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Live Notes from @HarvardMed Bioethics: Authors Jerome Groopman, MD & Pamela Hartzband, MD, discuss Your Medical Mind

Writer: Stephen J. Williams, Ph.D.

As part of the Harvard Medical School Series on Bioethics: author, clinician and professor Jerome Groopman, MD and Pamel Harzband, MD gave an online discussion of their book “Your Medical Mind”, a part of Harvard Medical School Center for Bioethics Program’s Critical Reading of Contemporary Books in Bioethics Series. The Contemporary Authors in Bioethics series brings together authors and the community to discuss books that explore new and developing topics in the field. This was held as an online Zoom meeting on March 26, 2020 at 5 pm EST and could be followed on Twitter using #HarvardBioethics.  A recording of the discussion will be made available at the Harvard Med School Center for Bioethics.

 

Available at Amazon: From the Amazon book description:

An entirely new way to make the best medical decisions.

Making the right medical decisions is harder than ever. We are overwhelmed by information from all sides—whether our doctors’ recommendations, dissenting experts, confusing statistics, or testimonials on the Internet. Now Doctors Groopman and Hartzband reveal that each of us has a “medical mind,” a highly individual approach to weighing the risks and benefits of treatments.  Are you a minimalist or a maximalist, a believer or a doubter, do you look for natural healing or the latest technology?  The authors weave vivid narratives of real patients with insights from recent research to demonstrate the power of the medical mind. After reading this groundbreaking book, you will know how to arrive at choices that serve you best.

 

Doctors Groopman and Hartzband began the discussion with a recapping medical research studies and medical panels, which had reported conflicting results or reversal of recommendations, respectively.  These included studies on the benefits of statin therapy in cholesterol management, studies on whether or not Vitamin D therapy is beneficial for postmenopausal women, the ongoing controversy on the frequency with which women should get mammograms, as well as the predictive value of Prostate Specific Antigen and prostate cancer screening.  The authors singled out the research reports and medical panels reviewing the data on PSA in which the same medical panel first came out in support of using PSA levels to screen for prostate cancer and then later, after reconvening, recommended that PSA was not useful for mass screenings for prostate cancer.

In fact, both authors were

completed surprised of the diametrically opposed views within or between panels given similar data presented to those medical professionals.

The authors then asked a question:  Why would the same medical panel come to a reversal of their decision and more, importantly,  why are there such disparate conclusions from the same medical data sets, leading to varied clinical decision-making.

In general, Drs. Groopman and Hartzband asked how do physicians and patients make their decisions?

To answer this they looked at studies that Daniel Bernouli had conducted to model the economic behaviors of risk aversion in the marketplace. Bernouli’s theorem correlated market expectation with probability and outcomes

expectation = probability x utility of outcome

However, in medicine, one can measure probability (or risk) but it is very hard to measure utility (which is the value or worth of the outcome).

For example, they gave an example if a person was born blind but offered a risky to regain sight, the individual values their quality of life from their own perspective and might feel that, as their life is worthwhile as it is, they would not undergo a risky procedure. However a person who had suddenly lost their sight might value sight more, and be willing to undergo a risky procedure.

Three methods are used to put a value on utility or outcome worth with regards to medical decisions

  1. linear scale (life or death; from 0 to 1)
  2. time trade off:  e.g. how much longer do I have to live
  3. standard gamble:  let’s try it

All of these methods however are flawed because one doesn’t know their future medical condition (e.g. new information on the disease) and people values and perceptions change over time.

An example of choice of methods the medical community uses to make decisions include:

  • In the United Kingdom, their system uses a time trade off method to determine value in order to determine appropriate course of action which may inadvertently, result in rationed care
  • in the United States, the medical community uses the time trade off to determine cost effectiveness

 

Therefore Drs. Groopman and Harztband, after conducing multiple interviews with patients and physicians were able to categorize medical decision making based on groups of mindsets

  1. Maximalist: Proactive behavior, wants to stay ahead of the curve
  2. Minimalist: less intervention is more; more hesitant to try any suggested therapy
  3. Naturalist:  more prone to choose natural based therapies or home remedies
  4. Tech Oriented: wants to try the latest therapies and more apt to trust in branded and FDA approved therapeutics
  5. Believer:  trust in suggestions by physician; physician trusts medical panels suggestions
  6. Doubter: naturally inquisitive and more prone to investigate risk benefits of any suggested therapy

The authors also identified many Cognitive Traps that both physicians and patients may fall into including:

  • Relative versus Absolute Numbers: for instance putting emphasis on one number or the other without regard to context; like looking at disease numbers without taking into consideration individual risk
  • Availability: availability or lack of available information; they noticed if you fall in this trap depends on whether you are a Minimalist or Maximalist
  • Framing:  for example  when people talk to others about their conditions and hear stories about others treatments, conditions .. mainly anecdotal evidence

Stories can be helpful but they sometimes increase our overestimation of risk or benefit so framing the information is very important for both the patient as well as the physician (even doctors as patients)

Both authors have noticed a big shift in US to minimalism probably because of the rising costs of healthcare.

How do these mindsets affect the patient-physician relationship?

A University of Michigan study revealed that patients who would be characterized as maximalists pushed their physicians to do more therapy and were more prone to seek outside advice.

Physicians need to understand and listen to their patients during the patients’s first visit and determine what medical mindset that this patient has.

