Sonya Dougal, PhD

New Age Therapeutics: Cannabis and CBD

CBD has become the ingredient driving a billion-plus dollar market of consumer products — researchers are sorting the hype from the hope.

Published May 1, 2020

By Sonya Dougal, PhD
Senior Vice President, Scientific Programs and Awards

Image courtesy of Gelpi via stock.adobe.com.

Enter any drugstore, vitamin chain, big box store, e-commerce site, gas-station convenience store or street corner bodega and you’ll find CBD products — in shampoos, oils, vapes, gummies and even treats for people and pets. Many of these products come with creative claims of the therapeutic benefits of CBD, true or not.

Such mass market hype and wishful thinking aside, Epidiolex®, an FDA-approved breakthrough treatment for rare drug-resistant epilepsies, is currently the only CBD product (cannabidiol) demonstrated to be effective by controlled studies in people.

CBD was previously known as the non-intoxicating sibling of the psychoactive intoxicant THC (tetrahydrocannabinol) — both cannabinoids produced in the marijuana plant. Traditional medicines have used cannabis for millennia, yet the United States first placed legal restrictions on its use in the 1920s and 1930s. In 1970, marijuana became illegal under Schedule I of the U.S. Controlled Substances Act.

CBD, though, received an enormous boost when the Farm Act of 2018 allowed the legal growth and sale of hemp products which include CBD. However, THC remained illegal, along with CBD produced from marijuana. These changes have only added to the ambiguity of CBD’s status from the perspectives of both law and science.

Imagine You’re a Caveman: The Human Endocannabinoid System

In the 1980s and 1990s, researchers identified cannabinoid receptors in humans (CB1 for THC and CB2 for CBD). What they were uncovering was the human body’s own endocannabinoid system (ECS).

“It’s a system as ancient as our immune system and our central nervous system. They co-evolved and our endocannabinoid system acts as a bridge between the two,” says Yuval Cohen, CEO and Director of Corbus Pharmaceuticals. “It’s designed to help us recover from trauma and is absolutely essential to life.”

To illustrate his point, Cohen said: “Imagine you’re a caveman and you just got mauled by a saber-toothed tiger. You are injured, you’re bleeding, you’re going into shock, you’re scared, you’re in a ton of pain; the wound is swollen and tender. You’re a hot mess. And that is where your endocannabinoid system kicks in. Without it, you’re going to die in that cave. It’s that simple.”

He is describing what many CBD promoters claim as general benefits of CBD in any form: pain management, seizure control, physical and psychological trauma relief, and tissue healing. Cohen, himself, sees the endocannabinoid system as an increasingly more explored therapeutic target for new treatments of disease.

Corbus is rationally designing synthetic signaling molecules to target the human ECS receptor molecule CB2 more selectively than a plant molecule could. Corbus’ lead product candidate, lenabasum, is designed to resolve chronic inflammation and fibrotic processes without interfering with the central nervous system.

Patient-Driven Advances

***Yuval Cohen****, **Ph.D**.*
CEO and Director, Corbus Pharmaceuticals, Inc.
Photo: Corbus Pharmaceuticals

Elizabeth Thiele, M.D., Ph.D., Director of the Pediatric Epilepsy Program at Massachusetts General Hospital, has firsthand experience with the pain and courage of parents who have exhausted existing medical options for treating extremely ill children. “I think what has really set this whole CBD story apart is that it was the patient community that drove the interest. It wasn’t big pharma saying ‘Here’s this drug we had in trials’,” she said.

Dr. Thiele has direct knowledge of a couple of related cases. One family moved from Maine to Colorado so they could access a CBD product for their daughter’s debilitating, treatment-resistant

epilepsy. A second family, from California, became interested in medical marijuana when their son had trouble with the restrictions of dietary therapy. But they encountered the same difficulty many experience with extracts: consistency of the product. Eventually, the California boy became patient one for Epidiolex in the United States.

“When I first got involved with this, one of my colleagues told me I was risking my career and another that I was wasting my time,” said Thiele. “But my approach has always been that I get parents who are desperate for treatments for their child and I need to support them.”

Still, Thiele firmly warns against trying CBD products whose contents you cannot confirm: “Right now, the only data we have is that purified CBD can be effective in helping children with refractory epilepsy. Parents should be very leery of claims of CBD curing or being good for everything.”

