Famous people who die at age 27, such as Janis Joplin, Jimi Hendrix and Amy Winehouse, get even more famous because of the mythology surrounding that number—an example of how modern folklore emerges

The Martian new year arrives with the Red Planet’s vernal equinox. Explaining why requires a deep dive into celestial mechanics and Earth’s calendrical history

A team at Columbia University School of Engineering and Applied Science has developed a technique to enhance chimeric antigen receptor (CAR) T cell therapy in solid tumors. The technique involves engineering E. coli bacteria, that naturally tend to accumulate in the immune privileged core of solid tumors. The bacteria have been engineered to interact with […]

Researchers at Rice University have developed a magnetoelectric material that converts a magnetic field into an electric field. The material can be formulated such that it can be injected into the body, near a neuron, and then an alternating magnetic field can be applied to the area from outside the body. Magnetic fields are very […]

Researchers at the Wyss Institute at Harvard University have developed a microfluidic chip that can recreate some of the features of radiation-induced lung injury. The lungs are very sensitive to radiation, and this can limit the application of radiotherapy to treat cancer. Accurately modeling radiation-induced lung injury could assist in developing new methods to prevent […]

Researchers at the National University of Singapore have developed a magneto-responsive hydrogel wound dressing that also contains two different regenerative cell types. The hydrogel is also embedded with magnetic particles that can be stimulated using an external magnetic field. The action of the magnetic field on the gel-encapsulated particles causes mechanical stresses within the gel […]

On October 8, 2024, Drug Channels Institute will release our 2024-25 Economic Report on Pharmaceutical Wholesalers and Specialty Distributors. This report—our fifteenth edition—remains the most comprehensive, fact-based tool for understanding and analyzing the large and growing U.S. pharmaceutical distribution industry.

9 chapters, 350+ pages, 178 exhibits, 750+ endnotes: There is nothing else available that comes close to this valuable resource.

We are providing you with the opportunity to preorder this thoroughly updated, revised, and expanded 2024-25 edition at special discounted prices. This means that you can be among the first to access our new report. Those who preorder will receive a download link before October 8.

• Review pricing/license options and place a preorder

• Download a free pre-publication report overview (including key industry trends, What's New in this edition, the Table of Contents, and a List of Exhibits)

You can pay online with all major credit cards (Visa, MasterCard, American Express, and Discover) or via PayPal. Click here to contact us if you would like to pay by corporate check or ACH.

Special preorder and launch pricing discounts will be valid through October 23, 2024.

Read on for more details.
Read more »

Today’s guest post comes from Timothy Nielsen, Vice President of Customer Success at AssistRx.

Timothy discusses the affordability and patient journey challenges of specialty-lite products for patients, manufacturers, and health care providers. He explains how AssistRx's Advanced Access Anywhere (AAA) solution streamlines processes for specialty-lite products and facilitates enrollment via a digital hub.

To learn more, register for AssistRx's free webinar on October 8: Meet Your Patients Where They Are & Gain Visibility: Even at Retail.

Read on for Timothy’s insights.
Read more »

I am pleased to announce Drug Channels Institute's new 2024–25 Economic Report on Pharmaceutical Wholesalers and Specialty Distributors, available for purchase and immediate download.

• Download a free report overview (including key industry trends, the Table of Contents, and a List of Exhibits)

• Review pricing/license options and download the full 2024-25 report

We’re offering special discounted pricing if you order before October 23, 2024.

2024–25 Economic Report on Pharmaceutical Wholesalers and Specialty Distributors—our 15th edition--remains the most comprehensive, fact-based tool for understanding and analyzing the large and growing U.S. pharmaceutical distribution industry. This 2024-25 edition includes substantial new material—outlined on page vii of the report overview.

9 chapters, 380+ pages, 178 exhibits, more than 750 endnotes: There is nothing else available that comes close to this valuable resource.

You can pay online with all major credit cards (Visa, MasterCard, American Express, and Discover) or via PayPal. Click here to contact us if you would like to pay by corporate check or ACH.

Email Paula Fein (paula@drugchannels.net) if you’d like to bundle your report purchase with access to DCI’s video webinars.

If you preordered the report, you should have already received an email with download instructions last week. Please contact us if you did not receive your email.

