Poronui Associate Professor of Business Administration
Ariel Dora Stern is an Associate Professor of Business Administration in the Technology and Operations Management Unit at Harvard Business School. She co-teaches Transforming Health Care Delivery in the MBA elective curriculum.
Ariel's research focuses on the management of innovation in health care, with a focus on the medical device and pharmaceutical industries. Her projects seek to understand the drivers of innovation among firms and the determinants of how medical technologies are adopted and used in practice. Ariel is particularly interested in the intersection of the regulation, firm strategy, and economics of health care. She also researches the digital transformation of medical technology and health care delivery, investigating the policy and managerial questions raised by the growth of “digital health.” Her research has been cited by Bloomberg, The New York Times, and National Public Radio.
Ariel Dora Stern is an Associate Professor of Business Administration in the Technology and Operations Management Unit at Harvard Business School. She co-teaches Transforming Health Care Delivery in the MBA elective curriculum.
Ariel's research focuses on the management of innovation in health care, with a focus on the medical device and pharmaceutical industries. Her projects seek to understand the drivers of innovation among firms and the determinants of how medical technologies are adopted and used in practice. Ariel is particularly interested in the intersection of the regulation, firm strategy, and economics of health care. She also researches the digital transformation of medical technology and health care delivery, investigating the policy and managerial questions raised by the growth of “digital health.” Her research has been cited by Bloomberg, The New York Times, and National Public Radio.
Professor Stern received her Ph.D. in Public Policy from Harvard, where she was a National Bureau of Economic Research Predoctoral Fellow in the Economics of Health and Aging and was honored with the Harvard Kennedy School Dean’s Award for excellence in student teaching. She holds an undergraduate degree in economics from Dartmouth College, where she was a Presidential Scholar and a two-time U.S. national collegiate figure skating champion. Before beginning her academic career, she worked as an economist on Wall Street and at the Federal Reserve Bank of New York, the German Institute for Economic Research (DIW), the German Development Bank (KfW), and LeapFrog Investments, an impact investment fund.
Ariel is currently a faculty affiliate of the Harvard Business School Health Care Initiative and Digital Initiative and a Research Associate at Ariadne Labs, a joint center between the Brigham and Women’s Hospital and the Harvard T.H. Chan School of Public Health, which focuses on scaling health care delivery innovation.
In recent years, the applications of Machine Learning (ML) in the health care delivery setting have grown to become both abundant and compelling. Regulators have taken notice of these developments and the U.S. Food and Drug Administration (FDA) has been engaging actively in thinking about how best to facilitate safe and effective use. Although the scope of its oversight for software-driven products is limited, if FDA takes the lead in promoting and facilitating appropriate applications of causal inference as a part of ML development, that leadership is likely to have implications well beyond regulated products.
Peter P. Monteleone, Subhash Banerjee, Priya Kothapalli, Ariel Dora Stern, Daniel Fehder, Ron Ginor, Dominic Vollmar, Edward T. A. Fry and Mark J. Pirwitz
Background. A meta-analysis of trials in endovascular therapy suggested an increased mortality associated with treatment exposure to paclitaxel. Multiple publications and corrections of prior data were performed, and the United States Food and Drug Administration has issued multiple advisories regarding paclitaxel use. We analyzed how this controversy impacted device purchasing and related utilization patterns in the period immediately following publication of the meta-analysis.
Methods and Results. Ascension Healthcare System purchase data over a 14-month period were synthesized across centers for both paclitaxel and non-paclitaxel devices. A fixed-effects regression model and a binary regression model with facility-level controls were used to compare purchasing patterns before and after the meta-analysis. Purchase volumes of each paclitaxel device fell. Pooled purchase volumes of all paclitaxel devices decreased from a 14-month peak of 631 devices in October 2018 to a 14-month nadir of 359 devices in February 2019. An F-test comparing the pooled-month specific fixed effects for the months before vs. after the publication of the meta-analysis has an F-statistic of 11.64, suggesting that average purchasing levels in the two periods are statistically different (P<.001). Utilization of non-paclitaxel devices did not decline.
Conclusions. Purchase volumes of paclitaxel devices decreased immediately during the months following publication of the related meta-analysis. Total Ascension-wide paclitaxel device purchase volume in February 2019 demonstrated a 43.1% reduction from peak monthly purchase volume during the assessed period and a 32.5% reduction compared with November 2019, the last month preceding publication of the meta-analysis.