Above and Beyond Caveat Emptor

***Margaret Haney, Ph.D.***
*Professor of Neurobiology at Columbia University Medical Center*

When states legalize something, people assume it is safe. But experts at government agencies and university-affiliated research institutes continue to seek accurate data about potential health risks associated with cannabinoids, especially for people who may be more vulnerable because of age, neurological development, pregnancy, or interactions with other medications.

THC can affect fetal and adolescent neurological development, but CBD’s effects are still being determined. Data collected during studies of Epidiolex, for example, revealed that CBD affected availability levels of the antiepileptic clobazam, requiring dosage adjustments.

Scientists are actively studying the therapeutic potential of CBD with the removal of hemp from Schedule I.

Among her responsibilities, Susan Weiss, Ph.D., National Institute on Drug Abuse, Director, Division of Extramural Research, represents NIDA in talks on cannabis, marijuana and CBD. “Our goal is to get a better understanding, to get more knowledge and to be able to present evidence in an unbiased fashion,” she said. “We are also interested in developing therapeutics for cannabis use disorder.”

The Legal Hurdles

But NIDA research is not immune to legal ambiguity, jurisdictional conflicts, and their consequential impact on science. “Our researchers can’t actually purchase products from dispensaries because they would be in violation of federal law,” Weiss said. “As a result, NIDA must depend on people self-reporting what they’re using. But we don’t have access to those products to get a good sense of their dangers.”

Margaret Haney, Ph.D., Professor of Neurobiology, Columbia University Medical Center, is a leading researcher on cannabis use disorder but also explores the science behind specific areas of therapeutic value for THC and CBD. “I feel like there’s an anti-science moment right now where people are just believing,” she said. “They’re distrustful of pharma but not of the person selling them CBD at the farmer’s market. People aren’t aware that it’s just snake oil all over again.”

According to Haney, what most stands in the way of large-scale rigorous clinical studies is the DEA Schedule I status for cannabis and cannabinoids, which essentially shuts down the ability to conduct these studies. “If scientists could treat cannabis and its constituents as Schedule II, that would open things up tremendously,” she said.

The Entourage Effect

Ziva Cooper, Ph.D., Research Director of the UCLA Cannabis Research Initiative and Associate Professor in the Jane and Terry Semel Institute for Neuroscience and Human Behavior, understands the strong arguments for the purity, precision and predictability that synthesized THC or CBD molecules can provide in a rationalized drug design approach. But as a pharmacologist she wonders if potential benefits may be lost the further away a drug molecule moves from the whole plant.

“You want to know what the individual constituents do, but then there is this idea that the whole plant can offer greater therapeutic potential because it has all these different chemical components — some call this the entourage effect,” said Cooper.

“This hypothesis hasn’t really been tested in the clinic yet. We’re hoping to begin studying that very soon to determine if these different molecules in the plant work together to improve the potential therapeutic effects of cannabis. Will the combination of these chemicals be effective? What can we expect it will do? What are the risks we should be aware of? I’m confident that over the next 10 to 15 years we’ll actually be able to answer some of these questions,” said Cooper.

Dan Zenowich, a freelance health writer, contributed to this story.

Also read: What Near-Death and Psychedelic Experiences Reveal about Human Consciousness

The Challenge of Keeping Women in STEM

A woman conducts research in a science lab.

Efforts to close the gender gap in STEM by encouraging girls to study science have resulted in more young women considering careers in science. Yet systemic biases in academia create an uncertain future.

Published October 1, 2019

By Sonya Dougal, PhD
Senior Vice President, Scientific Programs and Awards

Many women who earn PhDs in life sciences choose to pursue non-academic careers during the critical period between receiving their doctoral degree and becoming an independent investigator. This gender specific phenomenon, described as a “leaky pipeline,” is a significant source of brain drain for academic and biomedical research.

Anne L. Taylor, MD, Columbia University Vagelos College of Physicians and Surgeons

A Biased Culture

Overt bias against women in the sciences is less common today than in decades past, but implicit bias remains a major challenge for male and female scientists alike.

According to Virginia Valian, distinguished professor at Hunter College and CUNY Graduate Center and director of the Hunter College Gender Equity Project, bias, whether conscious or not, shapes attitudes and behavior.

“The traits that are perceived to be better for science are those we often ascribe to men, such as independence and a focus on the task at hand, while women are nurturant, communal and express their feelings,” Valian said. “These gender schemas can impact reality, such that women’s achievements are systematically slightly under-acknowledged and men’s are slightly over-acknowledged.”