Read on for some additional details.
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As regular readers of Drug Channels know, U.S. distribution and dispensing channels for prescription drugs are undergoing significant evolution and consolidation as the changing economics of pharmaceuticals challenge conventional business models.

During this period of volatility, the core business model of the Big Three public pharmaceutical distribution companies—Cardinal Health, Cencora, and McKesson—remains intact. Put simply: Buy low, sell high, collect early, and pay late.

But as I explain below, wholesalers continue to position themselves as essential intermediaries by expanding their industry position and strengthening their economic fundamentals.

Read on for five key pricing, pharmacy, provider, and manufacturer trends that are driving the U.S. drug wholesaling industry.

For even more, check out DCI's new 2024-25 Economic Report on Pharmaceutical Wholesalers and Specialty Distributors, the fifteenth edition of our deep dive into wholesale distribution channels.Click here to download a free report overview (including key industry trends, the table of contents, and a list of exhibits)
Read more »

Eeek! It's time for Drug Channels’ Halloween roundup of terrifying tales to share with your ghoulish fiends. This month’s tricks and treats:

• Spooky! Blue Shield of California frightens away the gross-to-net bubble with its Humira biosimilar strategy

• Vampiric! Prior authorization sinks its fangs into providers’ time

• Wicked! How the IRA will put a stake through specialty physician practices

• Eerie! Google’s monstrous AI podcasts leave me petrified

• Zoinks! Join the vampire hunters at Drug Channels Institute

Plus, Dr. Glaucomflecken tells us a frightening tale of copayments.

P.S. Stretch out your arms and join the ever-growing zombie horde who shamble after me on LinkedIn. You’ll find my ghostly rantings along with commentary from the undead hordes in the DCI community.
Read more »

Prepare to witness the convergence of strategy and science at the highly anticipated the DIA 2024 Global Annual Meeting! Immerse yourself in four days of conversations that don’t happen anywhere else, where strategic thinking seamlessly intertwines with scientific innovation: Elevate Your Professional Profile Expand your knowledge base with continuing education opportunities available virtually from June […]

The post Science Meets Strategy at DIA 2024 first appeared on ACRO.

FDA’s mission is “at risk” because of inadequate funding. So says Alliance for a Stronger FDA President Diane Dorman, testifying before the FDA Science Board. Her remarks come 5 years after the Science Board made a similar declaration, concluding that decades of underfunding had left FDA without the resources to fulfill its mandate and make science-based decisions. Congress responded with more monies for the agency, but since then the FDA’s workload has increased even faster. The current threat to FDA comes from two sources: four major new laws to implement since 2009; and changes in the environment in which FDA operates, notably acceleration of globalization and increasing scientific complexity. Ms. Dorman’s remarks are reprinted below. If you care about FDA, FDA Matters urges you to read her testimony, go to the Alliance’s site (www.StrengthenFDA.org) and join.

FDA Matters appreciates your patience. New columns will be coming in June, with fresh insights into FDA and the FDA-regulated world.  Meantime, I write a weekly column in the Friday Update, published by the Alliance for a Stronger FDA. If you want to receive the Friday Update when it's published each week, you can sign […]

Effective on October 21st of this year, the Federal Trade Commission (FTC) issued a new final rule that is intended to better combat ​“fake” reviews and testimonials by prohibiting the sale or purchase of “fake reviews” as well as granting the agency the opportunity to seek civil penalties against ​willful violators. The FTC made only […]

We still don’t know what COVID-19 is doing to the heart or how we should be investigating it and treating it. Last month JAMA Cardiology published a German cohort study of 100 patients recently recovered from COVID-19… A number of striking problems with the study were noted on Twitter…...

Click here to continue reading...

<p>In May 2024, Malaysia’s National Pharmaceutical Regulatory Agency (NPRA) announced that it will trial new timelines for variation applications&nbsp;of registered pharmaceutical products and natural health supplements (TMHS).</p>

<p>In October 2024, China based Bio-Thera Solutions&nbsp;(Bio-Thera)&nbsp;and Hungary’s Gedeon Richter announced they have reached an exclusive commercialization and license agreement for BAT2206, a biosimilar candidate to&nbsp;Johnson &amp; Johnson’s Stelara (ustekinumab).</p>

The Royal Pharmaceutical Society and the British Pharmaceutical Students’ Association have called for all overseas candidates to sit the March 2021 registration assessment in their home countries.