Samantha F. Sanders, Mats Terwiesch, William J. Gordon and Ariel Dora Stern
The development of intelligent machines holds great promise for making health care delivery more accurate, efficient, and accessible, but challenges remain for incorporating AI into clinical and administrative settings.
The use of biomarkers holds great promise for the development of new therapeutics and the acceleration of clinical research. However, biomarkers must be validated—a complex and costly endeavor. Importantly, biomarker validation is meaningfully shaped by economic and policy-driven incentives.
Derek C. Angus, Brian M. Alexander, Scott Berry, Meredith Buxton, Roger Lewis, Melissa Paoloni, Steven A. R. Webb, Steven Arnold, Anna Barker, Donald A. Berry, Marc J. M. Bonten, Mary Brophy, Christopher Butler, Timothy F. Cloughesy, Lennie P. G. Derde, Laura J. Esserman, Ryan Ferguson, Louis Fiore, Sarah C. Gaffey, J. Michael Gaziano, Kathy Giusti, Herman Goossens, Stephane Heritier, Bradley Hyman, Michael Krams, Kay Larholt, Lisa M. LaVange, Philip Lavori, Andrew W. Lo, Alexander J. London, Victoria Manax, Colin McArthur, Genevieve O’Neill, Giovanni Parmigiani, Jane Perlmutter, Elizabeth A. Petzold, Craig Ritchie, Kathryn M. Rowan, Christopher W. Seymour, Nathan I. Shapiro, Diane M. Simeone, Bradley Smith, Bradley Spellberg, Ariel Dora Stern, Lorenzo Trippa, Mark Trusheim, Kert Viele, Patrick Y. Wen and Janet Woodcock
Researchers, clinicians, policymakers, and patients are increasingly interested in questions about therapeutic interventions that are difficult or costly to answer with traditional, free-standing, parallel-group randomized controlled trials (RCTs). Examples include scenarios in which there is a desire to compare multiple interventions, to generate separate effect estimates across subgroups of patients with distinct but related conditions or clinical features, or to minimize downtime between trials. In response, researchers have proposed new RCT designs such as adaptive platform trials (APTs), which are able to study multiple interventions in a disease or condition in a perpetual manner, with interventions entering and leaving the platform on the basis of a predefined decision algorithm. APTs offer innovations that could reshape clinical trials, and several APTs are now funded in various disease areas. With the aim of facilitating the use of APTs, here we review common features and issues that arise with such trials and offer recommendations to promote best practices in their design, conduct, oversight, and reporting.
Angus, Derek C., Brian M. Alexander, Scott Berry, Meredith Buxton, Roger Lewis, Melissa Paoloni, Steven A. R. Webb, Steven Arnold, Anna Barker, Donald A. Berry, Marc J. M. Bonten, Mary Brophy, Christopher Butler, Timothy F. Cloughesy, Lennie P. G. Derde, Laura J. Esserman, Ryan Ferguson, Louis Fiore, Sarah C. Gaffey, J. Michael Gaziano, Kathy Giusti, Herman Goossens, Stephane Heritier, Bradley Hyman, Michael Krams, Kay Larholt, Lisa M. LaVange, Philip Lavori, Andrew W. Lo, Alexander J. London, Victoria Manax, Colin McArthur, Genevieve O’Neill, Giovanni Parmigiani, Jane Perlmutter, Elizabeth A. Petzold, Craig Ritchie, Kathryn M. Rowan, Christopher W. Seymour, Nathan I. Shapiro, Diane M. Simeone, Bradley Smith, Bradley Spellberg, Ariel Dora Stern, Lorenzo Trippa, Mark Trusheim, Kert Viele, Patrick Y. Wen, and Janet Woodcock. "Adaptive Platform Trials: Definition, Design, Conduct and Reporting Considerations."Nature Reviews: Drug Discovery (forthcoming). (Pre-published online August 28, 2019.)
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The safety and security of medical devices driven by software, the software-development processes, and the need for data collection and privacy, all offer challenges and opportunities for device regulation and clinical care.