The Impact of Implicit Bias on Hiring Decisions

A slew of research studies examining the impact of implicit bias on hiring decisions and career advancement, conference presentations, manuscript authorship and grant funding, confirm Valian’s assertion. For example, in a 2012 study from Yale University, 100 male and female faculty members at top research institutions reviewed an identical resume for a hypothetical lab position with one change — the applicant was either a man or a woman. The resume bearing a man’s name was favored over the same resume with a woman’s name. Male candidates were perceived as more competent and offered higher salaries, while female candidates were rated as more likeable.

Navigating the transition from graduate school or postdoctoral researcher to independent investigator hinges largely on funding, and this too is an area rife with inequalities. While women receive grants from the National Institutes of Health (NIH) at about the same rate as their male peers, first-time female PIs are funded at comparatively lower levels.

A further consequence of implicit bias is that female professors do more of the service work within departments — taking on additional teaching responsibilities and serving on committees. While this work is essential, it does not support the attainment of federal and foundation grant funding needed to advance to academic leadership positions, nor is it valued during tenure review.

Not Just Women’s Work

The difficulties of juggling career and family demands have especially stark repercussions in the scientific workforce. A surprising 43 percent of women scientists — and nearly 25 percent of men — transition to part-time employment or leave their careers altogether after having their first child, according to Cech & Blair-Loy’s 2019 study of the impact of parenthood on STEM careers. In response, some institutions have implemented policies to address retention of both women and men.

“Having children should not be a permanent impediment to advancement,” said Ann Taylor, MD, vice dean of academic affairs at the Columbia University Vagelos College of Physicians and Surgeons. “Yet when women lessen their workload to accommodate their family responsibilities, we don’t do a good job putting them back on the path to leadership.”

Taylor believes that gender-neutral policies at Columbia, such as 13 weeks of paid leave for primary caregivers and an extra year on the tenure clock for each child, “really help support careers,” but acknowledges that some difficulties are harder to address. Grant funds often come with strict timelines, posing challenges for women and men who temporarily trim their work responsibilities during the early years of family life.

“You don’t have the luxury of saying, ‘I’m going to take this three-year grant and make it a six-year grant,’” Taylor said. “These are problems we have to solve, and we are actively thinking about how to do that.”

Creating the systemic, institutional change that Taylor and others envision requires support from male STEM professionals as well. Neuroscientist Paul Greengard — who was Vincent Astor Professor at The Rockefeller University until his death last year — was an early advocate for gender equality in academia.

“There’s absolutely no evidence one way or another as to whether there’s a difference between the sexes in terms of creativity, the most important parameter of scientific discovery,” Greengard said in an interview with The Rockefeller University in 2016.

Establishing a Preeminent Annual Prize for Women in STEM

When he won the Nobel Prize in 2000, Greengard donated his share of the honorarium to establish the preeminent annual prize for women in science — The Pearl Meister Greengard Prize. Named for Dr. Greengard’s mother, the prize sparked a robust program of advocacy and fundraising to support women scientists at Rockefeller. Aaron Mertz, director of the Aspen Institute Science & Society Program and a former postdoctoral fellow at Rockefeller, served as the vice president of the professional development group WISeR (Women in Science at Rockefeller).

“Men must be active contributors to discussions about gender equality, and have a significant role in creating a scientific environment in which women can flourish,” he said. “I firmly believe that women’s issues are men’s issues.”

Without men at the table, institutional change will not happen.

The New York Academy of Sciences is committed to a diverse balance of program speakers.

If You Can’t See It, You Can’t Be It

A culture of mentoring is vital in business — including guidance on salary negotiation, self-promotion and other skills necessary to advance in competitive fields — yet this type of support is a relative newcomer to academia. For early and mid-career women scientists, direction from senior colleagues can mean the difference between choosing an alternative career path and advancing to leadership positions.

Critically, Taylor highlighted that “the nature of mentorship can vary. Women are more likely to have mentorship that involves psychosocial support and are not provided with tactical career development strategies.” Columbia recently augmented their leadership and management programs to address the needs of women and diverse faculty by making both types of mentoring available for all faculty members, along with initiatives to ensure salary parity and timely promotions.

Men have so outnumbered women in scientific conference programs that a new word — manels — to describe all-male panels has entered the scientific lexicon. Feminist and activist Marie Wilson popularized the notion “if you can’t see it, you can’t be it” to encourage women’s leadership as role models.

