Coherence is the essence of everything successful. Then we add integrity.

October 2015

Survival guide to stem cell research and therapies

29. october 2015 at 15:51 | Veronika Valdova, ARETE-ZOE |  Medicine & Pharmacy
Learn how to find and utilize publicly available information to make better treatment decisions.

Survival guide to stem cell research and therapies provides comprehensive guidance to publicly available resource materials, libraries and registries for people who are interested in currently available treatment options involving human stem cells.

The first section explains how stem cells are currently used in research, drug testing, and therapy, and how they have to be manipulated before transfer to make any treatments possible.

Origin and ability of stem cells to differentiate into different cell types determines how different types of stem cells are typically used.

In this section, we will introduce two most important registries of clinical trials: NIH registry and WHO International Clinical Trials Registry Platform. A project is part of this section to give students the opportunity to get hands on experience with collecting and collating relevant information from registries and libraries, and interpretation of the findings. Real time interactive sessions are included to allow students to ask questions and offer additional guidance.

In this section, we briefly introduce challenges relating to marketing claims, objective outcome measures, advertising strategies and patient autonomy.

Stem cell therapies are regulated differently in various countries around the world. In this section, we will focus on regulations that govern stem cell research and therapies in the U.S. and in the European Union. Policies on stem cell research are driven by ethical concerns relating to research that utilizes human embryos. China recently announced new ethical guidelines and new rules for their stem cell clinics, regulating both trials and treatments.

The last section explains the role of professional societies in stem cell research and therapies.

Resources included in this course can be obtained from various libraries free of charge and are available for download for students enrolled in this course.

Available at Udemy

Review: Integrating Research and Practice 2/2

25. october 2015 at 8:00 | Veronika Valdova, ARETE-ZOE |  Medicine & Pharmacy

Institutional governance of continuous learning activities that can accelerate progress and sustainability was the focus of a panel of brief presentations by James Rohack (Baylor Scott & White Health), Mary Brainerd (HealthPartners), and John Steiner (Institute for Health Research at Kaiser Permanente Colorado) (p 86).

John Steiner (Kaiser Permanente National Research Council and the HMO Research Network governing board) noted that transformation of research can only occur through transformation of governance. Research studies, he said, need to be larger, of higher quality, using trustworthy, high-quality data and better analytic methods while achieving or maintaining regulatory and fiscal compliance. He also stressed that research needs to be faster, in terms of initiating studies, organizing the contractual relationship between collaborators, and getting studies approved by IRBs; less expensive and more engaging, and has to rely on data collected during the course of routine care (p 92).

In section Fostering the well-prepared stakeholder culture Peter Knox presented Bellin Health's high-performance health care model. This framework holds that for an organization to execute effectively it must think about six dimensions: strategic position (understanding the market, the value proposition, and focus on patients' important priorities); production system or organizational structure that delivers on the specifications; and a system of measurement that provides insights into how the system is performing. Only then is it time to create a system of improvement, marketing the product, that is to give individual patients diagnosis-to-treatment options within 3days, and finally a high-performance culture that supports creating value at speed (p 98).

According to Patrick Conway, sustainability requires that learning become part of the fabric of care and that health care organizations embrace infrastructure support as essential to their survival. Additionally, infrastructure needs to become part of the financial model in a way that enables investments in the research infrastructure that will drive continuous learning to improve population health and the efficiency of care delivery (p 109).

Scott Armstrong stressed that an organization can foster a culture in which its leadership team and medical professionals work together consistently to create a virtuous cycle between research and operations to create value at speed (p 109). John Warner added that PCORnet represents an opportunity to build the infrastructure needed to maximize return on the huge investment that health systems have made in EHRs (p 109).

As Jonathan Perlin said, there is a strong business case for health care systems that have already made significant investments in information technologies to support research networks. These networks allow the systems to leverage their investments by investigating questions that can be best addressed using data from multiple organizations. Raymond Baxter added that because organizations have a limited supply of intellectual capital, it should be spent on research that produces change for patients; and that the barometer for success is the speed at which research results produce changes in care and outcome (p 119).