Ariel Dora Stern, Felicitas Pietrulla, Annika Herr, Aaron S. Kesselheim and Ameet Sarpatwari
The 2011 German Pharmaceutical Market Restructuring Act (“AMNOG”) subjected branded, non-rare disease drugs to price regulation based on an assessment of their clinical benefit. Assessment outcomes range from “major added benefit” to “less benefit than the appropriate comparator,” and impact price negotiations beyond the first year on the market. Using data on drugs that entered the market from 2012 to 2016, we evaluated benefit assessment findings, subsequent drug exits, and their correlates. We considered 171 drug-indication pairs, corresponding to 138 different drugs. Of these, 66 drug-indication pairs (55 different drugs) were found to have any additional benefit. Almost all drugs with any positive benefit assessment (98%) remained on the market, while drugs without a positive benefit assessment were over ten times more likely to exit (25% vs. 2%). U.S. policymakers considering how to address rapidly increasing drug costs may draw valuable lessons from the German experience.
Ariel Dora Stern, William J. Gordon, Adam B. Landman and Daniel B. Kramer
Objectives:
To more clearly define the landscape of digital medical devices subject to U.S. Food and Drug Administration (FDA) oversight, this analysis leverages publicly available regulatory documents to characterise the prevalence and trends of software and cybersecurity features in regulated medical devices.
Design:
We analysed data from publicly available FDA product summaries to understand the frequency and recent time trends of inclusion of software and cybersecurity content in publicly available product information.
Setting:
The full set of regulated medical devices, approved over the years 2002–2016, included in the FDA’s 510(k) and premarket approval databases.
Primary and secondary outcome measures: The primary outcome was the share of devices containing software that included cybersecurity content in their product summaries. Secondary outcomes were differences in these shares (a) over time and (b) across regulatory areas.
Results:
Among regulated devices, 13.79% were identified as including software. Among these products, only 2.13% had product summaries that included cybersecurity content over the period studied. The overall share of devices including cybersecurity content was higher in recent years, growing from an average of 1.4% in the first decade of our sample to 5.5% in 2015 and 2016, the most recent years included. The share of devices including cybersecurity content also varied across regulatory areas from a low of 0% to a high of 22.2%.
Conclusions:
To ensure the safest possible health care delivery environment for patients and hospitals, regulators and manufacturers should work together to make the software and cybersecurity content of new medical devices more easily accessible.
As pressure mounts on the Food and Drug Administration (FDA) to speed its review process for novel devices, and budgetary pressures further strain its resources, the critical role of guidance documents in assuring consistent, rigorous, and scientifically grounded review across device types has never been more important. In this article, we use the regulatory experience of one medical device class, specifically implantable breast prostheses, to illustrate the crucial role of FDA guidance documents. We find that the emergence of FDA guidance preceded significant growth of scientific publications around breast prostheses, with 0.30 +/- 0.57 papers/year published in the period 1987–2006 compared with 2.27 +/- 1.56 papers/year in the period 2007–2017, P=0.0017. This illustrates the importance of supporting the FDA to enhance guidance document drafting, revision, publication, and updating to reflect evolving scientific consensus and the needs of sponsors, regulators, and patients for transparent and consistent standards in a broad range of fields.
David Cutler, Jonathan Skinner, Ariel Dora Stern and David Wennberg
There is considerable controversy about the causes of regional variations in health care expenditures. Using vignettes from patient and physician surveys linked to fee-for-service Medicare expenditures, this study asks whether patient demand-side factors or physician supply-side factors explain these variations. The results indicate that patient demand is relatively unimportant in explaining variations. Physician organizational factors matter, but the most important factor is physician beliefs about treatment. In Medicare, we estimate that 35% of spending for end-of-life care and 12% of spending for heart attack patients (and for all enrollees) is associated with physician beliefs unsupported by clinical evidence.
Biologics represent a substantial and growing share of the U.S. drug market. Traditional “small molecule” generics quickly erode the price and share of the branded product upon entry; however, only a few biosimilars have been approved in the U.S. since 2015, thereby largely preserving biologics from competition. We analyze European markets, which have had biosimilar competition since 2006. Using our own survey, we analyze how market features and public policies predict biosimilar entry, price, and penetration, finding significant heterogeneity across countries and products. Effective buyer institutions are associated with increased biosimilar penetration. Our estimates can inform ongoing policy discussions.
