trials under the control of the CRM office. The third, often overlooked level of evaluation, is the strategic level, whose goal is encapsulated in the phrase, “doing the right trials, while doing trials right.” The global (“plus one”) evaluation level concerns the need to evaluate the ever-increasing number of multi-institutional and multinational studies. As there are host of evaluation metrics, this article provides representative examples of metrics at each level and provides methods that can aid in the selecting appropriate metrics for an organization.

PurposeThe authors assessed the prevalence and associated economic impact of low-enrolling clinical studies at a single academic medical center.MethodThe authors examined all clinical studies receiving institutional review board (IRB) review between FY2006 and FY2009 at Oregon Health & Scien

Objectives Improvements in electronic health record (EHR) system development will require an understanding of psychiatric clinicians' views on EHR system acceptability, including effects on psychotherapy communications, data-recording behaviors, data accessibility versus security and privacy, data quality and clarity, communications with medical colleagues, and stigma. Design Multidisciplinary development of a survey instrument targeting psychiatric clinicians who recently switched to EHR system use, focus group testing, data analysis, and data reliability testing. Measurements Survey of 120 university-based, outpatient mental health clinicians, with 56 (47%) responding, conducted 18 months after transition from a paper to an EHR system. Results Factor analysis gave nine item groupings that overlapped strongly with five a priori domains. Respondents both praised and criticized the EHR system. A strong majority (81%) felt that open therapeutic communications were preserved. Regarding data quality, content, and privacy, clinicians (63%) were less willing to record highly confidential information and disagreed (83%) with including their own psychiatric records among routinely accessed EHR systems. Limitations single time point; single academic medical center clinic setting; modest sample size; lack of prior instrument validation; survey conducted in 2005. Conclusions In an academic medical center clinic, the presence of electronic records was not seen as a dramatic impediment to therapeutic communications. Concerns regarding privacy and data security were significant, and may contribute to reluctances to adopt electronic records in other settings. Further study of clinicians' views and use patterns may be helpful in guiding development and deployment of electronic records systems.

This paper investigates the dynamics of a complex adaptive supply network (CASN), focusing on understanding stability of the structural evolution of a supply network and supplier population emergence. Supply network evolution data collected from simulated responses of the U.S. automobile industry are used in multivariate statistics and time series analysis to identify patterns of network evolution. This analysis reveals that the type of environment a supply network evolves in appears to be a major factor in determining critical timing of structural changes during the evolution of a CASN. Further, time series analysis of firm population evolution highlights how supply networks evolve due to path dependencies in the CASN system. Information about these two aspects of supply network evolution can prove useful to a decision maker in determining how to respond to supply network changes.

While ISO 9000 has been shown to improve internal metrics of firm performance, external measurements may be unaffected. This paper examines the economic value of successive generations of the ISO 9000 standard by assessing the equity returns of 204 firms certified between 1999 and 2002. This study also examines the economic effects of ISO 9001:2000 versus the superseded 1994 standards. The complete sample experienced no significant changes in stock price. The market reaction to ISO 9001:2000 certification is significantly more positive than the reaction to ISO 9000:1994 registration.

Supply chains, or supply networks (SNs), exist in a multitude of different topologies, yet little is known concerning how such topologies grow, evolve, and adapt over time. To study this complex phenomenon, we begin by identifying some primary topological structures that SNs may form. Then, to investigate the evolution of such structures, a theory-based framework is developed that combines aspects of complex adaptive systems theory, industrial growth theory, network theory, market structure, and game theory. This framework specifies categories of rules that may evoke different behaviors in the two fundamental components of any adaptive SN, i.e., the environment and the Arms in that environment. The framework is implemented as a multiparadigm simulation utilizing software agents and it joins discrete-time with discrete-event simulation formalisms. This methodology allows the spontaneous generation of network structures so that it is possible to examine the potential factors behind the evolution of different SN topologies. Using data and parameters extracted from 80 years of the U.S. automobile industry, we have been able to "grow" a wide range of SN topologies and preliminary results show that certain environmental and firm-level factors may impact the eventual evolution of such structures.

Due to a lack of valid and reliable scales, few studies have sought to describe and measure the business incubation process. After rigorously developing and pre-testing scales intended to measure the incubation process (Study A), we collected data from 53 incubators operating in the US in order to (a) systematically examine the incubation process, and (b) validate the scales. Accordingly, this study offers (1) new, validated scales for measuring the process of incubating new ventures, (2) empirically-based refinements to a theoretical model of the incubation process, and (3) data on business incubation outcomes that are very useful for incubator planning and benchmarking purposes.