According to David Labby, there is a concern about the biases inherent in using observational data and about the generalizability and scalability of results. Steven Corwin said that

"Taking cost out of the system will not happen without moving toward population health and providing value, and both of those steps require knowledge of the sort that a learning health system can produce. In the absence of knowledge to refine the blunt measurement of cost and utilization, the health care system will bifurcate into one that has hospitals that treat the "haves" and hospitals that treat the "have nots," which would be problematic for the country as a whole. Privacy and security issues need to be addressed in a way that balances the need for transparency with the concerns of liability" (p 120).

From the presented materials it is apparent that there is a strong business case for the utilization of various tools which facilitate learning of healthcare organizations toward improvement of patient outcomes. Tendency toward observational research within real-life context is becoming a trend that may substantially transform clinical research toward greater integration with care. The workshop summary is an essential resource for those who need to stay on top of the latest trends in clinical research.

Review: Integrating Research and Practice 1/2

25. october 2015 at 8:00 | Veronika Valdova, ARETE-ZOE |  Medicine & Pharmacy

Review:Integrating Research and Practice:Health System Leaders Working Toward High-Value Care: Workshop Summary (2015)

The Institute of Medicine Roundtable on Value & Science-Driven Health Care introduced an intriguing vision of
"a continuously learning health system in which science, informatics, incentives, and culture are aligned for continuous improvement and innovation, with best practices seamlessly embedded in the care process, patients and families active participants in all elements, and new knowledge captured as an integral by-product of the care experience" (p xi).

The authors argue that care is often not relevant due to failure to apply the evidence about treatment efficacy as a result of lack of knowledge, accountability, coordination support or insurance, or as the result of misplaced patient expectations (p xi), and that datasets generated through the normal course of health care offer great potential for achieving the "triple aim"-improved care, better health for populations, and reduced health care costs (p 1).

The main topics discussed in the book are: Continuous learning and improvement in healthcare, integration of clinical research and practice, sustainability, regulatory oversight and its challenges, and stakeholder culture which accommodates culture of learning and patient and clinician engagement. Continuous learning of organizations is then seen as the utmost priority.

Efforts to share information across systems are designed to compare data for quality improvement, benchmarking, for public health and drug safety surveillance (e.g. Mini-Sentinel), for the conduct of pragmatic clinical trials, or comparative effectiveness research (CER) through PCORnet (p 3).

In another workshop, Raymond Baxter and Elizabeth McGlynn described the PORTAL network developed by Kaiser Permanente which sees research as a critical part of its strategy (p 21).

"PORTAL's contract with PCORnet focuses its efforts on three specific groups of its 11 million patients: colorectal cancer patients, with an emphasis on treatment and how patients navigate survivorship; 330 adolescents and adults with severe congenital heart disease; and obesity in adults" (p 24).

In workshops relating to the integration of clinical research and practice the speakers introduced among other projects REDUCE MRSA trial (p 46), Improve Care Now Network created to transform care for children with inflammatory bowel disease (p 48), and embedding research into clinical care at Group Health, a nonprofit health system with about 600,000 members in Washington State (p 50).

In a discussion on learning healthcare systems, Brent James recommended Realistic Evaluation, material that that proposes an alternative to the randomized clinical trial that may be useful for evaluating context-specific interventions, and Meta-Analysis by the Confidence Profile Method, that describes methods that could be used to construct more appropriate designs for testing complex interventions (p58).

In section on sustainability, Brent James introduced Intermountain knowledge management system that, according to his experience, saves lives. In addition, the experience suggests that better care is almost always less expensive (p 60).