The introduction of new medical devices has transformed cardiovascular care in recent decades. Devices, such as heart valves, pacemakers, stents, ventricular assist devices, and implantable defibrillators, have prolonged and improved the quality of life for millions of patients worldwide. Medical device innovation requires a robust ecosystem that involves medical technology innovators, often at start-ups, large medical device manufacturers, and clinical investigators. Central to this process is strong regulatory oversight, which in the United States is provided by the U.S. Food and Drug Administration’s Center for Devices and Radiologic Health (FDA/CDRH). This viewpoint discusses the effect of the regulatory approval process and the role that FDA/CDRH plays in the design and execution of the pivotal trials (clinical studies) that are used to support the regulatory approval of high-risk devices. We also review norms in the publication of pivotal trials in peer-reviewed medical journals; these publications often fail to acknowledge the role of the FDA/CRH or discuss results within the context of the device approval process.
Previously, we have discussed the importance of economic incentives in shaping markets for precision medicines. Here we consider incentives for biomarker development, including discovery and establishment. Biomarkers can reveal valuable information regarding diagnosis and prognosis, predict treatment efficacy or toxicity, serve as markers of disease progression, and serve as auxiliary endpoints for clinical trials. Some have multiple uses, while others have a specialized role, resulting in diverse incentives across players in the healthcare system.
Many public and private efforts in coming years will focus on research in precision medicine, developing biomarkers to indicate which patients are likely to benefit from a certain treatment so that others can be spared the cost—financial and physical—of being treated with unproductive therapies while more easily uncovering therapeutic signals. However, such research initiatives alone will not deliver new medicines to patients in the absence of strong incentives to bring new products to market. We examine the unique economics of precision medicines and associated biomarkers, placing an emphasis on the factors affecting their development, pricing, and access.
This paper explores how the regulatory approval process affects innovation incentives in medical technologies. Prior studies have found early mover regulatory advantages for drugs. I find the opposite for medical devices, where pioneer entrants spend 34% (7.2 months) longer than follow-on entrants in regulatory approval. Back-of-the-envelope calculations suggest that the cost of a delay of this length is upwards of 7% of the total cost of bringing a new high-risk device to market. Considering potential explanations, I find that approval times are largely unrelated to technological novelty but are meaningfully reduced by the publication of objective regulatory guidelines. Finally, I consider how the regulatory process affects small firms' market entry patterns and find that small firms are less likely to be pioneers in new device markets, a fact consistent with relatively higher costs of doing so for more financially constrained firms.
Malinda S. Lee, Brady T. Evans, Ariel Dora Stern and Mark D. Hornstein
Objective: To estimate the national cost savings resulting from reductions in higher-order multiple (HOM) live births (defined as three or more fetuses), following the initial publication of the Society for Assisted Reproductive Technology (SART) guidelines on ET in 1998. Design: Descriptive use and cost analysis. Main Outcome Measure(s): Estimates of the total number of HOM deliveries prevented (from 1998 to 2012) following the publication of SART guidelines; the associated healthcare savings (2014 U.S. dollars). Result(s): A singleton live birth was estimated to cost $17,100–$24,200. A twin live birth was estimated at $66,000–$117,500. A triplet live birth was estimated at $190,800–$456,300. The percentage of HOM gestations among all ART pregnancies decreased from 11.4% in 1997 to 2.0% in 2012, with the sharpest year-over-year decline of 20.3% occurring in the year following the publication of the guidelines. The number of prevented HOM deliveries from 1998 through 2012 was estimated to be between 13,500 and 16,300, corresponding to cost savings of $6.02B (billion) (range, $2.35B–$7.03B, 2014 U.S. dollars). Conclusion(s): Iatrogenic HOM gestations represent a substantial economic burden to our healthcare system. The introduction of guidelines for ET in 1998 coincided with a dramatic decrease in the HOM rate in subsequent years and an associated cumulative cost savings of more than $6B. Further reductions in HOM gestations could save up to an additional $2B annually.