The Pharmaceutical Services Negotiating Committee is in talks with the government over potential plans to distribute COVID-19 treatments in primary care.

The type 2 diabetes mellitus drug semaglutide is effective for weight loss in non-diabetic overweight or obese adults, when taken alongside a reduced-calorie diet and exercise, researchers have found.

Researchers around the world are working at record speed to find the best ways to treat and prevent COVID-19, from investigating the possibility of repurposing existing drugs to searching for novel therapies against the virus.

Pharmacy negotiators have discussed proposals to take “a patient registration-based approach” to the community pharmacy contractual framework.

Novartis recently announced the acquisition of Mariana Oncology, an emerging biotech focused on advancing a radioligand therapeutics platform, for up to $1.75 billion in upfronts and future milestones. The capstone of its three short years of operations, this acquisition represents

The post Mariana Oncology’s Radiopharm Platform Acquired By Novartis appeared first on LifeSciVC.

By Ivana Magovčević-Liebisch, CEO of Vigil Neuroscience, as part of the From The Trenches feature of LifeSciVC In the last decade, our industry has made great strides in combating cancer by harnessing the body’s own immune system. As it was

The post Neuro-Immunology: The Promise Of A Differentiated Approach To Neurodegenerative Disease appeared first on LifeSciVC.

By Peter Tummino, CSO of Nimbus Therapeutics, as part of the From The Trenches feature of LifeSciVC  “Over the next five to 10 years, our goal is to become a company that’s leading the world in personalized medicines, a company

The post Medicinal Chemistry In The Age Of Artificial Intelligence appeared first on LifeSciVC.

The UK body that oversees health research is writing a new strategy on clinical trial transparency and it wants to hear opinions on it. The Health Research Authority (HRA) says its strategy aims to “make transparency easy, make compliance clear and make information public.” It has opened a public consultation on the strategy and some […]

An AllTrials report for the House of Commons Science and Technology Select Committee this week has found that 33 NHS trust sponsors and six UK universities are reporting none of their clinical trial results, while others have gone from 0% to 100% following an announcement from the Select Committee in January that universities and NHS […]

When university and hospital trusts were called to the UK parliament last year to answer questions on why they were not following the rules on reporting results, we saw how effective the questioning from politicians was. Those of you who watched the parliamentary session saw the pressure the university representatives were put under. Because the politicians asked […]

New research has shown that the majority of clinical trials which should be following the US law on reporting results aren’t. Less than half (41%) of clinical trial results were reported on time and 1 in 3 trials (36%) remain unreported. The research also found that clinical trials sponsored by companies are the most likely […]

A judge in New York has ruled that hundreds of clinical trials registered on ClinicalTrials.gov are breaking the law by not reporting results. The ruling came in a court case launched against the US Department of Health and Human Services by two plaintiffs, a family doctor and a professor of journalism. The case focused on […]

Even by the already-painfully-embarrassingly-low standards of clinical trial enrollment in general, patient enrollment in cancer clinical trials is slow. Horribly slow. In many cancer trials, randomizing one patient every three or four months isn't bad at all – in fact, it's par for the course. The most
commonly-cited number is that only 3% of cancer patients participate in a trial – and although exact details of how that number is measured are remarkably difficult to pin down, it certainly can't be too far from reality.

Ultimately, the cost of slow enrollment is borne almost entirely by patients; their payment takes the form of fewer new therapies and less evidence to support their treatment decisions.

So when a couple dozen thousand of the world's top oncologists fly into Chicago to meet, you'd figure that improving accrual would be high on everyone’s agenda. You can't run your trial without patients, after all.

But every year, the annual ASCO meeting underdelivers in new ideas for getting more patients into trials. I suppose this a consequence of ASCO's members-only focus: getting the oncologists themselves to address patient accrual is a bit like asking NASCAR drivers to tackle the problems of aerodynamics, engine design, and fuel chemistry.