Measuring the efficiency of resource allocation for the conduct of scientific projects in medical research is difficult due to, among other factors, the heterogeneity of resources supplied (e.g., dollars or FTEs) and outcomes expected (e.g., grants, publications). While this is an issue in medical science, it has been approached successfully in other fields by using data envelopment analysis (DEA). DEA has a number of advantages over other techniques as it simultaneously uses multiple heterogeneous inputs and outputs to determine which projects are performing most efficiently, referred to as being at the efficiency frontier, when compared to others in the data set.This research uses DEA for the evaluation of supported translational science projects by the Oregon Clinical and Translational Research Institute (OCTRI), a NCATS ClinicalTranslational Science Award (CTSA) recipient.These results suggest that the primary determinate of overall project efficiency at OCTRI is the amount of funding, with smaller amounts of funding providing more efficiency than larger funding amounts.These results, and the use of DEA, highlight both the success of using this technique in helping determine medical research efficiency and those factors to consider when distributing funds for new projects at CTSAs.

Through application of collective action and stakeholder theories, examination of theoretical and analytical studies of technological planning and technology roadmapping, and collection and analysis of survey data from organizational participants in six different industry technology roadmapping exercises, a theoretical model predicting factors that influence the impact on organizations participating in the creation of an industry-level technology roadmap (ITR) was developed and evaluated. The model includes: 1) motivations for organizations to participate in the development of an ITR, 2) industry-related motivations for developing a roadmap, 3) stakeholder-based structure and processes used to create the roadmap, 4) characteristics of the roadmap document, 5) industry clockspeed (pace of change), and 6) organizational impacts from ITR development (e.g. technology planning, pace of innovation, collaborative activities and partnering, implementation of new technologies, etc.). A survey instrument was administered to participants (N=128) involved with six different industry technology roadmapping exercises: concrete, electronics, forest products, magnesium, metal casting, and powder metallurgy industries. This paper summarizes the feedback from ITR development organizational participants regarding six open-ended questions, and makes some conclusions about what characteristics determine whether a roadmap experiences future iterations or is left as a one-time exercise in an industry.

Purpose To investigate the administrative barriers that impact the opening of clinical trials at the Vanderbilt-Ingram Cancer Center (VICC) and at VICC Affiliate Network (VICCAN) sites. Methods VICC, a National Cancer Institute–designated comprehensive cancer center, and three VICCAN community practice sites were studied. Methodology used was identification and mapping of existing processes and analysis of historical timing data. Results At course granularity, the process steps required at VICC and VICCAN main office plus local sites are 20 v 17 to 30 steps, respectively; this gap widens with finer granularity, with more than 110 v less than 60 steps, respectively. Approximately 50% of the steps are nonvalue added. For example, in the institutional review board (IRB) process, less than one third of the steps add value to the final protocol. The numbers of groups involved in the approval processes are 27 (VICC) and 6 to 14 (VICCAN home office and local sites). The median times to open a trial are 171 days (95% CI, 158 to 182 days) for VICC and 191 days (95% CI, 119 to 269 days) for the VICCAN sites. Contrary to expectations, the time for IRB review and approval (median, 47 days) is the fastest process compared with the scientific review committee review and approval (median, 70 days) and contracts and grants review (median, 78.5 days). Opening a cooperative group clinical trial is significantly (P = .05) more rapid because they require fewer review steps. Conclusion There are numerous opportunities to remove nonvalue-added steps and save time in opening clinical trials. With increasing numbers of new agents, fewer domestic principal investigators, and more companies off-shoring clinical trials, overcoming such barriers is of critical importance for maintenance of core oncology research capabilities in the United States.

Purpose National Cancer Institute–sponsored cooperative oncology groups are major sponsors of phase III clinical trials, yet the time and steps required to design and activate such studies has not been well studied. We examine the processes and document the calendar time required to activate such studies opened by the Cancer and Leukemia Group B (CALGB). Methods Setup steps were documented by (1) interviewing CALGB headquarters and statistical center staff and committee chairs to discover the steps required to transit from concept development to final study activation, (2) reviewing procedure manuals, and (3) inspecting all study records, documents, and e-mails to identify any additional steps. Calendar time was collected for each major process. Results Thirteen phase III studies were activated by CALGB during the study period of May 2002 to May 2005. More than 370 distinct processes were required for study activation: 317 work steps, 42 decision points, and 29 processing loops. Sixty-three percent of the decision points were outside CALGB. The complete process map measures 243.5” × 41” in 8-point font. Median calendar days to activate a phase III study at CALGB was 580 days (range, 295 to 1,248 days) from concept approval and 784 days (range, 537 to 1,130 days) from initial conception of the study. Conclusion Setup of a phase III study at a major cooperative oncology group is a complex and lengthy process, with the majority of decision points external to the cooperative group. To improve the activation process, research should to be directed toward both internal and external groups and processes.