Only a few rich nations are currently at replacement levels of fertility and many are considerably below. We believe that changes in the status of women are driving fertility change. At low levels of female status, women specialize in household production and fertility is high. In an intermediate phase, women have increasing opportunities to earn a living outside the home yet still shoulder the bulk of household production. Fertility is at a minimum in this regime due to the increased opportunity cost in women's foregone wages with no decrease in time allocated to childcare. We see the lowest fertility nations (Japan, Spain, Italy) as being in this regime. At even higher levels of women's status, men begin to share in the burden of child care at home and fertility is higher than in the middle regime. This progression has been observed in the US, Sweden and other countries. Using ISSP and World Values Survey data we show that countries in which men perform relatively more of the childcare and household production (and where female labor force participation was highest 30 years ago) have the highest fertility within the rich country sample. Fertility and women's labor force participation have become positively correlated across high income countries. The trend in men's household work suggests that the low fertility countries may see increases in fertility as women's household status catches up to their workforce opportunities.
We also note that as the poor nations of the world undergo the demographic transition they appear to be reducing fertility faster and further than the current rich countries did at similar levels of income. By examining fertility differences between the rich nations we may be able to gain insight into where the world is headed.
Summer Sherburne Hawkins, Ariel Dora Stern, Christopher F. Baum and Matthew W. Gillman
Objectives: Despite the passage of state laws promoting breast feeding, a formal evaluation has not yet been conducted to test whether and/or what type of laws may increase breast feeding. The enactment of breastfeeding laws in different states in the USA creates a natural experiment. We examined the impact of state breastfeeding laws on breastfeeding initiation and duration as well as on disparities in these infant feeding practices.
Methods: Using data from the Pregnancy Risk Assessment Monitoring System, we conducted differences-in-differences models to examine breastfeeding status before and after the institution of laws between 2000 and 2008 among 326,263 mothers from 32 states in the USA. For each mother, we coded the presence of two types of state breastfeeding laws. Mothers reported whether they ever breast fed or pumped breast milk (breastfeeding initiation) and, if so, how long they continued. We defined breastfeeding duration as continuing to breast feed for ≥4 weeks.
Results: Breastfeeding initiation was 1.7 percentage points higher in states with new laws to provide break time and private space for breastfeeding employees (p=0.01), particularly among Hispanic mothers (adjusted coefficient 0.058). While there was no overall effect of laws permitting mothers to breast feed in any location, among Black mothers we observed increases in breastfeeding initiation (adjusted coefficient 0.056). Effects on breastfeeding duration were in the same direction, but slightly weaker.
Conclusions: State laws that support breast feeding appear to increase breastfeeding rates. Most of these gains were observed among Hispanic and Black women and women of lower educational attainment suggesting that such state laws may help reduce disparities in breast feeding.
Hanna I. Hyry, Ariel Dora Stern, Jonathan CP Roos and Timothy M. Cox
Funding of expensive treatments for rare ('orphan') diseases is contentious. These agents fare poorly on 'efficiency' or health economic measures, such as the QALY, because of high cost and frequently poor gains in quality of life and survival. We show that cost-effectiveness assessments are flawed, and have only a limited role to play in reimbursement decisions for orphan drugs and beyond.
BOOK ABSTRACT: Personalized and precision medicine (PPM)—the targeting of therapies according to an individual’s genetic, environmental, or lifestyle characteristics—is becoming an increasingly important approach in health care treatment and prevention. The advancement of PPM is a challenge in traditional clinical, reimbursement, and regulatory landscapes because it is costly to develop and introduces a wide range of scientific, clinical, ethical, and socioeconomic issues. PPM raises a multitude of economic issues, including how information on accurate diagnosis and treatment success will be disseminated and who will bear the cost; changes to physician training to incorporate genetics, probability and statistics, and economic considerations; questions about whether the benefits of PPM will be confined to developed countries or will diffuse to emerging economies with less developed health care systems; the effects of patient heterogeneity on cost-effectiveness analysis; and opportunities for PPM’s growth beyond treatment of acute illness, such as prevention and reversal of chronic conditions. This volume explores the intersection of the scientific, clinical, and economic factors affecting the development of PPM, including its effects on the drug pipeline, on reimbursement of PPM diagnostics and treatments, and on funding the requisite underlying research. The research also examines recent empirical applications of PPM.
Chandra, Amitabh, Craig Garthwaite, and Ariel Dora Stern. "Characterizing the Drug Development Pipeline for Precision Medicines." Chap. 5 in Economic Dimensions of Personalized and Precision Medicine, edited by Ernest R. Berndt, Dana P. Goldman, and John W. Rowe, 115–158. University of Chicago Press, 2019.