Concerning business imperatives, Thomas Garthwaite said there are a number of factors that can contribute to sustainability: good quality care is the most effective and efficient care, with reduced variable cost, reduced complications, shorter lengths of stay, and engaged nurses who feel more valued and proud of their efforts. Improved staff retention and morale and reputation enhancement are another benefits that can help grow market share (p 63).

In section Regulatory oversight, Nancy Kass proposed a new way of thinking about ethics and human research, from the current regulatory definition, to a "learning health care system paradigm" in which research and care are integrated (p 72). The most controversial of the obligations, based on feedback Kass received holds that patients have an obligation to participate in the enterprise of learning (p 75).

James Weinstein in his contribution compared RCT and observational trials on spine outcomes. Weinstein and his colleagues found that the RCT was not much better than the observational trial, and that patients had a great deal of decisional regret if they were not involved in the decision-making process. He said that rather than have the process be one of informed consent, it should be one of informed choice, with the patient actively involved in the decision-making process (p 79).


Review: Sharing Clinical Trial Data 2/2

18. october 2015 at 8:00 | Veronika Valdova, ARETE-ZOE |  Risk Management
Key stakeholders in clinical trials include participants, research Ethics Committees, Data Monitoring Committees (DMCs/DSMBs), disease advocacy organizations, funders and sponsors of trials both non-profit and the industry, regulatory agencies, investigators including secondary analysts, research institutions and universities, journals and professional societies (p 48). Jurisdictional differences in protection of personal data can also be a concern, especially in Europe (p 52). Funders and sponsors have significant leverage to set standards and to encourage data sharing for the trials they fund (p 58). Specific examples of effects of secondary analyses are discussed in the context of conflict of interest of different stakeholders (pp 65-67).

U.S. regulatory agencies have to maneuver within the constraints of the Freedom of Information Act (FOIA), the Trade Secrets Act (TSA), and 21 CFR 20.61(c) which makes information submitted or divulged to the FDA unavailable for public disclosure (p 70). Some legal scholars have argued that the FDA potentially has the power to disclose trade secrets for public health reasons, citing the Hatch-Waxman Act (p 71). The first recommendation of the Committee says:

"Stakeholders in clinical trials should foster a culture in which data sharing is the expected norm, and should commit to responsible strategies aimed at maximizing the benefits, minimizing the risks, and overcoming the challenges of sharing clinical trial data for all parties" (p 80).

Publication in scientific journals is the primary method for sharing clinical trial data with the scientific and medical communities. These publications, however, contain only a small subset of the data. In trials that are not part of a regulatory submission, detailed clinical study reports may or may not be prepared (p 91). The committee acknowledges that no single body or authority in the global clinical trials ecosystem has the power to enforce clinical trial data sharing (p 92).

Chapter 4 scrutinizes in thorough detail what kind of data is produced in different type of trials, and how practical (or impractical) it is to share raw data, analyzable data set, clinical trial registration number and data set, full trial protocol, manual of operations, standard operating procedures, names of members of the team, Steering Committee, Clinical Events Committee, Data and Safety Monitoring Board, Data Monitoring Committee, committee charters, details of study execution, informed consent templates, included hypotheses, full statistical analysis plan (SAP), and analytic code (pp 91-105). Additional data for sharing include publications, summaries of results for registries, lay-language summaries, and clinical study reports, either in full or abbreviated form (p 105-111).

The main argument for sharing data from legacy trials is that many current treatment decisions are based on clinical trials done in the past (p 111). The second Committee recommendation states:

"Sponsors and investigators should share the various types of clinical trial data no later than the times specified below. Sponsors and investigators who decide to make data available for sharing before these times are encouraged to do so" (p 132-133).

Chapter 5 examines with whom the data are shared and under what conditions. Potential data recipients may seek access to data for a variety of purposes, which may present different potential benefits and risks: researchers, attorneys, competitors, consultants, whose clients may include investment and financing companies and research organizations, participants in the trial, journalists, disease advocacy groups, members of the public, research ethics committees, peer-review committees, data monitoring committees or educators (p 140).