It is acknowledged that progress in combined therapeutic approaches for Alzheimer’s disease (AD) will require an unprecedented level of collaboration. At a meeting co-hosted by the Accelerate Cure/Treatments for Alzheimer’s Disease Coalition and the Critical Path Institute, investigators from industry, academia and regulatory agencies agreed on the need for combinatorial approaches to treating AD. The need for advancing multiple targets includes recognition for novel adaptive trial designs that incorporate existing and new biomarkers to evaluate drug effects independently and in combination. A combination trial now being planned may test drugs targeting different pathogenic pathways or multiple targets along a common pathway. Collaborations and consortia-based strategies are pivotal for success and a regulatory framework is recommended for success.

Our research examines factors used by public service personnel and their contractors to reach the decision to terminate a project. Two decision-making roles are studied: executives, those with the authority to start or cancel a project, and project managers, those who direct the day-to-day operations of the project. Our exploratory survey research, an initial step in this topic, suggests that different roles cluster critical termination factors uniquely and use different decision weighting levels on these factors. On a second construct, information gathering actions, such as scanning and interpretation, show an indication of bias, particularly sunk cost bias, and this bias is experienced differently by executives and project managers. Interestingly, the scale of a project, in terms of labor-hours, calendar time, or budget, does not appear to be related to perception of ‘failure’. The implications for the management of government safety projects are that care must be taken to understand the differing viewpoints of the two types of decision-makers and that the initial presentation of information concerning a project may influence the perception of a project's outcome. While there are several implications for operations management research, the most critical is that care must be given when surveying “managers” concerning subjective measures of ‘success’ or ‘failure’ as there can be radical perceptual differences by role.

Information technology is providing manufacturers with additional flexibility with regard to their supply chain network choices. Our research studies supply chain network organization structures categorized by the organic and mechanistic management control structures. The structural impacts on cost and fill rate performance are studied in two-echelon and two-supply-chain network organization models under different market coordination conditions using system dynamic simulations. Our results show significant effects of demand and network structural factors, and their interactions, on these measures. As demand becomes dynamic, the cooperative interaction model, where supply chains cooperate to satisfy customer demand, is found to have better system performance than the competitive supply chain model. The analysis also suggests that increasing the responsiveness at the downstream plant is particularly important to the overall system performance improvement.

This article systematically reviews the literature on business incubators and business incubation. Focusing on the primary research orientations—i.e. studies centering on incubator development, incubator configurations, incubatee development, incubator-incubation impacts, and theorizing about incubators-incubation—problems with extant research are analyzed and opportunities for future research are identified. From our review, it is clear that research has just begun to scratch the surface of the incubator-incubation phenomenon. While much attention has been devoted to the description of incubator facilities, less attention has been focused on the incubatees, the innovations they seek to diffuse, and the incubation outcomes that have been achieved. As interest in the incubator-incubation concept continues to grow, new research efforts should focus not only on these under-researched units of analysis, but also on the incubation process itself.

This article employs real options-theoretic reasoning to develop a theory of business incubation. This theory seeks to predict and explain how business incubators and the process of business incubation increase the likelihood that new ventures will survive the early stages of development. It conceptualizes the incubator as an entrepreneurial firm that sources and macro-manages the innovation process within emerging organizations, infusing these organizations with resources at various developmental stage-gates while containing the cost of their potential failure. The incubator is the unit of analysis while incubation outcomes—measured in terms of incubatee growth and financial performance at the time of incubator exit—provide indicators of success. Our model of the incubation process and specification of the range of possible incubation outcomes offer implications for managerial practice and policy-making vis-a-vis incubator management and good entrepreneurial failure.