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Nicholas Bagley, Benjamin Berger, Amitabh Chandra, Craig Garthwaite and Ariel Dora Stern
On the 35th anniversary of the adoption of the Orphan Drug Act (ODA), we describe the enormous changes in the markets for therapies for rare diseases that have emerged over recent decades. The most prominent example is the fact that the profit-maximizing price of new orphan drugs appears to be greater today than it was in 1983. All else being equal, this should reduce the threshold for research and development (R&D) investment in an economically viable product. Further, the small size of patient populations for orphan drugs, together with the increasing prevalence of biologics among orphan drugs, have created a set of natural monopoly-like markets in which firms face little competition, even after the end of formal periods of patent protection and market exclusivity. Additionally, the evolving technologies of drug development—in particular, the increasingly common use of auxiliary endpoints in clinical trials and the use of biomarkers for patient selection for treatment—now allow manufacturers to target smaller populations. Taken together, these changes raise doubts about whether the ODA encourages the development of products that otherwise would not have been brought to market—or whether, instead, it simply rewards the producers of inframarginal products. After presenting empirical support for our claims of an evolving marketplace, we discuss the tradeoffs associated with reshaping the ODA for the 21st century.
Does the large-scale technological change that is characteristic of an industry-wide digital transformation entrench industry leaders or enable the rise of new entrants? We offer a novel approach to this question by studying the medical device industry, a unique setting in which we observe all new product commercialization over several years and in which the introduction of software has created fresh opportunities for new product development. Pioneering a new application of text analysis, we consider over 35,000 new medical devices that came to market in the United States from 2002 to 2016 in order to identify digital products. We examine the relative importance of within-firm know-how, geography, and financial resources in predicting digital new product development. We find that prior product-area commercialization experience and location in a region of concentrated expertise reinforce one another as predictors of digital innovation. Access to financing through public capital markets and venture capital are also positive predictors, but the magnitudes of these effects are smaller and do not appear to compensate for past product experience or geography. We conclude that the digital transformation of the medical device industry is disproportionately driven by product area and geographic incumbents.
This study sheds new light on first- and early-mover advantages in the context of product innovation. Research on this classic topic often assumes that each firm participates in the entire innovation process. However, a division of labor between innovative new entrants and incumbents with complementary assets is common in many industries. In such settings, small new entrants have the additional option to be acquired in a “market for technology.” Using data from the U.S. medical device industry, we find that pioneers “pave the way” for a new product type to reduce the technological and market risks, where the former is of paramount importance. Although pioneers ultimately realize a higher likelihood of acquisition, they wait longer to be acquired. Therefore, to some extent, later movers can free ride on early-movers’ efforts.
Innovation and new product development are the lifeblood of firms in R&D-intensive industries, yet malfunctioning products can cause immense damage. Product failures thus create managerial challenges and opportunities for focal firms and their competitors. Focal firm failures often result in sales decreases and cost increases associated with remedial public relations and manufacturing activities. Competitor firm failures, however, can create market opportunities and elicit strategic responses by focal firms. We develop theory and provide empirical evidence of how innovative activity changes in response to product recalls in the U.S. medical device industry. Focal firm recalls slow incremental innovation while competitor firm recalls accelerate incremental and major innovation. Recall prevention and remediation efforts are thus more important than previously suggested, due to significant competitor responses.
This Technical Note provides an introduction to Bayes’ Rule and the statistical intuition that stems from it. In this note, we review the concepts that underlie Bayesian statistics, and we offer several simple mathematical examples to illustrate applications of Bayes’ Rule. Instructors can assign this note either as a standalone reading to familiarize students with Bayesian statistics or as a supplement to accompany “Adaptive Platform Trials: The Clinical Trial of the Future?” (HBS Case No. 618-025). This case introduces the concept of an adaptive platform clinical trial, in which Bayesian statistical methods are used to expedite the investigation and regulatory approval of promising new therapies, such as cancer treatments.
Chandra, Amitabh, and Ariel Dora Stern. "Technical Note on Bayesian Statistics and Frequentist Power Calculations." Harvard Business School Technical Note 620-032, December 2019.