About the authors:

Jerome Groopman, M.D. is the Dina and Raphael Recanati Professor of Medicine at Harvard Medical School, Chief of Experimental Medicine at Beth Israel Deaconess Medical Center, and one of the world’s leading researchers in cancer and AIDS. He is a staff writer for The New Yorker and has written for The New York TimesThe Wall Street Journal,The Washington Post and The New Republic. He is author of The Measure of Our Days (1997), Second Opinions (2000), Anatomy of Hope (2004), How Doctors Think (2007), and the recently released, Your Medical Mind.

Dr. Pamela Hartzband is an Assistant Professor at the Harvard Medical School and Attending Physician in the Division of Endocrinology at the Beth Israel Deaconess Medical Center in Boston. She specializes in disorders of the thyroid and pituitary glands. A magna cum laude graduate of Radcliffe College, Harvard University, she received her M.D. from Harvard Medical School. She served her internship and residency in internal medicine at the Massachusetts General Hospital, and her specialty fellowships in endocrinology and metabolism at UCLA.

More articles on BioEthics and Patient experiences in this Online Open Access Journal Include:

Ethics Behind Genetic Testing in Breast Cancer: A Webinar by Laura Carfang of survivingbreastcancer.org

Tweets and Re-Tweets by @Pharma_BI ‏and @AVIVA1950 at 2019 Petrie-Flom Center Annual Conference: Consuming Genetics: Ethical and Legal Considerations of New Technologies, Friday, May 17, 2019 from 8:00 AM to 5:00 PM EDT @Harvard_Law

Innovation + Technology = Good Patient Experience

Drivers of Patient Experience

Factors in Patient Experience

Patient Experience Survey

Please also see our offering on Amazon at https://www.amazon.com/dp/B076HGB6MZ

“The VOICES of Patients, Hospital CEOs, Health Care Providers, Caregivers and Families: Personal Experience with Critical Care and Invasive Medical Procedures,”

 

 

 

 

 

 

 

 

 

 

 

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US Responses to Coronavirus Outbreak Expose Many Flaws in Our Medical System

Curator: Stephen J. Williams, Ph.D.

The  coronavirus pandemic has affected almost every country in every continent however, after months of the novel advent of novel COVID-19 cases, it has become apparent that the varied clinical responses in this epidemic (and outcomes) have laid bare some of the strong and weak aspects in, both our worldwide capabilities to respond to infectious outbreaks in a global coordinated response and in individual countries’ response to their localized epidemics.

 

Some nations, like Israel, have initiated a coordinated government-private-health system wide action plan and have shown success in limiting both new cases and COVID-19 related deaths.  After the initial Wuhan China outbreak, China closed borders and the government initiated health related procedures including the building of new hospitals. As of writing today, Wuhan has experienced no new cases of COVID-19 for two straight days.

 

However, the response in the US has been perplexing and has highlighted some glaring problems that have been augmented in this crisis, in the view of this writer.    In my view, which has been formulated after social discussion with members in the field ,these issues can be centered on three major areas of deficiencies in the United States that have hindered a rapid and successful response to this current crisis and potential future crises of this nature.

 

 

  1. The mistrust or misunderstanding of science in the United States
  2. Lack of communication and connection between patients and those involved in the healthcare industry
  3. Socio-geographical inequalities within the US healthcare system

 

1. The mistrust or misunderstanding of science in the United States

 

For the past decade, anyone involved in science, whether directly as active bench scientists, regulatory scientists, scientists involved in science and health policy, or environmental scientists can attest to the constant pressure to not only defend their profession but also to defend the entire scientific process and community from an onslaught of misinformation, mistrust and anxiety toward the field of science.  This can be seen in many of the editorials in scientific publications including the journal Science and Scientific American (as shown below)

 

Stepping Away from Microscopes, Thousands Protest War on Science

Boston rally coincides with annual American Association for the Advancement of Science (AAAS) conference and is a precursor to the March for Science in Washington, D.C.

byLauren McCauley, staff writer

Responding to the troubling suppression of science under the Trump administration, thousands of scientists, allies, and frontline communities are holding a rally in Boston’s Copley Square on Sunday.

#standupforscience Tweets

 

“Science serves the common good,” reads the call to action. “It protects the health of our communities, the safety of our families, the education of our children, the foundation of our economy and jobs, and the future we all want to live in and preserve for coming generations.”

It continues: 

But it’s under attack—both science itself, and the unalienable rights that scientists help uphold and protect. 

From the muzzling of scientists and government agencies, to the immigration ban, the deletion of scientific data, and the de-funding of public science, the erosion of our institutions of science is a dangerous direction for our country. Real people and communities bear the brunt of these actions.

The rally was planned to coincide with the annual American Association for the Advancement of Science (AAAS) conference, which draws thousands of science professionals, and is a precursor to the March for Science in Washington, D.C. and in cities around the world on April 22.

 

Source: https://www.commondreams.org/news/2017/02/19/stepping-away-microscopes-thousands-protest-war-science

https://images.app.goo.gl/UXizCsX4g5wZjVtz9

 

https://www.washingtonpost.com/video/c/embed/85438fbe-278d-11e7-928e-3624539060e8

 

 

The American Association for Cancer Research (AACR) also had marches for public awareness of science and meaningful science policy at their annual conference in Washington, D.C. in 2017 (see here for free recordings of some talks including Joe Biden’s announcement of the Cancer Moonshot program) and also sponsored events such as the Rally for Medical Research.  This patient advocacy effort is led by the cancer clinicians and scientific researchers to rally public support for cancer research for the benefit of those affected by the disease.