The key argument in favor of open access is that removing barriers facilitates reproducibility and more rapid advancement of new knowledge and discovery, and that the accompanying risk of invalid analyses is acceptable (p 141). Main concerns are participant privacy, unfair commercial use, invalid secondary analyses, and credit for clinical trialists and sponsors (p 145). The authors also mention already existing multi-sponsor web system ClinicalStudyDataRequest for requesting clinical trial data launched in January 2014 (p 149). Committee recommendation No 3 suggests:

"Holders of clinical trial data implement operational strategies that include employing data use agreements, designating an independent review panel, including members of the lay public in governance, and making access to clinical trial data transparent" (p 157)".

There are more platforms for sharing clinical trial data, with different data access models and sufficient total capacity to meet demand. The Committee shared its vision of culture of data sharing, articulated best practices, and called for allocating the cost of data sharing among stakeholders and protections to minimize the risks (p 164). Recommendation 4 says:
"The sponsors of this study should take the lead, together with or via a trusted impartial organization(s), to convene a multistakeholder body with global reach and broad representation to address, in an ongoing process, the key infrastructure, technological, sustainability, and workforce challenges associated with the sharing of clinical trial data" (p 177).

Appendices include details on study approach, concepts and methods of study data de-identification and legal discussions of risks to industry sponsors.

The report is an essential reading for those who need to understand industry perspective. Industry generates vast majority of clinical trial data, and its primary purpose is to generate data for approval of new drugs and return on investment. A business case has to support public health perspective to incentivize data sharing.

Review: Sharing Clinical Trial Data 1/2

18. october 2015 at 8:00 | Veronika Valdova, ARETE-ZOE |  Risk Management

Review:Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk. Committee on Strategies for Responsible Sharing of Clinical Trial Data; Board on Health Sciences Policy; Institute of Medicine (2015)

According to Bernard Lo, M.D., Chair of the Committee on Strategies for Responsible Sharing of Clinical Trial Data, both patients and their physicians depend on clinical trials for evidence of efficacy and safety of therapies. Responsible sharing clinical trial data raises complex issues and challenges with regards to jurisdictional differences, privacy concerns, and variety of designs utilizing different kind of data (p x).

The Committee was formed to develop guiding principles and a framework (activities and strategies) for the responsible sharing of clinical trial data (p xiii). The report assesses how key stakeholders including participants, sponsors, regulators, investigators, research institutions, journals, and professional societies assess the benefits, risks, and challenges of data sharing. The recommendations include fostering culture of data sharing in reasonable timeframe in a transparent way. The Committee suggests creation of "a multi-stakeholder body with global reach and broad representation to address the key infrastructure, technological, sustainability, and workforce challenges associated with the sharing of clinical trial data" (p xiv).

Data sharing means that data from scientific studies is made available for secondary uses, namely reanalysis to check replicability and validity, meta-analyses and de-novo analyses (p 24).

Chapter 2 presents the major potential benefits and risks of sharing clinical trial data and sets forth the guiding principles. In Chapter 3, stakeholders are identified, including their roles and responsibilities, and the benefits and risks of data sharing from their perspectives. Chapters 4 and 5 discuss type of data and timelines and methods of data sharing. Visions for data sharing are presented in Chapter 6 (p 27).

Sharing of clinical trial data has great potential to accelerate scientific progress and improve public health. Data sharing increases contributions of trial participants to beyond narrow interests of the sponsor. The potential benefits need to be weighed against any potential harm, namely legitimate protection of intellectual property and privacy concerns which could potentially deter people from participating in trials. Distorted and invalid analyses may lead to lawsuits for negligence and burdensome responses. Additionally, qui tam lawsuits create a conflict of interest in the U.S. (p 34). The most important benefit of data sharing in intangible, though:

"Public trust is an intrinsic value undergirding the biomedical science and health research enterprise, which is fundamentally aimed at improving human health. At a more instrumental level, trust also is essential for ensuring continued public support for clinical research and for fostering participation in clinical trials" (p 38).