To raise the visibility of women scientists, the New York Academy of Sciences requires gender parity among conference speakers. Forty-five percent of the speakers in the Academy’s 2018-2019 programming cycle were women, with an organizational goal of reaching 50 percent in the coming year.

Recently, NIH director Francis Collins released a statement indicating that he would decline participation at scientific conferences where “inclusiveness was not evident in the agenda,” writing that these parameters should include women and underrepresented groups. Conference organizers striving to meet that mandate may turn to Request a Woman Scientist, a database created by the 500 Women Scientists initiative — an organization galvanizing public support for STEM diversity and equality. In less than one year, more than 9,000 women scientists from 133 countries have added their profiles.

The Challenge Ahead

A 2018 paper by Lerchenmueller & Sorenson of the Yale School of Management noted that, “Rather than women dripping out of the STEM career pipe every centimeter along the way, they appear to pour out at one of the critical junctures.” This metaphor suggests that the first step to gender equality is raising awareness of the pressure points in women scientists’ careers such as the transition between trainee and independent investigator.

The path forward will require collective action between universities, government agencies and funders to remove systemic barriers and biases. Momentum is building for those willing to make the effort. As Taylor emphasized, “Equity and justice is work every single day.”

AI and Big Data to Improve Healthcare

Am image of a stethoscope and a tablet displaying a health/medical app.

The next decade will be a pivotal one for the integration of AI and Big Data into healthcare, bringing both tremendous advantages as well as challenges.

Published May 1, 2019

By Sonya Dougal, PhD
Senior Vice President, Scientific Programs and Awards

One of the most common causes of death among hospital patients in the United States is also one of the most preventable — sepsis.

Sepsis symptoms can resemble other common conditions, making it notoriously challenging to identify, yet early diagnosis and intervention are critical to halting the disease’s rapid progress. In children, for each hour that sepsis treatment is delayed, the risk of death increases by as much as 50 percent.

Novel innovations, such as the one pioneered by Suchi Saria, director of the Machine Learning and Healthcare Lab and the John C. Malone Assistant Professor at Johns Hopkins University, are helping to reverse this trend. In 2013, Saria and a team of collaborators began testing a machine learning algorithm designed to improve early diagnosis and treatment of sepsis.

Using troves of current and historical patient data, Saria’s artificial intelligence (AI) system performs real-time analysis of dozens of inpatient measurements from electronic health records (EHRs) to monitor physiologic changes that can signal the onset of sepsis, then alert physicians in time to intervene.

“Some of the greatest therapeutic benefits we’re going to see in the future will be from computational tools that show us how to optimize and individualize medical care,” Saria said. She explained that the emergence of EHRs, along with the development of increasingly sophisticated AI algorithms that derive insights from patient data, will fuel a seismic shift in medicine — one that merges “what we are learning from the data, with what we already know from our best physicians and best practices.”

Electronic Health Records: A Gold Mine for Computer Scientists

EHRs have become a data gold mine for computer scientists and other researchers who are tapping them in ways designed to improve physician-patient encounters, inform and simplify treatment decisions, and reduce diagnostic errors. Like many other technological advances, though, there are those physicians who regard EHR systems with less enthusiasm.

A 2016 American Medical Association study revealed that physicians spend nearly twice as much time engaged in EHR tasks than they do in direct clinical encounters. Physician and author Atul Gawande recently lamented in The New Yorker that “a system that promised to increase my mastery over my work has, instead, increased my work’s mastery over me.”

Yet, data scientist Nicholas Tatonetti, the Herbert Irving Assistant Professor of Biomedical Informatics at Columbia University envisions a day when such AI algorithms will enable physicians to deepen their interaction with patients by freeing them from the demands of entering data into the EHR. Tatonetti has designed a system using natural language processing algorithms that takes accurate notes while physicians talk with patients about their symptoms. Like Saria’s AI system, Tatonetti’s takes advantage of the vast amount of data captured in EHRs to alert physicians in real time to potentially dangerous drug interactions or side effects.

Unknown Interactions

Anyone who has filled a prescription is familiar with the patient information leaflet that accompanies each medication, detailing potential side effects and known drug interactions. But what about the unknown interactions between medications?

Tatonetti has also developed an algorithm to analyze existing data in electronic health records, along with information in the FDA’s “adverse outcomes” database, to tease out previously unknown interactions between drugs. In 2016, he published a study showing that ceftriaxone, a common antibiotic, can interact with lansoprazole, an over-the-counter heartburn medication, increasing a patient’s risk of a potentially dangerous form of cardiac arrhythmia.