Assessing impact of poor accrual on premature trial closure requires a relevant metric. We propose defining accrual sufficiency on apparent ability to address primary endpoints (PE) rather than attaining accrual targets.All phase III trials open January 1, 1993, to December 31, 2002, by five U.S. oncology Clinical Trials Cooperative Groups (CTCG) were evaluated for accrual sufficiency and scientific results. Sufficient accrual included meeting accrual target, CTCGs documentation attesting adequate accrual, or conclusive results at interim analysis; insufficient accrual included poor accrual as cited closure reason or other reasons rendering a trial unable to address its primary endpoints. Closure rates based on our accrual sufficiency definition are compared with rates of meeting accrual targets and addressing the primary endpoints. A percentage of target accrual above which trials commonly answer the intended scientific question was identified to serve as an alternative to meeting full target accrual in designating accrual success.Of 238 eligible trials, 158 (66%) closed with sufficient accrual. Among 80 trials with insufficient accrual, 70 (29%) closed specifically because of poor accrual. Inadequate accrual rates are overemphasized when defining accrual success solely by meeting accrual targets. Nearly 75% of trials conclusively addressed the primary endpoints with positive results in 39% of trials. Exceeding 80% of target accrual serves as a reliable proxy for answering the intended scientific question.Approximately one third of phase III trials closed with insufficient accrual to address the primary endpoints, primarily due to poor accrual. Defining accrual sufficiency broader than meeting accrual targets represents a fairer account of trial closures.

In the 40 years since the war on cancer was announced, over a $105 billion and hundreds of thousands hours by researchers, statisticians, data managers, and clinical trial offices have been spent in oncology research. There has been amazing progress made in some cancer types during these four decades, however the process is still taking too many resources for too little gain. It is time to speed up this progress by, among other things, re-envisioning the goals, or the bar of oncology clinical research. The accompanying article for this editorial, Ellis et al provide specific guidance on how to raise the bar for oncology clinical trials in selected patient populations. This report of four working groups, convened by American Society of Clinical Oncology, challenges current clinical trial design to stop seeking only limited gains but to strive for clinically meaningful results that are “larger incremental gains than have been achieved in the past.” While the article identifies these goals as aspirational or stretch goals currently, it is time that trial designs with such high expectations be created, executed, and prioritized by funding agencies, companies, and regulatory agencies. Throughout history, innovations have been influenced by stretch goals, or prizes, which to be achieved required meaningful advances to their fields. We know of Thomas Edison as the inventor of the incandescent light bulb not because he was the first to invent one (there were over 22 inventors of light bulbs before Edison) but because he was the first to create a bulb that lasted a meaning amount of time. Indeed, different organizations have been set up strictly to foster material, significant innovations, including government agencies (eg, the Defense Advanced Research Projects Agency [DARPA], responsible for early global positioning system and the Internet) and commercial entities (eg, Bell Lab, responsible for transistors, lasers, and chargecoupled devices; IBM Research Lab, responsible for hard disks, the modern automatic teller machine, and universal product code barcodes; and Palo Alto Research Center, responsible for the laser printers and graphical user interface). Returning to clinical trials with high aspirations, the problem is that such trials are by definition meaningful (ie, they upset the status quo and require a different view of what is needed in and by a clinical trial). Two views that should be included in every new trial are the inclusion of “-omics” and the use of adaptive trial design. The former provides information concerning which patient populations may benefit from the intervention, and the later uses such information to help properly select which patients for which treatment arm, thus reducing the total accrual requirements for the trial. Such trials have already been successfully executed in oncology, including the BATTLE (Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination), the I-SPY 2 (Investigation of Serial Studies to Predict Your Therapeutic Response With Imagine and Molecular Analysis 2), and the CUSTOM (Molecular Profiling and Targeted Therapy for Advanced Non–Small-Cell Lung Cancer and Thymic Malignancies) trials. Like many meaningful innovations, using such knowledge can make the phase III trial faster to complete, provide more and better information, and be less expensive to complete. These designs then fulfill the old Bell Labs motto: better, cheaper, or both. However, like all radical innovations, they also come with risks. The first risk is that of lack of knowledge. As acknowledged in the article, validated biomarkers or companion diagnostics are not always present. It is difficult to hit a target when it is not certain where it is or if it is valid. This, not insubstantial risk, should be ameliorated in the near future as all major clinical research organizations are banking specimens, some of which are highly annotated, and as technology to analyze such specimens become faster, better, and cheaper. The second risk is that the expectations of patients and regulatory agencies out strip the technical capabilities of achieving the aspirational trial goals. There are numerous examples of technologies that could not keep up with meaningful expectations, including the personal robots, the self-cleaning kitchen, and, until recently, self-driving cars. Thus expectations need to be tempered with reality. However, saying that, there is a complementary risk of not striving hard or fast enough. The genius of Steven Jobs was not only that he was a consummate inventor but also that he understood how to create a future that customers wanted, even if they didn’t know they wanted it. Apple computer, without Jobs’ leadership, became an organization that concentrated on incremental improvement and it nearly entered bankruptcy. Today, Apple is acknowledged to be one of the most radically innovative firms in the world. This took risk taking, an understanding of customer’s desires, and a tight knowledge of underlying technologies. It is time that oncology clinical trials become less incremental and more innovative, striving for more, faster. Basically, it is time for them to invent the future of oncology care. The final risk with striving for aggressive goals is in not understanding the need to manage the inevitable failures in a visible and collective manner. It is important that such failures not be a focus of blame but viewed as a set of lessons learned to improve the entire clinical trial process. For example, when Corning was creating the JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 32 NUMBER 12 APRIL 2