Source: https://leadingdiscoveries.aacr.org/cancer-patients-front-and-center/

 

 

     However, some feel that scientists are being too sensitive and that science policy and science-based decision making may not be under that much of a threat in this country. Yet even as some people think that there is no actual war on science and on scientists they realize that the public is not engaged in science and may not be sympathetic to the scientific process or trust scientists’ opinions. 

 

   

From Scientific American: Is There Really a War on Science? People who oppose vaccines, GMOs and climate change evidence may be more anxious than antagonistic

 

Certainly, opponents of genetically modified crops, vaccinations that are required for children and climate science have become louder and more organized in recent times. But opponents typically live in separate camps and protest single issues, not science as a whole, said science historian and philosopher Roberta Millstein of the University of California, Davis. She spoke at a standing-room only panel session at the American Association for the Advancement of Science’s annual meeting, held in Washington, D.C. All the speakers advocated for a scientifically informed citizenry and public policy, and most discouraged broadly applied battle-themed rhetoric.

 

Source: https://www.scientificamerican.com/article/is-there-really-a-war-on-science/

 

      In general, it appears to be a major misunderstanding by the public of the scientific process, and principles of scientific discovery, which may be the fault of miscommunication by scientists or agendas which have the goals of subverting or misdirecting public policy decisions from scientific discourse and investigation.

 

This can lead to an information vacuum, which, in this age of rapid social media communication,

can quickly perpetuate misinformation.

 

This perpetuation of misinformation was very evident in a Twitter feed discussion with Dr. Eric Topol, M.D. (cardiologist and Founder and Director of the Scripps Research Translational  Institute) on the US President’s tweet on the use of the antimalarial drug hydroxychloroquine based on President Trump referencing a single study in the International Journal of Antimicrobial Agents.  The Twitter thread became a sort of “scientific journal club” with input from international scientists discussing and critiquing the results in the paper.  

 

Please note that when we scientists CRITIQUE a paper it does not mean CRITICIZE it.  A critique is merely an in depth analysis of the results and conclusions with an open discussion on the paper.  This is part of the normal peer review process.

 

Below is the original Tweet by Dr. Eric Topol as well as the ensuing tweet thread

 

https://twitter.com/EricTopol/status/1241442247133900801?s=20

 

Within the tweet thread it was discussed some of the limitations or study design flaws of the referenced paper leading the scientists in this impromptu discussion that the study could not reasonably conclude that hydroxychloroquine was not a reliable therapeutic for this coronavirus strain.

 

The lesson: The public has to realize CRITIQUE does not mean CRITICISM.

 

Scientific discourse has to occur to allow for the proper critique of results.  When this is allowed science becomes better, more robust, and we protect ourselves from maybe heading down an incorrect path, which may have major impacts on a clinical outcome, in this case.

 

 

2.  Lack of communication and connection between patients and those involved in the healthcare industry

 

In normal times, it is imperative for the patient-physician relationship to be intact in order for the physician to be able to communicate proper information to their patient during and after therapy/care.  In these critical times, this relationship and good communication skills becomes even more important.

 

Recently, I have had multiple communications, either through Twitter, Facebook, and other social media outlets with cancer patients, cancer advocacy groups, and cancer survivorship forums concerning their risks of getting infected with the coronavirus and how they should handle various aspects of their therapy, whether they were currently undergoing therapy or just about to start chemotherapy.  This made me realize that there were a huge subset of patients who were not receiving all the information and support they needed; namely patients who are immunocompromised.

 

These are patients represent

  1. cancer patient undergoing/or about to start chemotherapy
  2. Patients taking immunosuppressive drugs: organ transplant recipients, patients with autoimmune diseases, multiple sclerosis patients
  3. Patients with immunodeficiency disorders

 

These concerns prompted me to write a posting curating the guidance from National Cancer Institute (NCI) designated cancer centers to cancer patients concerning their risk to COVID19 (which can be found here).

 

Surprisingly, there were only 14 of the 51 US NCI Cancer Centers which had posted guidance (either there own or from organizations like NCI or the National Cancer Coalition Network (NCCN).  Most of the guidance to patients had stemmed from a paper written by Dr. Markham of the Fred Hutchinson Cancer Center in Seattle Washington, the first major US city which was impacted by COVID19.

 

Also I was surprised at the reactions to this posting, with patients and oncologists enthusiastic to discuss concerns around the coronavirus problem.  This led to having additional contact with patients and oncologists who, as I was surprised, are not having these conversations with each other or are totally confused on courses of action during this pandemic.  There was a true need for each party, both patients/caregivers and physicians/oncologists to be able to communicate with each other and disseminate good information.

 

Last night there was a Tweet conversation on Twitter #OTChat sponsored by @OncologyTimes.  A few tweets are included below

https://twitter.com/OncologyTimes/status/1242611841613864960?s=20

https://twitter.com/OncologyTimes/status/1242616756658753538?s=20

https://twitter.com/OncologyTimes/status/1242615906846547978?s=20

 

The Lesson:  Rapid Communication of Vital Information in times of stress is crucial in maintaining a good patient/physician relationship and preventing Misinformation.

 

3.  Socio-geographical Inequalities in the US Healthcare System

It has become very clear that the US healthcare system is fractioned and multiple inequalities (based on race, sex, geography, socio-economic status, age) exist across the whole healthcare system.  These inequalities are exacerbated in times of stress, especially when access to care is limited.