As data-driven AI techniques become more accessible to clinicians, the treatment of conditions both straightforward, like hypertension, and highly complex, such as cancer, will be transformed.

A Paradigm Shift in Physician-Patient Interactions

Ajay Royyuru, vice president of healthcare and life sciences research at IBM and an IBM Fellow, explained that, “when a practitioner makes a patient-specific decision, the longitudinal trail of information from thousands of other patients from that same clinic is often not empowering that physician to make that decision. The data is there, but it’s not yet being used to provide those insights.”

In the coming years, physicians and researchers will be able to aggregate and better utilize EHR data to guide treatment decisions and help set patients’ expectations.

The ability to draw on information from tens or even hundreds of thousands of patients, in addition to a physician’s own experience and expertise, could represent a paradigm shift in physician-patient interactions, according to Bethany Percha, assistant professor at the Icahn School of Medicine at Mount Sinai, and CTO of the Precision Health Enterprise, a team that turns AI research into tangible products for the health system.

“Big Data offers us the promise of using data to have a real dialogue with patients — if you’re newly diagnosed with cancer, it means giving people a realistic, data-driven assessment of what their future is likely to be,” she said.

Biases and Pitfalls

Despite the surge of interest and investment in AI over the past two decades, significant barriers to its widespread application and deployment in healthcare remain.

AI systems that tap current and historical patient health data risk reinforcing well-noted biases and embedded disparities. Medical research and clinical trials have long suffered from a lack of both ethnic and gender diversity, and EHR data may reflect patient outcomes and treatment decisions influenced by race, sex or socioeconomic status. AI systems that “learn” from datasets that include these biases will inherently share and perpetuate them.

Percha noted that greater transparency within the algorithms themselves — such as systems that learn which features an algorithm uses to make a prediction — could alert users to obvious examples of bias. Removing bias from AI algorithms is a work in progress, but the research community’s awareness of the issue and efforts to address it mirror a greater push to eliminate bias and decrease inequities in medicine overall. Optimistically, Percha noted that Big Data and AI may ultimately help create a more level playing field in healthcare delivery.

“Clinical decisions made on the basis of data have the potential to be much more standardized across different health facilities, so people who are in a rural area, for example, might have access to the same decision-making benefits as someone in a city,” she said.

Patient Data Privacy

Ensuring patient data privacy is another hot-button issue. Training artificial intelligence systems requires access to massive troves of patient data. Despite the fact that this information is anonymized, some patient advocates and bioethicists object to this access without explicit permission from the patients themselves.

Another privacy issue looms equally large: how to safely collect and protect the streams of potentially useful health data generated by wearable devices and in-home technologies without making patients and consumers feel, in Royyuru’s words, “like they are living their lives in front of a camera.” Studies have shown that data from smartphone apps can provide valuable information about the progression of certain diseases, such as Parkinson’s.

Wearables and in-home IoT devices can also extend the realm of clinical observation well beyond the doctor’s office, revealing, for example, important details about a Parkinson’s patient’s ability to complete the tasks of daily living. Yet Royyuru emphasizes that unless patients trust that their data will be kept private and ethically utilized, these technologies will fizzle long before they’re widely adopted.

Building Trust

The next decade will be a pivotal one for the integration of AI and Big Data into healthcare, bringing both tremendous advantages as well as challenges. Some applications of AI, such as image recognition, are already especially well-suited to healthcare — AI algorithms often match or even outperform radiologists in interpreting medical images — while others are far from ready for widespread use.

Saria, who has deployed her system successfully at multiple hospitals says, “physicians often greet news of AI breakthroughs with skepticism because they’re being over-promised results without clear data demonstrating this promise. True integration and adoption of AI requires not just careful attention to physician workflows, but transparency into exactly how and why an algorithm has arrived at a particular recommendation.”

Rather than replacing or challenging a physician’s place in the healthcare ecosystem, Saria believes that AI has the ability to lighten the load, and as algorithms improve, generate diagnostic and treatment recommendations that physicians and patients can both deem trustworthy.

“We are still figuring out how to make real-time information available so that it’s possible for physicians or expert decision-makers to understand, interpret and determine the right thing to do — and to do that in an error-free way, over and over again,” Saria said. “It’s a high-stakes scenario, and you want to get to a good outcome.”