A number of models have been proposed to predict optimal setup times, or optimal investment in setup reduction, in manufacturing cells. These have been based on the economic order quantity (EOQ) or economic production quantity (EPQ) model formulation, and have a common limitation in that they neglect work-in-process (WIP) inventories, which can be substantial in manufacturing systems. In this paper a new model is developed that predicts optimal production batch sizes and investments in setup reduction. This model is based on queuing theory, which permits it to estimate WIP levels as a function of the decisions variables, batch size and setup time. Optimal values for batch size and setup time are found analytically, even though the total cost model was shown to be strictly non-convex.

Reply to the “Comment: Using Product Profiling to Illustrate Manufacturing-Marketing Misalignment” by Richard J. Schonberger (Interfaces vol. 29, no. 6, November–December 1999, pp. 127–129) referring to the Interfaces July–August 1998 article “Using product profiling to illustrate manufacturing-marketing misalignment” by Hill, Menda, and Dilts, where they described Rumack Pharmaceutical Company (disguised name) as an example of misalignment between marketing and manufacturing.

Ordinal data is prevalent in medical outcomes research; for example, gender, living condition, and use of assistive devices are all both critical explanatory factors in determining the efficacy of medical procedures and are nominal or ordinal data. One basic objective of this study was to compare four assignment (ordinal analysis techniques') prediction of expected patient resource requirements in a specialty ambulatory (outpatient) health care setting. Data from 2427 patient discharges from 7 specialty low vision clinics were collected. Biographical and discharge characteristics of patients were used to develop homogeneous patient groups on the basis of resource use. Resource-use features were then stripped from the data. The four ordinal analysis techniques were subsequently applied to the reduced data set to predict iso-resource group membership for each patient in the data. Chance criterion was used as a benchmark in gauging the predictive ability of each ordinal analysis technique. Prediction results obtained were clinic-specific. This may largely be explained by the fact that the initial iso-resource groups were unique to each clinic and no meaningful iso-resource groups could be obtained from combined data across clinics. No technique was found to be universally superior at all clinics, however, each technique's performance across clinics was consistently better than the benchmark. Contrary to initial expectations, neural networks, in some cases, significantly underperformed the more traditional techniques.

As companies choose among process alternatives, they need a clear understanding of the changing alignment between manufacturing and the needs of their markets. Assessing how well existing processes fit these market requirements and making choices to meet future needs are critical strategic responsibilities for manufacturing. Product profiling can be used to examine the degree of alignment between the needs of a company's markets and the characteristics of its existing manufacturing process and infrastructure investments. We compare product profiling with another tool, the product-process matrix, and examine the applicability of both in a typical mismatch situation. In-depth analysis in one firm indicates that product profiling is a valuable tool to uncover the origins of misalignments that occur over time and to illustrate the phenomenon to executives.