 

An example:

 

On May 12, 2015, an Amtrak Northeast Regional train from Washington, D.C. bound for New York City derailed and wrecked on the Northeast Corridor in the Port Richmond neighborhood of Philadelphia, Pennsylvania. Of 238 passengers and 5 crew on board, 8 were killed and over 200 injured, 11 critically. The train was traveling at 102 mph (164 km/h) in a 50 mph (80 km/h) zone of curved tracks when it derailed.[3]

Some of the passengers had to be extricated from the wrecked cars. Many of the passengers and local residents helped first responders during the rescue operation. Five local hospitals treated the injured. The derailment disrupted train service for several days. 

(Source Wikipedia https://en.wikipedia.org/wiki/2015_Philadelphia_train_derailment)

What was not reported was the difficulties that first responders, namely paramedics had in finding an emergency room capable of taking on the massive load of patients.  In the years prior to this accident, several hospitals, due to monetary reasons, had to close their emergency rooms or reduce them in size. In addition only two in Philadelphia were capable of accepting gun shot victims (Temple University Hospital was the closest to the derailment but one of the emergency rooms which would accept gun shot victims. This was important as Temple University ER, being in North Philadelphia, is usually very busy on any given night.  The stress to the local health system revealed how one disaster could easily overburden many hospitals.

 

Over the past decade many hospitals, especially rural hospitals, have been shuttered or consolidated into bigger health systems.  The graphic below shows this

From Bloomberg: US Hospital Closings Leave Patients with Nowhere to go

 

 

https://images.app.goo.gl/JdZ6UtaG3Ra3EA3J8

 

Note the huge swath of hospital closures in the midwest, especially in rural areas.  This has become an ongoing problem as the health care system deals with rising costs.

 

Lesson:  Epidemic Stresses an already stressed out US healthcare system

 

Please see our Coronavirus Portal at

https://pharmaceuticalintelligence.com/coronavirus-portal/

 

for more up-to-date scientific, clinical information as well as persona stories, videos, interviews and economic impact analyses

and @pharma_BI

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Diversity and Health Disparity Issues Need to be Addressed for GWAS and Precision Medicine Studies

Curator: Stephen J. Williams, PhD

 

 

From the POLICY FORUM ETHICS AND DIVERSITY Section of Science

Ethics of inclusion: Cultivate trust in precision medicine

 See all authors and affiliations

Science  07 Jun 2019:
Vol. 364, Issue 6444, pp. 941-942
DOI: 10.1126/science.aaw8299

Precision medicine is at a crossroads. Progress toward its central goal, to address persistent health inequities, will depend on enrolling populations in research that have been historically underrepresented, thus eliminating longstanding exclusions from such research (1). Yet the history of ethical violations related to protocols for inclusion in biomedical research, as well as the continued misuse of research results (such as white nationalists looking to genetic ancestry to support claims of racial superiority), continue to engender mistrust among these populations (2). For precision medicine research (PMR) to achieve its goal, all people must believe that there is value in providing information about themselves and their families, and that their participation will translate into equitable distribution of benefits. This requires an ethics of inclusion that considers what constitutes inclusive practices in PMR, what goals and values are being furthered through efforts to enhance diversity, and who participates in adjudicating these questions. The early stages of PMR offer a critical window in which to intervene before research practices and their consequences become locked in (3).

Initiatives such as the All of Us program have set out to collect and analyze health information and biological samples from millions of people (1). At the same time, questions of trust in biomedical research persist. For example, although the recent assertions of white nationalists were eventually denounced by the American Society of Human Genetics (4), the misuse of ancestry testing may have already undermined public trust in genetic research.

There are also infamous failures in research that included historically underrepresented groups, including practices of deceit, as in the Tuskegee Syphilis Study, or the misuse of samples, as with the Havasupai tribe (5). Many people who are being asked to give their data and samples for PMR must not only reconcile such past research abuses, but also weigh future risks of potential misuse of their data.

To help assuage these concerns, ongoing PMR studies should open themselves up to research, conducted by social scientists and ethicists, that examines how their approaches enhance diversity and inclusion. Empirical studies are needed to account for how diversity is conceptualized and how goals of inclusion are operationalized throughout the life course of PMR studies. This is not limited to selection and recruitment of populations but extends to efforts to engage participants and communities, through data collection and measurement, and interpretations and applications of study findings. A commitment to transparency is an important step toward cultivating public trust in PMR’s mission and practices.

From Inclusion to Inclusive

The lack of diverse representation in precision medicine and other biomedical research is a well-known problem. For example, rare genetic variants may be overlooked—or their association with common, complex diseases can be misinterpreted—as a result of sampling bias in genetics research (6). Concentrating research efforts on samples with largely European ancestry has limited the ability of scientists to make generalizable inferences about the relationships among genes, lifestyle, environmental exposures, and disease risks, and thereby threatens the equitable translation of PMR for broad public health benefit (7).

However, recruiting for diverse research participation alone is not enough. As with any push for “diversity,” related questions arise about how to describe, define, measure, compare, and explain inferred similarities and differences among individuals and groups (8). In the face of ambivalence about how to represent population variation, there is ample evidence that researchers resort to using definitions of diversity that are heterogeneous, inconsistent, and sometimes competing (9). Varying approaches are not inherently problematic; depending on the scientific question, some measures may be more theoretically justified than others and, in many cases, a combination of measures can be leveraged to offer greater insight (10). For example, studies have shown that American adults who do not self-identify as white report better mental and physical health if they think others perceive them as white (1112).