Nonetheless, every year, a few brave souls do try. Here is a quick rundown of accrual-related abstracts at this year’s meeting, conveniently sorted into 3 logical categories:

1. As Lord Kelvin may or may not have said, “If you cannot measure it, you cannot improve it.”

• Abstract e15572: Inadequate data availability on clinical trial accrual and its effect on progress in cancer research

Probably the most sensible of this year's crop, because rather than trying to make something out of nothing, the authors measure exactly how pervasive the nothing is. Specifically, they attempt to obtain fairly basic patient accrual data for the last three years' worth of clinical trials in kidney cancer. Out of 108 trials identified, they managed to get – via search and direct inquiries with the trial sponsors – basic accrual data for only 43 (40%).

That certainly qualifies as “terrible”, though the authors content themselves with “poor”.

Interestingly, exactly zero of the 32 industry-sponsored trials responded to the authors' initial survey. This fits with my impression that pharma companies continue to think of accrual data as proprietary, though what sort of business advantage it gives them is unclear. Any one company will have only run a small fraction of these studies, greatly limiting their ability to draw anything resembling a valid conclusion.

• Abstract TPS6645: Predictors of accrual success for cooperative group trials: The Cancer and Leukemia Group B (Alliance) experience

CALGB investigators look at 110 trials over the past 10 years to see if they can identify any predictive markers of successful enrollment. Unfortunately, the trials themselves are pretty heterogeneous (accrual periods ranged from 6 months to 8.8 years), so finding a consistent marker for successful trials would seem unlikely.

And, in fact, none of the usual suspects (e.g., startup time, disease prevalence) appears to have been significant. The exception was provision of medication by the study, which was positively associated with successful enrollment.

The major limitation with this study, apart from the variability of trials measured, is in its definition of “successful”, which is simply the total number of planned enrolled patients. Under both of their definitions, a slow-enrolling trial that drags on for years before finally reaching its goal is successful, whereas if that same trial had been stopped early it is counted as unsuccessful. While that sometimes may be the case, it's easy to imagine situations where allowing a slow trial to drag on is a painful waste of resources – especially if results are delayed enough to bring their relevance into question.

Even worse, though, is that a trial’s enrollment goal is itself a prediction. The trial steering committee determines how many sites, and what resources, will be needed to hit the number needed for analysis. So in the end, this study is attempting to identify predictors of successful predictions, and there is no reason to believe that the initial enrollment predictions were made with any consistent methodology.

2. If you don't know, maybe ask somebody?

• Abstract 8592: Strategies to overcome barriers to accrual (BtA) to NCI-sponsored clinical trials: A project of the NCI-Myeloma Steering Committee Accrual Working Group (NCI-MYSC AWG)
  
• Abstract 1596: Rapid online feedback to improve clinical trial accrual: CODEL anaplastic glioma (AG) (NCCTG/Alliance N0577) as a model

With these two abstracts we celebrate and continue the time-honored tradition of alchemy, whereby we transmute base opinion into golden data. The magic number appears to be 100: if you've got 3 digits' worth of doctors telling you how they feel, that must be worth something.

In the first abstract, a working group is formed to identify and vote on the major barriers to accrual in oncology trials. Then – and this is where the magic happens – that same group is asked to identify and vote on possible ways to overcome those barriers.

In the second, a diverse assortment of community oncologists were given an online survey to provide feedback on the design of a phase 3 trial in light of recent new data. The abstract doesn't specify who was initially sent the survey, so we cannot tell response rate, or compare survey responders to the general population (I'll take a wild guess and go with “massive response bias”).

Market research is sometimes useful. But what cancer clinical trial do not need right now are more surveys are working groups. The “strategies” listed in the first abstract are part of the same cluster of ideas that have been on the table for years now, with no appreciable increase in trial accrual.

3. The obligatory “What the What?” abstract

• Abstract 6564: Minority accrual on a prospective study targeting a diverse U.S. breast cancer population: An analysis of Wake Forest CCOP research base protocol 97609

The force with which my head hit my desk after reading this abstract made me concerned that it had left permanent scarring.

If this had been re-titled “Poor Measurement of Accrual Factors Leads to Inaccurate Accrual Reporting”, would it still have been accepted for this year’s meeting? That's certainly a more accurate title.