While there has been considerable research on the content of manufacturing strategy, there is a paucity of literature concerning the process of manufacturing strategy formulation [Ward, P.T., Brickford, D.J., Leong, G.K., 1996. Configuration of manufacturing strategy, business strategy, environment, and structure, J. Manage., 22(4) 597–626; Leong, G.K., Snyder, D.L., Ward, P.T., 1990. Research in the process and content of manufacturing strategy, Omega, 18(2) 109–122]. Many researchers have highlighted the need to overcome this deficiency by studying the process of developing manufacturing strategy [Adam, E.E., Swamidass, P.M., 1989. Assessing operations management from a strategic perspective, J. Manage., 15(2) 181–203; Anderson et al., 1989; Leong, G.K., Snyder, D.L., Ward, P.T., 1990. Research in the process and content of manufacturing strategy, Omega, 18(2) 109–122]. To effectively link the manufacturing strategy of a firm to the needs of the marketplace, critical competitive factors or order-winning criteria must be understood and agreed upon both by operations and marketing managers [Hill, T.J., 1983. Manufacturing's strategic role, J. Operational Res. Soc., 34(9) 853–860; Hill, T.J., 1994. Manufacturing Strategy—Text and Cases, 2nd edn., Irwin, Homewood, IL]. For this study, we created and examined a process of establishing a set of order-winning criteria for a consumer pharmaceuticals firm which involved the participation of sixteen managers from seven functional areas over four months. The foundation of the process was developed by Hill [Hill, T.J., 1989. Manufacturing Strategy—Text and Cases. Irwin, Homewood, IL; Hill, T.J., 1994. Manufacturing Strategy—Text and Cases, 2nd edn., Irwin, Homewood, IL], however it was soon evident that additional steps were required. The expanded process we developed both exposed significantly differing views among the managers and raised several questions with important managerial and research implications.

Clinical trials are essential to cancer care, and data about the current state of research in oncology are needed to develop benchmarks and set the stage for improvement.To perform a comprehensive analysis of the national oncology clinical research portfolio.All interventional clinical studies registered on ClinicalTrials.gov between October 2007 and September 2010 were identified using Medical Subject Heading terms and submitted conditions. They were reviewed to validate classification, subcategorized by cancer type, and stratified by design characteristics to facilitate comparison across cancer types and with other specialties.Of 40 970 interventional studies registered between October 2007 and September 2010, a total of 8942 (21.8%) focused on oncology. Compared with other specialties, oncology trials were more likely to be single arm (62.3% vs 23.8%; P.001), open label (87.8% vs 47.3%; P.001), and nonrandomized (63.9% vs 22.7%; P.001). There was moderate but significant correlation between number of trials conducted by cancer type and associated incidence and mortality (Spearman rank correlation coefficient, 0.56 [P = .04] and 0.77 [P = .001], respectively). More than one-third of all oncology trials were conducted solely outside North America.There are significant variations between clinical trials in oncology and other diseases, as well as among trials within oncology. The differences must be better understood to improve both the impact of cancer research on clinical practice and the use of constrained resources.

We have constructed a computer program that allows sequential sets of data from tessellated cellular mosaics to be evaluated such that the presence and position of abnormal cells in the mosaic can be easily, quickly, and quantitatively identified. Conventional parametric analysis of the global morphological organization of large tessellated cellular mosaics does not provide the necessary granularity of analysis to allow for rapid identification of such atypical cellular structures. Our program, written in C using structured programming techniques, provides the needed analytical granularity for detailed studies of subsections of large cellular mosaics, while also providing conventional statistical evaluation of the data set. The architecture of the program is modular and designed as a set of procedures and subprocessess that can either analyze the entire mosaic or discrete sets of cells within the larger sample. The types of morphological heterogeneity (or dishomogeneity) that the program can investigate occur in a variety of biological mosaics where there is a continuum of the structural features, including fairly regular linear stacked arrays of cells or tissue partitions, to less regular mosaics of epithelial or endothelial cell layers, to heterogeneous patterns found on tissue surfaces, such as fluorescein dye-highlighted features on the human conjunctiva. The program has been used to successfully evaluate several different types of mosaics.

While the concepts of design for manufacturability and concurrent engineering have made significant advances in integrating the design function with other areas in the firm, there are still major gaps in timely and accurate costing information available to designers. Our research develops a conceptual model and working prototype of a new application for blending product design and cost accounting, that of automated design-to-cost. The purpose of the application is to provide rapid and dynamic feedback during the design process regarding estimated final product cost of a new part design. The system first calculates the cost of a new part design directly from existing computer-aided design, accounting, and other computer-integrated manufacturing databases. It then finds and displays, along with their costs, all existing parts that are similar or ‘near’ to the proposed part. The model developed was successfully implemented as a prototype. It is able to integrate and process information from the diverse databases of feature-based modelling computer-aided design, group technology classification, computer-aided process planning and activity-based costing. Copyright

Translational research in medicine is facing burdens stemming from an increase in the complexity of science, increase in partnerships across national and international collaborations, and reduction in the finite resources to support all research endeavors. Schools of business offer unique perspectives on translational processes because they address global challenges through research and teaching to transform ideas into successful practice-changing innovations. While there are multiple approaches to investigating translational processes using business management tools, this chapter will focus on three representative lenses: (1) process flows for mass customization, (2) knowledge supply chain, and (3) strategic management. Each lens yields the potential to significantly streamline the translational processes in healthcare for efficiency and effectiveness.