The benefit of using multiple measures of race and ancestry also extends to genetic studies. In a study of hypertension in Puerto Rico, not only did classifications based on skin color and socioeconomic status better predict blood pressure than genetic ancestry, the inclusion of these sociocultural measures also revealed an association between a genetic polymorphism and hypertension that was otherwise hidden (13). Thus, practices that allow for a diversity of measurement approaches, when accompanied by a commitment to transparency about the rationales for chosen approaches, are likely to benefit PMR research more than striving for a single gold standard that would apply across all studies. These definitional and measurement issues are not merely semantic. They also are socially consequential to broader perceptions of PMR research and the potential to achieve its goals of inclusion.

Study Practices, Improve Outcomes

Given the uncertainty and complexities of the current, early phase of PMR, the time is ripe for empirical studies that enable assessment and modulation of research practices and scientific priorities in light of their social and ethical implications. Studying ongoing scientific practices in real time can help to anticipate unintended consequences that would limit researchers’ ability to meet diversity recruitment goals, address both social and biological causes of health disparities, and distribute the benefits of PMR equitably. We suggest at least two areas for empirical attention and potential intervention.

First, we need to understand how “upstream” decisions about how to characterize study populations and exposures influence “downstream” research findings of what are deemed causal factors. For example, when precision medicine researchers rely on self-identification with U.S. Census categories to characterize race and ethnicity, this tends to circumscribe their investigation of potential gene-environment interactions that may affect health. The convenience and routine nature of Census categories seemed to lead scientists to infer that the reasons for differences among groups were self-evident and required no additional exploration (9). The ripple effects of initial study design decisions go beyond issues of recruitment to shape other facets of research across the life course of a project, from community engagement and the return of results to the interpretation of study findings for human health.

Second, PMR studies are situated within an ecosystem of funding agencies, regulatory bodies, disciplines, and other scholars. This partly explains the use of varied terminology, different conceptual understandings and interpretations of research questions, and heterogeneous goals for inclusion. It also makes it important to explore how expectations related to funding and regulation influence research definitions of diversity and benchmarks for inclusion.

For example, who defines a diverse study population, and how might those definitions vary across different institutional actors? Who determines the metrics that constitute successful inclusion, and why? Within a research consortium, how are expectations for data sharing and harmonization reconciled with individual studies’ goals for recruitment and analysis? In complex research fields that include multiple investigators, organizations, and agendas, how are heterogeneous, perhaps even competing, priorities negotiated? To date, no studies have addressed these questions or investigated how decisions facilitate, or compromise, goals of diversity and inclusion.

The life course of individual studies and the ecosystems in which they reside cannot be easily separated and therefore must be studied in parallel to understand how meanings of diversity are shaped and how goals of inclusion are pursued. Empirically “studying the studies” will also be instrumental in creating mechanisms for transparency about how PMR is conducted and how trade-offs among competing goals are resolved. Establishing open lines of inquiry that study upstream practices may allow researchers to anticipate and address downstream decisions about how results can be interpreted and should be communicated, with a particular eye toward the consequences for communities recruited to augment diversity. Understanding how scientists negotiate the challenges and barriers to achieving diversity that go beyond fulfilling recruitment numbers is a critical step toward promoting meaningful inclusion in PMR.

Transparent Reflection, Cultivation of Trust

Emerging research on public perceptions of PMR suggests that although there is general support, questions of trust loom large. What we learn from studies that examine on-the-ground approaches aimed at enhancing diversity and inclusion, and how the research community reflects and responds with improvements in practices as needed, will play a key role in building a culture of openness that is critical for cultivating public trust.

Cultivating long-term, trusting relationships with participants underrepresented in biomedical research has been linked to a broad range of research practices. Some of these include the willingness of researchers to (i) address the effect of history and experience on marginalized groups’ trust in researchers and clinicians; (ii) engage concerns about potential group harms and risks of stigmatization and discrimination; (iii) develop relationships with participants and communities that are characterized by transparency, clear communication, and mutual commitment; and (iv) integrate participants’ values and expectations of responsible oversight beyond initial informed consent (14). These findings underscore the importance of multidisciplinary teams that include social scientists, ethicists, and policy-makers, who can identify and help to implement practices that respect the histories and concerns of diverse publics.

A commitment to an ethics of inclusion begins with a recognition that risks from the misuse of genetic and biomedical research are unevenly distributed. History makes plain that a multitude of research practices ranging from unnecessarily limited study populations and taken-for-granted data collection procedures to analytic and interpretive missteps can unintentionally bolster claims of racial superiority or inferiority and provoke group harm (15). Sustained commitment to transparency about the goals, limits, and potential uses of research is key to further cultivating trust and building long-term research relationships with populations underrepresented in biomedical studies.

As calls for increasing diversity and inclusion in PMR grow, funding and organizational pathways must be developed that integrate empirical studies of scientific practices and their rationales to determine how goals of inclusion and equity are being addressed and to identify where reform is required. In-depth, multidisciplinary empirical investigations of how diversity is defined, operationalized, and implemented can provide important insights and lessons learned for guiding emerging science, and in so doing, meet our ethical obligations to ensure transparency and meaningful inclusion.