Let’s review: a trial intends to enroll both white and minority patients. Whites enroll much faster, leading to a period where only minority patients are recruited. Then, according to the authors, “an almost 4-fold increase in minority accrual raises question of accrual disparity.” So, sites will only recruit minority patients when they have no choice?

But wait: the number of sites wasn't the same during the two periods, and start-up times were staggered. Adjusting for actual site time, the average minority accrual rate was 0.60 patients/site/month in the first part and 0.56 in the second. So the apparent 4-fold increase was entirely an artifact of bad math.

This would be horribly embarrassing were it not for the fact that bad math seems to be endemic in clinical trial enrollment. Failing to adjust for start-up time and number of sites is so routine that not doing it is grounds for a presentation.

The bottom line

What we need now is to rigorously (and prospectively) compare and measure accrual interventions. We have lots of candidate ideas, and there is no need for more retrospective studies, working groups, or opinion polls to speculate on which ones will work best.  Where possible, accrual interventions should themselves be randomized to minimize confounding variables which prevent accurate assessment. Data needs to be uniformly and completely collected. In other words, the standards that we already use for clinical trials need to be applied to the enrollment measures we use to engage patients to participate in those trials.

This is not an optional consideration. It is an ethical obligation we have to cancer patients: we need to assure that we are doing all we can to maximize the rate at which we generate new evidence and test new therapies.

[Image credit: Logarithmic turtle accrual rates courtesy of Flikr user joleson.]

PDUFA V commitments signal a strong commitment to tolerance of open debate in the face of uncertainty.

I can admit to a rather powerful lack of enthusiasm when reading about interpersonal squabbles. It’s even worse in the scientific world: when I read about debates getting mired in personal attacks I tend to simply stop reading and move on to something else.

However, the really interesting part of this week’s meeting of an FDA joint Advisory Committee to discuss the controversial diabetes drug Avandia – at least in the sense of likely long-term impact – is not the scientific question under discussion, but the surfacing and handling of the raging interpersonal battle going on right now inside the Division of Cardiovascular and Renal Products. So I'll have to swallow my distaste and follow along with the drama.

Two words that make us mistrust Duke:  Anil Potti Christian Laettner

Not that the scientific question at hand – does Avandia pose significant heart risks? – isn't interesting. It is. But if there’s one thing that everyone seems to agree on, it’s that we don’t have good data on the topic. Despite the re-adjudication of RECORD, no one trusts its design (and, ironically, the one trial with a design to rigorously answer the question was halted after intense pressure, despite an AdComm recommendation that it continue).  And no one seems particularly enthused about changing the current status of Avandia: in all likelihood it will continue to be permitted to be marketed under heavy restrictions. Rather than changing the future of diabetes, I suspect the committee will be content to let us slog along the same mucky trail.

The really interesting question, that will potentially impact CDER for years to come, is how it can function with frothing, open dissent among its staffers. As has been widely reported, FDA reviewer Tom Marciniak has written a rather wild and vitriolic assessment of the RECORD trial, excoriating most everyone involved. In a particularly stunning passage, Marciniak appears to claim that the entire output of anyone working at Duke University cannot be trusted because of the fraud committed by Duke cancer researcher Anil Potti:

I would have thought that the two words “Anil Potti” are sufficient for convincing anyone that Duke University is a poor choice for a contractor whose task it is to confirm the integrity of scientific research. 

(One wonders how far Marciniak is willing to take his guilt-by-association theme. Are the words “Cheng Yi Liang” sufficient to convince us that all FDA employees, including Marciniak, are poor choices for deciding matter relating to publicly-traded companies? Should I not comment on government activities because I’m a resident of Illinois (my two words: “Rod Blagojevich”)?)

Rather than censoring or reprimanding Marciniak, his supervisors have taken the extraordinary step of letting him publicly air his criticisms, and then they have in turn publicly criticized his methods and approach.

I have been unable to think of a similar situation at any regulatory agency. The tolerance for dissent being displayed by FDA is, I believe, completely unprecedented.

And that’s the cliffhanger for me: can the FDA’s commitment to transparency extend so far as to accommodate public disagreements about its own approval decisions? Can it do so even when the disagreements take an extremely nasty and inappropriate tone?