6537Background: Two major barriers to patient clinical trial (CT) participation are lack of awareness of CTs and limited communication from physicians about available trials. Many call for a nation...

In the financial arena, there is a well-known difference between the income statement and the cash flow statement. An income statement provides a financial snapshot of the expected fiscal performance of an organization in a period, whereas a cash flow statement captures the movement of funds in and out of an organization. In a unique piece of research, Seow et al identify the cash flow aspects of clinical research. Specifically, they highlight two important issues with respect to National Cancer Institute (NCI) cooperative group clinical trials: first, that there is a major cost of patient follow-up in such trials that is not being adequately covered by current trial reimbursement, and second, sites may cover this funds shortage by opening new trials, in essence using new trial funds to pay for old trial follow-up. It is well known that cooperative group trials do not cover the total cost of their clinical trials. Until recently, the normal per-case reimbursement was $2,000, which had not changed in nearly a decade, but the actual cost per case ranged from $5,000 to $6,000. One result of this is that one third of 509 sites surveyed by the American Society of Clinical Oncology in 2010 reported that they would limit enrollment to cooperative group trials. Recently it was reported that the NCI intends to develop a plan to increase reimbursement to $4,000 for high performance academic and community sites that enroll a large number of patients to help offset the additional costs that result from increased accruals and large patient follow-up burden. This would be an excellent step in the right direction but ultimately requires either an increase in the NCI budget or a reallocation of scarce, existing NCI resources. Expansion in any US federal agency budget is problematic given that the US Congress has difficulty approving even continuing budget appropriations until the very last moment. If we assume that the NCI budget can be enhanced and that trial reimbursement will increase to a more realistic level, then there is the question of what will be the most likely use of these additional funds. In today’s oncology clinical research environment, there is appropriate pressure to fully characterize study patients, that is, to increase the degree and intensity of tissue collection and molecular testing of those patients who are enrolled onto clinical trials. Such collection and testing will provide important biomarker information for better understanding about treatment effectiveness for specific types of patients. However, collecting such information can be expensive; thus, it is possible that the increased funding could be used for important assessment testing rather than being saved for follow-up costs. As shown by Seow et al, up-front revenues should be saved but are often spent before patient follow-up. If follow-up is not completed, this will limit the value of the initial patient characterization. Perhaps it is time to consider more closely following the pharmaceutical industry model of progress payments. A pay-for-performance system does not give a single blanket payment per enrollee but gives staged payments on the basis of patients’ achievement of specific milestones. From a site perspective, this would allow for a better match with the timing of expenses incurred and reimbursement for those expenses. This would help prevent a site from opening new studies to help pay for the costs of follow-up in previous studies, as shown in Figure 2 in the article by Soew et al. Additionally, it might help to govern the use of any increased funding for a different aspect of the trial. If we assume a status-quo NCI budget or, more realistically, a budget decrease, then it will be increasingly important to select and prioritize trials correctly, which was one of the overarching goals in the 2010 Institute of Medicine report on the NCI Clinical Trials Cooperative Group Program. Sites should be more selective about which trials they open, and cooperative groups should be more selective about which studies to activate. This will mean fewer clinical trials, but such studies should be high-priority, major-impact trials that use innovative concepts and trial designs that enable achievement in a timely manner. Fewer, better characterized studies that are designed to answer important fundamental questions would be the best use of limited resources. In part, it is hoped that the existing merger efforts by multiple cooperative groups will lead to some degree of this prioritization. In an ideal world, there should be a clinical trial for every patient. Unfortunately, that is not the case. In an era of declining budgets, it is important to understand that sites cannot continue to cross-subsidize the follow-up cost outflows of old trials with the reimbursement inflows from the start-up phases of new trials because this only increases the delayed costs. Using financial parlance: this is taking on more new debt to pay off old debt. Or, as delightfully highlighted in the I Love Lucy episode “The Million Dollar Idea,” Lucy and Ethel go into business selling salad dressing, and when Ricky inquires about the economics of it, Lucy replies, “Maybe there is no profit on each individual jar, but we’ll make it up on volume,” to which Ricky replies, “I didn’t figure shipping, mailing, insurance, taxes, or overhead.” Clearly, it is time for all concerned to stop trying to make it up in volume and to understand and fully support the total costs of key clinical trials. JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 30 NUMBER 13 MAY 1 2012

Clinical research is burdened by inefficiencies and complexities, with a poor record of trial completion, none of which is desirable. The Clinical and Translational Science Award (CTSA) Consortium, including more than 60 clinical research institutions, supports a unified national effort to become, in effect, a virtual national laboratory designed to identify, implement, evaluate, and extend process improvements across all parts of clinical research, from conception to completion. If adequately supported by academic health centers, industry, and funding agencies, the Consortium could become a test bed for improvements that can dramatically reduce wasteful complexity, thus increasing the likelihood of clinical trial completion.