References and Notes

  1. C. P. Jones et al Ethn. Dis. 18496 (2008).
  2. C. C. GravleeA. L. NonC. J. Mulligan
  3. S. A. Kraft et al Am. J. Bioeth. 183 (2018).
  4. A. E. Shields et al Am. Psychol. 6077 (2005).

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Parkinson’s Disease (PD), characterized by both motor and non-motor system pathology, is a common neurodegenerative disorder affecting about 1% of the population over age 60. Its prevalence presents an increasing social burden as the population ages. Since its introduction in the 1960’s, dopamine (DA)-replacement therapy (e.g., L-DOPA) has remained the gold standard treatment. While improving PD patients’ quality of life, the effects of treatment fade with disease progression and prolonged usage of these medications often (>80%) results in side effects including dyskinesias and motor fluctuations. Since the selective degeneration of A9 mDA neurons (mDANs) in the substantia nigra (SN) is a key pathological feature of the disease and is directly associated with the cardinal motor symptoms, dopaminergic cell transplantation has been proposed as a therapeutic strategy.

 

Researchers showed that mammalian fibroblasts can be converted into embryonic stem cell (ESC)-like induced pluripotent stem cells (iPSCs) by introducing four transcription factors i.e., Oct4, Sox2, Klf4, and c-Myc. This was then accomplished with human somatic cells, reprogramming them into human iPSCs (hiPSCs), offering the possibility of generating patient-specific stem cells. There are several major barriers to implementation of hiPSC-based cell therapy for PD. First, probably due to the limited understanding of the reprogramming process, wide variability exists between the differentiation potential of individual hiPSC lines. Second, the safety of hiPSC-based cell therapy has yet to be fully established. In particular, since any hiPSCs that remain undifferentiated or bear sub-clonal tumorigenic mutations have neoplastic potential, it is critical to eliminate completely such cells from a therapeutic product.

 

In the present study the researchers established human induced pluripotent stem cell (hiPSC)-based autologous cell therapy. Researchers reported a platform of core techniques for the production of mDA progenitors as a safe and effective therapeutic product. First, by combining metabolism-regulating microRNAs with reprogramming factors, a method was developed to more efficiently generate clinical grade iPSCs, as evidenced by genomic integrity and unbiased pluripotent potential. Second, a “spotting”-based in vitro differentiation methodology was established to generate functional and healthy mDA cells in a scalable manner. Third, a chemical method was developed that safely eliminates undifferentiated cells from the final product. Dopaminergic cells thus produced can express high levels of characteristic mDA markers, produce and secrete dopamine, and exhibit electrophysiological features typical of mDA cells. Transplantation of these cells into rodent models of PD robustly restored motor dysfunction and reinnervated host brain, while showing no evidence of tumor formation or redistribution of the implanted cells.

 

Together these results supported the promise of these techniques to provide clinically applicable personalized autologous cell therapy for PD. It was recognized by researchers that this methodology is likely to be more costly in dollars and manpower than techniques using off-the-shelf methods and allogenic cell lines. Nevertheless, the cost for autologous cell therapy may be expected to decrease steadily with technological refinement and automation. Given the significant advantages inherent in a cell source free of ethical concerns and with the potential to obviate the need for immunosuppression, with its attendant costs and dangers, it was proposed that this platform is suitable for the successful implementation of human personalized autologous cell therapy for PD.

 

References:

 

https://www.jci.org/articles/view/130767/pdf?elqTrackId=2fd7d0edee744f9cb6d70a686d7b273b

 

https://www.ncbi.nlm.nih.gov/pubmed/31714896

 

https://www.ncbi.nlm.nih.gov/pubmed/23666606

 

https://www.ncbi.nlm.nih.gov/pubmed/27343168

 

https://www.ncbi.nlm.nih.gov/pubmed/21495962

 

https://www.ncbi.nlm.nih.gov/pubmed/28083784

 

https://www.ncbi.nlm.nih.gov/pubmed/20336395

 

https://www.ncbi.nlm.nih.gov/pubmed/28585381

 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Effective humoral immune responses to infection and immunization are defined by high-affinity antibodies generated as a result of B cell differentiation and selection that occurs within germinal centers (GC). Within the GC, B cells undergo affinity maturation, an iterative and competitive process wherein B cells mutate their immunoglobulin genes (somatic hypermutation) and undergo clonal selection by competing for T cell help. Balancing the decision to remain within the GC and continue participating in affinity maturation or to exit the GC as a plasma cell (PC) or memory B cell (MBC) is critical for achieving optimal antibody avidity, antibody quantity, and establishing immunological memory in response to immunization or infection. Humoral immune responses during chronic infections are often dysregulated and characterized by hypergammaglobulinemia, decreased affinity maturation, and delayed development of neutralizing antibodies. Previous studies have suggested that poor antibody quality is in part due to deletion of B cells prior to establishment of the GC response.

 

In fact the impact of chronic infections on B cell fate decisions in the GC remains poorly understood. To address this question, researchers used single-cell transcriptional profiling of virus-specific GC B cells to test the hypothesis that chronic viral infection disrupted GC B cell fate decisions leading to suboptimal humoral immunity. These studies revealed a critical GC differentiation checkpoint that is disrupted by chronic infection, specifically at the point of dark zone re-entry. During chronic viral infection, virus-specific GC B cells were shunted towards terminal plasma cell (PC) or memory B cell (MBC) fates at the expense of continued participation in the GC. Early GC exit was associated with decreased B cell mutational burden and antibody quality. Persisting antigen and inflammation independently drove facets of dysregulation, with a key role for inflammation in directing premature terminal GC B cell differentiation and GC exit. Thus, the present research defines GC defects during chronic viral infection and identify a critical GC checkpoint that is short-circuited, preventing optimal maturation of humoral immunity.