• Rather than considering that open debate is a good thing, will journalists jump on the drama and portray agency leadership as weak and indecisive?
• Will the usual suspects in Congress be able to exploit this disagreement for their own political gain? How many House subcommittees will be summoning Janet Woodcock in the coming weeks?

I think what Bob Temple and Norman Stockbridge are doing is a tremendous experiment in open government. If they can pull it off, it could force other agencies to radically rethink how they go about crafting and implementing regulations. However, I also worry that it is politically simply not a viable approach, and that the agency will ultimately be seriously hurt by attacks from the media and legislators.

Where is this coming from?

As part of its recent PDUFA V commitment, the FDA put out a fascinating draft document, Structured Approach to Benefit-Risk Assessment in Drug Regulatory Decision-Making. It didn't get a lot of attention when first published back in February (few FDA documents do). However, it lays out a rather bold vision for how the FDA can acknowledge the existence of uncertainty in its evaluation of new drugs. Its proposed structure even envisions an open and honest accounting of divergent interpretations of data:

When they're frothing at the mouth, even Atticus doesn't let them publish a review

A framework for benefit-risk decision-making that summarizes the relevant facts, uncertainties, and key areas of judgment, and clearly explains how these factors influence a regulatory decision, can greatly inform and clarify the regulatory discussion. Such a framework can provide transparency regarding the basis of conflicting recommendations made by different parties using the same information.

(Emphasis mine.)

Of course, the structured framework here is designed to reflect rational disagreement. Marciniak’s scattershot insults are in many ways a terrible first case for trying out a new level of transparency.

The draft framework notes that safety issues, like Avandia, are some of the major areas of uncertainty in the regulatory process. Contrast this vision of coolly and systematically addressing uncertainties with the sad reality of Marciniak’s attack:

In contrast to the prospective and highly planned studies of effectiveness, safety findings emerge from a wide range of sources, including spontaneous adverse event reports, epidemiology studies, meta-analyses of controlled trials, or in some cases from randomized, controlled trials. However, even controlled trials, where the evidence of an effect is generally most persuasive, can sometimes provide contradictory and inconsistent findings on safety as the analyses are in many cases not planned and often reflect multiple testing. A systematic approach that specifies the sources of evidence, the strength of each piece of evidence, and draws conclusions that explain how the uncertainty weighed on the decision, can lead to more explicit communication of regulatory decisions. We anticipate that this work will continue beyond FY 2013.

I hope that work will continue beyond 2013. Thoughtful, open discussions of real uncertainties are one of the most worthwhile goals FDA can aspire to, even if it means having to learn how to do so without letting the Marciniaks of the world scuttle the whole endeavor.

[Fair Warning: I have generally tried to keep this blog separate from my corporate existence, but am making an exception for two quick posts about the upcoming DIA 2013 Annual Meeting.]

Improving Enrollment in Pediatric Clinical Trials

Logistically, ethically, and emotionally, involving children in medical research is greatly different from the same research in adults. Some of the toughest clinical trials I've worked on, across a number of therapeutic areas, have been pediatric ones. They challenge you to come up with different approaches to introducing and explaining clinical research – approaches that have to work for doctors, kids, and parents simultaneously.

On Thursday June 27, Don Sickler, one of my team members, will be chairing a session titled “Parents as Partners: Engaging Caregivers for Pediatric Trials”. It should be a good session.

Joining Don are 2 people I've had the pleasure of working with in the past. Both of them combine strong knowledge of clinical research with a massive amount of positive energy and enthusiasm (no doubt a big part of what makes them successful).

However, they also differ in one key aspect: what they work on. One of them – Tristen Moors from Hyperion Therapeutics - works on an ultra-rare condition, Urea Cycle Disorder, a disease affecting only a few hundred children every year. On the other hand, Dr. Ann Edmunds is an ENT working in a thriving private practice. I met her because she was consistently the top enroller in a number of trials relating to tympanostomy tube insertion. Surgery to place “t-tubes” is one of the most common and routine outpatients surgeries there is, with an estimated half million kids getting tubes each year.

Each presents a special challenge: for rare conditions, how do you even find enough patients? For routine procedures, how do you convince parents to complicate their (and their children’s) lives by signing up for a multi-visit, multi-procedure trial?