Preventing the disclosure, modification or destruction of information in a database has been the subject of considerable recent research (see, for example, [1-3]). While mandatory access control (MAC) assigns security clearance levels (e.g. top secret, secret) to all data for access control, discretionary access control (DAC) assigns privileges to users tailored to their responsibilities within an application. Both of these mechanisms have the fundamental limitation that they are unable to deal with the changing roles of a user (based on the occurrence of an event) within an application. As a result, user-role-based security (URBS) has been proposed [4, 5]. This paper demonstrates how URBS can be used to augment the existing security mechanisms. First the URBS concept, originally proposed for the object-oriented model, is extended to the relational model. Second, the extended model is augmented with the capability to respond to dynamic events. Finally, an integrated method is presented for the design of a dynamic, user-role-based security system.

Purpose: Present the design and initial evaluation of a unique, Web-enabled platform for the development of a community of practice around issues of oncology clinical trial accrual. Methods: The National Cancer Institute (NCI) conducted research with oncology professionals to identify unmet clinical trial accrual needs in thefield. In response, a comprehensive platform for accrual resources, AccrualNet, was created by using an agile development process, storyboarding, and user testing. Literature and resource searches identified relevant content to populate the site. Descriptive statistics were tracked for resource and site usage. Use cases were defined to support implementation. Results: AccrualNet has five levels: (1) clinical trial macrostages (prestudy, active study, and poststudy); (2) substages (developing a protocol, selecting a trial, preparing to open, enrolling patients, managing the trial, retaining participants, and lessons learned); (3) strategies for each substage; (4) multiple activities for each strategy; and (5) multiple resources for each activity. Since its launch, AccrualNet has had more than 45,000 page views, with the Tools & Resources, Conversations, and Training sections being the most viewed. Total resources have increased 69%, to 496 items. Analysis of articles in the site reveals that 22% are from two journals and 46% of the journals supplied a single article. To date, there are 29 conversations with 43 posts. Four use cases are discussed. Conclusion: AccrualNet represents a unique, centralized comprehensive-solution platform to systematically capture accrual knowledge for all stages of a clinical trial. It is designed to foster a community of practice by encouraging users to share additional strategies, resources, and ideas.

Purpose: The Institute of Medicine report on cooperative groups and the National Cancer Institute (NCI) report from the Operational Efficiency Working Group both recommend changes to the processes for opening a clinical trial. This article provides evidence for the need for such changes by completing the first comprehensive review of all the time and steps required to open a phase III oncology clinical trial and discusses the effect of time to protocol activation on subject accrual. Methods: The Dilts and Sandler method was used at four cancer centers, two cooperative groups, and the NCI Cancer Therapy Evaluation Program. Accrual data were also collected. Results: Opening a phase III cooperative group therapeutic trial requires 769 steps, 36 approvals, and a median of approximately 2.5 years from formal concept review to study opening. Time to activation at one group ranged from 435 to 1,604 days, and time to open at one cancer center ranged from 21 to 836 days. At centers, group trials are significantly more likely to have zero accruals (38.8%) than nongroup trials (20.6%; P < 0.0001). Of the closed NCI Cancer Therapy Evaluation Program–approved phase III clinical trials from 2000 to 2007, 39.1% resulted in Conclusions: The length, variability, and low accrual results demonstrate the need for the NCI clinical trials system to be reengineered. Improvements will be of only limited effectiveness if done in isolation; there is a need to return to the collaborative spirit with all parties creating an efficient and effective system. Recommendations put forth by the Institute of Medicine and Operational Efficiency Working Group reports, if implemented, will aid this renewal. Clin Cancer Res; 16(22); 5381–9. ©2010 AACR.

Cancer clinical trials in the US are at a major crossroads. Current government-sponsored research is some of the best in the world, but the field shares a worrying number of similarities with the American auto industry in its heyday. For clinical research to survive, the field must transform itself now to prevent a similar decline.