 

Together, these studies identify a key GC B cell differentiation checkpoint that is dysregulated during chronic infection. Further, it was found that the chronic inflammatory environment, rather than persistent antigen, is sufficient to drive altered GC B cell differentiation during chronic infection even against unrelated antigens. However, the data also indicate that inflammatory circuits are likely linked to perception of antigen stimulation. Nevertheless, this study reveals a B cell-intrinsic program of transcriptional skewing in chronic viral infection that results in shunting out of the cyclic GC B cell process and early GC exit with consequences for antibody quality and hypergammaglobulinemia. These findings have implications for vaccination in individuals with pre-existing chronic infections where antibody responses are often ineffective and suggest that modulation of inflammatory pathways may be therapeutically useful to overcome impaired humoral immunity and foster affinity maturation during chronic viral infections.

 

References:

 

https://www.biorxiv.org/content/10.1101/849844v1

 

https://www.ncbi.nlm.nih.gov/pubmed/25656706

 

https://www.ncbi.nlm.nih.gov/pubmed/27653600

 

https://www.ncbi.nlm.nih.gov/pubmed/26912368

 

https://www.ncbi.nlm.nih.gov/pubmed/26799208

 

https://www.ncbi.nlm.nih.gov/pubmed/23001146

 

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scPopCorn: A New Computational Method for Subpopulation Detection and their Comparative Analysis Across Single-Cell Experiments

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Present day technological advances have facilitated unprecedented opportunities for studying biological systems at single-cell level resolution. For example, single-cell RNA sequencing (scRNA-seq) enables the measurement of transcriptomic information of thousands of individual cells in one experiment. Analyses of such data provide information that was not accessible using bulk sequencing, which can only assess average properties of cell populations. Single-cell measurements, however, can capture the heterogeneity of a population of cells. In particular, single-cell studies allow for the identification of novel cell types, states, and dynamics.

 

One of the most prominent uses of the scRNA-seq technology is the identification of subpopulations of cells present in a sample and comparing such subpopulations across samples. Such information is crucial for understanding the heterogeneity of cells in a sample and for comparative analysis of samples from different conditions, tissues, and species. A frequently used approach is to cluster every dataset separately, inspect marker genes for each cluster, and compare these clusters in an attempt to determine which cell types were shared between samples. This approach, however, relies on the existence of predefined or clearly identifiable marker genes and their consistent measurement across subpopulations.

 

Although the aligned data can then be clustered to reveal subpopulations and their correspondence, solving the subpopulation-mapping problem by performing global alignment first and clustering second overlooks the original information about subpopulations existing in each experiment. In contrast, an approach addressing this problem directly might represent a more suitable solution. So, keeping this in mind the researchers developed a computational method, single-cell subpopulations comparison (scPopCorn), that allows for comparative analysis of two or more single-cell populations.

 

The performance of scPopCorn was tested in three distinct settings. First, its potential was demonstrated in identifying and aligning subpopulations from single-cell data from human and mouse pancreatic single-cell data. Next, scPopCorn was applied to the task of aligning biological replicates of mouse kidney single-cell data. scPopCorn achieved the best performance over the previously published tools. Finally, it was applied to compare populations of cells from cancer and healthy brain tissues, revealing the relation of neoplastic cells to neural cells and astrocytes. Consequently, as a result of this integrative approach, scPopCorn provides a powerful tool for comparative analysis of single-cell populations.

 

This scPopCorn is basically a computational method for the identification of subpopulations of cells present within individual single-cell experiments and mapping of these subpopulations across these experiments. Different from other approaches, scPopCorn performs the tasks of population identification and mapping simultaneously by optimizing a function that combines both objectives. When applied to complex biological data, scPopCorn outperforms previous methods. However, it should be kept in mind that scPopCorn assumes the input single-cell data to consist of separable subpopulations and it is not designed to perform a comparative analysis of single cell trajectories datasets that do not fulfill this constraint.

 

Several innovations developed in this work contributed to the performance of scPopCorn. First, unifying the above-mentioned tasks into a single problem statement allowed for integrating the signal from different experiments while identifying subpopulations within each experiment. Such an incorporation aids the reduction of biological and experimental noise. The researchers believe that the ideas introduced in scPopCorn not only enabled the design of a highly accurate identification of subpopulations and mapping approach, but can also provide a stepping stone for other tools to interrogate the relationships between single cell experiments.