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This case provides an update to the (A) case, which introduces students to adaptive platform trials, an ambitious, more efficient type of clinical trial that increases access to therapies. The A case centers on Dr. Brian Alexander’s efforts to launch an adaptive platform trial for studying potential therapies for glioblastoma (GBM), an aggressive form of brain cancer. The (B) case provides an update and explores the strategies that Alexander is considering for sustainably financing this trial.
Stern, Ariel D., and Sarah Mehta. "Adaptive Platform Trials: The Clinical Trial of the Future? (B)." Harvard Business School Case 620-001, September 2019.
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In September 2018, the executive team at Ariadne Labs (Ariadne), a Boston-based organization dedicated to improving health systems through the discovery and implementation of simple tools, faced a number of strategic decisions. Chief among them, the seven-year-old organization needed to determine how it might establish and shepherd successful partnerships with a wide range of diverse entities—ranging from major international public health organizations like the World Bank to small non-profit implementing organizations.
In late 2014, Dr. John Moore (CEO), Frank Moss (chairman), and Scott Gilroy (CTO) of Twine Health (Twine) had to resolve several challenges that threatened to restrict the widespread dissemination of its sole product, Twine. Twine was a cloud-based platform that enabled patients to create and manage chronic disease treatment plans in conjunction with their primary care providers and specialized coaches. Twine had already enjoyed impressive successes in early clinical trials and among early adopters. The issues Twine's leadership team had to address included identifying clinical care providers willing to pay for Twine, ensuring adoption and effective use by both patients and health care providers, adding capabilities to support the management of additional chronic diseases, and seamlessly integrating Twine with a client organization's electronic medical record (EMR) system and information technology (IT) infrastructure. The need to solve these problems had become more pressing since Twine was named a finalist in the Health Acceleration Challenge (HAC) sponsored by Harvard Business School and Harvard Medical School.
In late 2014, Dr. John Moore (CEO), Frank Moss (chairman), and Scott Gilroy (CTO) of Twine Health (Twine) had to resolve several challenges that threatened to restrict the widespread dissemination of its sole product, Twine. Twine was a cloud-based platform that enabled patients to create and manage chronic disease treatment plans in conjunction with their primary care providers and specialized coaches. Twine had already enjoyed impressive successes in early clinical trials and among early adopters. The issues Twine's leadership team had to address included identifying clinical care providers willing to pay for Twine, ensuring adoption and effective use by both patients and health care providers, adding capabilities to support the management of additional chronic diseases, and seamlessly integrating Twine with a client organization's electronic medical record (EMR) system and information technology (IT) infrastructure. The need to solve these problems had become more pressing since Twine was named a finalist in the Health Acceleration Challenge (HAC) sponsored by Harvard Business School and Harvard Medical School. Teaching Note for HBS No. 615-068.
In July 2017, Dr. Brian M. Alexander, president and CEO of the AGILE Research Foundation, was preparing to launch a new type of clinical trial—an adaptive platform trial—to study potential therapies for glioblastoma (GBM), an aggressive form of brain cancer.
Alexander believed that the standard way in which new cancer drugs were tested—the traditional randomized controlled trial (RCT)—was limited in many ways. While statistically rigorous and still considered the “gold standard” in clinical research, traditional RCTs were time-consuming, costly, and limited to testing just one new drug at a time. Adaptive platform trials, by contrast, facilitated simultaneously studying multiple therapies for a given disease and promised a number of efficiency improvements. They also used statistical techniques to allow more patients access to promising therapies. As such, they had the potential to fundamentally change the clinical research process, making clinical trials for new cancer drugs more efficient, more accessible to patients, and more ambitious in scope.
For the past three years, Alexander had been working closely with a group of like-minded oncologists, statisticians, and clinical trial strategists to design an adaptive platform trial for GBM in the hopes of identifying effective therapies more quickly. By mid-2017, Alexander and his colleagues had completed a master protocol for the trial. But now the research team faced several design and operational challenges as they prepared for the trial’s launch. Most pressing, how should Alexander and his colleagues finance the trial?
This teaching note provides guidance and recommendations for teaching HBS Case No. 618-025, entitled “Adaptive Platform Trials: The Clinical Trial of the Future?”
Stern, Ariel D., and Sarah Mehta. "Adaptive Platform Trials: The Clinical Trial of the Future?" Harvard Business School Teaching Note 618-048, March 2018.
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