Boyd cycle

11. october 2015 at 9:40 | Veronika Valdova, ARETE-ZOE

To make any system oriented toward desired outcome, systems approach is necessary to make the feedback mechanism work. Boyd's OODA loop is an elegantly simple grand theory, which contains high quality insight into strategic essentials. OODA loop has extensive domain of applicability, including clinical research and post-market drug surveillance.

Boyd cycle, or OODA loop, explains fundamental principles of decision-making loop based on observation, orientation, decision, and action. Author of the concept, Col. John Boyd, was a fighter pilot and author of designs of F-15 and F-16, who challenged Air Force orthodoxy at the heart of the service's very identity. In his 15-hour briefing "Discourse of Winning and Losing" Col. Boyd challenged the theory how wars were to be fought and won in the era after Vietnam. In Vietnam, the 10 to 1 kill ratio from the Korean War came close to 1 to 1. Boyd's theory redefined tactical air operations after almost 20 years under bomber generals who grew on Curtis LeMay.

The scenario described above shows some analogies with the current situation in the clinical research and pharmaceutical industries. Only about 2 out of 10 marketed drugs return revenues that match or exceed R&D costs. Whilst about 2/3 of clinical trials are still conducted in the U.S., Western Europe, and Australia, globalization has led to outsourcing and off-shoring critical operations overseas to decrease costs and reduce liabilities. The industry found itself in a quagmire of ever increasing costs and low returns.

OBSERVATION: known and observable FACTS (systematic collection of information)
1) Outside information: Proper background research is essential to identify potential critical points which can trigger additional expenses necessary to overcome obstacles or lead to halt of a trial. Critically important information must be "observable" and "detectable" in real time to allow processing. Obscuring information in the collection phase disrupts the OODA loop at the very beginning.
2) Unfolding circumstances: Efficacy and safety profile of a new drug, changing regulatory environment, but also organizational culture affect information coming in.
èFeed observations forward for orientation.

ORIENTATION: Information processing
1) Cultural traditions: Outsourcing and off-shoring brings different cultural traditions. The same information in exactly the same context can be evaluated very differently depending on the person's educational, cultural and personal background. Risk-perception or communication of project issues may be influenced by cultural traditions.
2) Genetic heritage: Nature and nurture affects our ability to detect and communicate potentially critical safety problems before they become self-evident. Different types of intelligence play a role - recognition of patterns, risk-assessment, as well as ability to communicate the message to the leadership. Distribution of personality types in pharma industry shall copy distribution in other high-risk industries to achieve similar results. In pharma, however, teams are often built to avoid personality clashes and ensure smooth function of office environment. System thinkers, who have the capacity to identify systemic flaws, may find it difficult to thrive in such environment.
3) Previous experience: Education, training, personal values, and individual biases affect reasoning and perception of risk. In clinical research, evidence comes from very diverse sources: study findings, observations by investigators, literature screening, colleagues and conference participants, imaging technologies, medical records, and patient feedback. Each source has its unique strengths, weaknesses, potential or actual biases, and vulnerability to manipulation and deception. Systematic work with meaning of the information is essential to accurately judge whether the drug candidate can successfully enter the market.
4) New information: Unexpected surprises can emerge at any stage of a trial or after drug approval. Boyd's OODA loop was designed to present decision-making and behavior of a single individual, well-coordinated team, or an organization with defined structure which behaves in a coordinated manner. Multiplicity of stakeholders within pharma may negatively affect information flow due to their at times conflicting interests. The need for accurate judgment is the same for a fighter pilot and for a pharmaceutical company. The only difference is, that the first will face consequences of a bad decision very fast, whilst the latter with long delay; the principle, however, remains exactly the same. For sound and timely decision-making it is necessary to process information in a structured and coherent manner, and to pass it on along with correct analysis including assessment of confidence levels.
5) Analysis & synthesis: Awareness and conscious examination of own biases and motivations facilitate self-correction in scientific judgement. If some national regulators do not include certain parts of the drug development process in their scrutiny, i.e. design of a trial, delegate certain tasks to the ethics committees without providing appropriate oversight, or if they fail to search for signs of scientific fraud and only focus on speed of certain procedures of interest, they effectively resign on their role in the system.