 

References:

 

https://www.sciencedirect.com/science/article/pii/S2405471219301887

 

https://www.tandfonline.com/doi/abs/10.1080/23307706.2017.1397554

 

https://ieeexplore.ieee.org/abstract/document/4031383

 

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0927-y

 

https://www.sciencedirect.com/science/article/pii/S2405471216302666

 

 

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eProceedings for BIO 2019 International Convention, June 3-6, 2019 Philadelphia Convention Center; Philadelphia PA, Real Time Coverage by Stephen J. Williams, PhD @StephenJWillia2

 

CONFERENCE OVERVIEW

Real Time Coverage of BIO 2019 International Convention, June 3-6, 2019 Philadelphia Convention Center; Philadelphia PA

Reporter: Stephen J. Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/05/31/real-time-coverage-of-bio-international-convention-june-3-6-2019-philadelphia-convention-center-philadelphia-pa/

 

LECTURES & PANELS

Real Time Coverage @BIOConvention #BIO2019: Machine Learning and Artificial Intelligence: Realizing Precision Medicine One Patient at a Time, 6/5/2019, Philadelphia PA

Reporter: Stephen J Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/05/real-time-coverage-bioconvention-bio2019-machine-learning-and-artificial-intelligence-realizing-precision-medicine-one-patient-at-a-time/

 

Real Time Coverage @BIOConvention #BIO2019: Genome Editing and Regulatory Harmonization: Progress and Challenges, 6/5/2019. Philadelphia PA

Reporter: Stephen J Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/05/real-time-coverage-bioconvention-bio2019-genome-editing-and-regulatory-harmonization-progress-and-challenges/

 

Real Time Coverage @BIOConvention #BIO2019: Precision Medicine Beyond Oncology June 5, 2019, Philadelphia PA

Reporter: Stephen J Williams PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/05/real-time-coverage-bioconvention-bio2019-precision-medicine-beyond-oncology-june-5-philadelphia-pa/

 

Real Time @BIOConvention #BIO2019:#Bitcoin Your Data! From Trusted Pharma Silos to Trustless Community-Owned Blockchain-Based Precision Medicine Data Trials, 6/5/2019, Philadelphia PA

Reporter: Stephen J Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/05/real-time-bioconvention-bio2019bitcoin-your-data-from-trusted-pharma-silos-to-trustless-community-owned-blockchain-based-precision-medicine-data-trials/

 

Real Time Coverage @BIOConvention #BIO2019: Keynote Address Jamie Dimon CEO @jpmorgan June 5, 2019, Philadelphia, PA

Reporter: Stephen J. Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/05/real-time-coverage-bioconvention-bio2019-keynote-address-jamie-dimon-ceo-jpmorgan-june-5-philadelphia/

 

Real Time Coverage @BIOConvention #BIO2019: Chat with @FDA Commissioner, & Challenges in Biotech & Gene Therapy June 4, 2019, Philadelphia, PA

Reporter: Stephen J. Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/04/real-time-coverage-bioconvention-bio2019-chat-with-fda-commissioner-challenges-in-biotech-gene-therapy-june-4-philadelphia/

 

Falling in Love with Science: Championing Science for Everyone, Everywhere June 4 2019, Philadelphia PA

Reporter: Stephen J. Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/04/real-time-coverage-bioconvention-bio2019-falling-in-love-with-science-championing-science-for-everyone-everywhere/

 

Real Time Coverage @BIOConvention #BIO2019: June 4 Morning Sessions; Global Biotech Investment & Public-Private Partnerships, 6/4/2019, Philadelphia PA

Reporter: Stephen J Williams PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/04/real-time-coverage-bioconvention-bio2019-june-4-morning-sessions-global-biotech-investment-public-private-partnerships/

 

Real Time Coverage @BIOConvention #BIO2019: Understanding the Voices of Patients: Unique Perspectives on Healthcare; June 4, 2019, 11:00 AM, Philadelphia PA

Reporter: Stephen J. Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/04/real-time-coverage-bioconvention-bio2019-understanding-the-voices-of-patients-unique-perspectives-on-healthcare-june-4/

 

Real Time Coverage @BIOConvention #BIO2019: Keynote: Siddhartha Mukherjee, Oncologist and Pulitzer Author; June 4 2019, 9AM, Philadelphia PA

Reporter: Stephen J. Williams, PhD. @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/04/real-time-coverage-bioconvention-bio2019-keynote-siddhartha-mukherjee-oncologist-and-pulitzer-author-june-4-9am-philadelphia-pa/

 

Real Time Coverage @BIOConvention #BIO2019:  Issues of Risk and Reproduceability in Translational and Academic Collaboration; 2:30-4:00 June 3, 2019, Philadelphia PA

Reporter: Stephen J. Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/03/real-time-coverage-bioconvention-bio2019-issues-of-risk-and-reproduceability-in-translational-and-academic-collaboration-230-400-june-3-philadelphia-pareal-time-coverage-bioconvention-bi/

 

Real Time Coverage @BIOConvention #BIO2019: What’s Next: The Landscape of Innovation in 2019 and Beyond. 3-4 PM June 3, 2019, Philadelphia PA

Reporter: Stephen J. Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/03/real-time-coverage-bioconvention-bio2019-whats-next-the-landscape-of-innovation-in-2019-and-beyond-3-4-pm-june-3-philadelphia-pa/

 

Real Time Coverage @BIOConvention #BIO2019: After Trump’s Drug Pricing Blueprint: What Happens Next? A View from Washington; June 3, 2019 1:00 PM, Philadelphia PA

Reporter: Stephen J. Williams, PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/03/real-time-coverage-bioconvention-bio2019-after-trumps-drug-pricing-blueprint-what-happens-next-a-view-from-washington-june-3-2019-100-pm-philadelphia-pa/

 

Real Time Coverage @BIOConvention #BIO2019: International Cancer Clusters Showcase June 3, 2019, Philadelphia PA

Reporter: Stephen J. Williams PhD @StephenJWillia2

https://pharmaceuticalintelligence.com/2019/06/03/real-time-coverage-bioconvention-bio2019-international-cancer-clusters-showcase-june-3-philadelphia-pa/

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