The process of ORIENTATION provides feedback back to OBSERVATION to alter data collection methods or forms in order to provide the right information for processing. More information does not necessarily mean better and more accurate judgment. This applies to intelligence as well as medicine. In horse racing selection of the right criteria and omission of noise leads to accurate judgment and statistically more successful prediction than indiscriminate assessment of numerous factors without providing value to them. In drug safety a good example of inclusion of "noise" in assessments is the screening of social networks rather than reliance on hard data.

In clinical research there is no structured way of documenting correctness of decisions. At the highest levels the most important indicator of correctness of a decision is amount of money earned on a particular product. The time lapse between preclinical phase, clinical phase, market approval and launch and capitalization on the investments typically exceeds time an average CEO spends in the office. Because of the long gap between initial investment, and series of decisions that follow until the product enters the market, and capitalization, the moment of truth, there is very little incentive to make any unpopular decisions on a project if the feedback (evaluation whether the decision was correct or not) is too far in the future to have any impact on an individual. Hence it is very easy to imagine how non-existence of a real-time real-life feedback leads to fundamentally flawed decision-making process by design. In biology feedback mechanism matters only if the organism can react in real-time. Postprandial insulin meaningfully decreases glucose levels if released in bloodstream in minutes-hours, not if the feedback is delayed long enough to become irrelevant.

Correctness of decision depends on accuracy and timing of information obtained, on its amount, and its form. Decision may lead to test of a hypothesis or directly to action. Whilst it would make sense to halt a trial as early as possible should the study prove non-viable, it does not always happen, and more resources are thrown at a project before it finally reaches a point when it has to be stopped. These delays are caused by the fact that all critical activities of OODA loop are not performed by a single well-coordinated entity but by numerous independent business units and individuals with often conflicting interests. Because the model is dynamic, new information comes in all the time.

Decision-making centers need to adjust information which is being gathered and how this is done. In clinical research and drug safety decisions are made based on data from clinical trials and post-market surveillance. Before the drug enters the market, the total number of patients exposed to the drug is relatively small, the population is well defined, and the frequency of any adverse events can be relatively easily established. After approval efficacy, unlike safety is no longer actively monitored. Post-market surveillance conducted via active reporting cannot provide reliable information on trends, populations exposed, and indications including off-label use. Due to disruption in observation part of the Boyd cycle, some kinds of safety information become invisible after drug launch. This can be resolved by making links between exposure to a substance and clinical outcome observable. To do that it would be necessary to make analytical outputs from real-life use available in real-time in a form which our brains can process.

Action is relevant if it follows decision which has been made. If nobody acts on decision made in real time the whole process of surveillance is fruitless and only documents activity (due diligence) without having an actual impact. Functionality of a system must not fall victim to observation of its outer attributes which document "activities" without substantive action.

IARMM Congress: Lessons from Three Mile Island

3. october 2015 at 14:36 | Veronika Valdova |  Risk Management

Three major industrial accidents - Three Mile Island, Chernobyl and the Volkswagen scandal, are analyzed to illustrate how organizations in highly sophisticated and regulated industries fail to live up to their obligations, and how the lessons learned apply to the pharmaceutical industry.

Arete-Zoe: Lessons from Three Mile Island. 4th World Congress of Clinical Safety (4WCCS) - Clinical Management and Governance for Healthcare Risk and Crisis. Organized by International Association of Risk Management in Medicine (IARMM); on 28 September 2015 in Vienna, Austria.