Ann and Tristen have spent a lot of time tackling these issues, and should have some great advice to give.

For more information on the session, here’s Don’s posting on our news blog.

Are we looking at our enrollment data in the right way?

Session Details:

June 25, 1:45PM - 3:15PM

• Session Number: 241
• Room Number: 205B

1. Enrollment Analytics: Moving Beyond the Funnel
Paul Ivsin
VP, Consulting Director
CAHG Clinical Trials

2. Use of Analytics for Operational Planning
Diana Chung, MSc
Associate Director, Clinical Operations
Gilead
3. Using Enrollment Data to Communicate Effectively with Sites
Gretchen Goller, MA
Senior Director, Patient Access and Retention Services
PRA

This morning I ran across a bit of a coffee-spitter: in the middle of an otherwise opaquely underinformative press release fromTranscelerate Biopharma about the launch of their

Counterfeits flooding the market? Really?

"Comparator Network" - which will perhaps streamline member companies' ability to obtain drugs from each other for clinical trials using active comparator arms -  the CEO of the consortium, Dalvir Gill, drops a rather remarkable quote:

"Locating and accessing these comparators at the right time, in the right quantities and with the accompanying drug stability and regulatory information we need, doesn't always happen efficiently. This is further complicated by infiltration of the commercial drug supply chain by counterfeit drugs.  With the activation of our Comparator Network the participating TransCelerate companies will be able to source these comparator drugs directly from each other, be able to secure supply when they need it in the quantities they need, have access to drug data and totally mitigate the risk of counterfeit drugs in that clinical trial."

Counterfeit drugs have even been known to have been involved in clinical drug trials.^{[citation needed]}

The articles identified through the search had to match the corresponding trial in terms of the information registered at ClinicalTrials.gov (i.e., same objective, same sample size, same primary outcome, same location, same responsible party, same trial phase, and same sponsor) and had to present results for the primary outcome. 

So it appears that a reviewed had to score the journal article as an exact match on 8 criteria in order for the trial to be considered the same. That could easily lead to exclusion of journal articles on the basis of very insubstantial differences. The authors provide no detail on this; and again, that would be easy to verify if the study dataset was published. 

The reason I harp on this, and worry about the matching methodology, is that two of the authors of this study were also involved in a methodologically opaque and flawed study about clinical trial results posted in the JCO. In that study, as well, the authors appeared to use an incorrect methodology to identify published clinical trials. When I pointed the issues out, the corresponding author merely reiterated what was already (insufficiently) in the paper's Methodology section.

I find it strange beyond belief, and more than a little hypocritical, that researchers would use a public, taxpayer-funded database as the basis of their studies, and yet refuse to provide their data for public review. There are no technological or logistical issues preventing this kind of sharing, and there is an obvious ethical point in favor of transparency.

But if the authors are reasonably close to correct in their results, I'm not sure what to make of this study. 

The Nature article covering this study contend that

[T]he [ClinicalTrials.gov] database was never meant to replace journal publications, which often contain longer descriptions of methods and results and are the basis for big reviews of research on a given drug.

I suppose that some journal articles have better methodology sections, although this is far from universally true (and, like this study here, these methods are often quite opaquely described and don't support replication). As for results, I don't believe that's the case. In this study, the opposite was true: ClinicalTrial.gov results were generally more complete than journal results. And I have no idea why the registry wouldn't surpass journals as a more reliable and complete source of information for "big reviews".

Perhaps it is a function of my love of getting my hands dirty digging into the data, but if we are witnessing a turning point where journal articles take a distant back seat to the ClinicalTrials.gov registry, I'm enthused. ClinicalTrials.gov is public, free, and contains structured data; journal articles are expensive, unparsable, and generally written in painfully unclear language. To me, there's really no contest. 

Carolina Riveros, Agnes Dechartres, Elodie Perrodeau, Romana Haneef, Isabelle Boutron, & Philippe Ravaud (2013). Timing and Completeness of Trial Results Posted at ClinicalTrials.gov and Published in Journals PLoS Medicine DOI: 10.1371/journal.pmed.1001566

The good folks down at eyeforpharma have asked me to write a few blog posts in the run-up to their Patient Centered Clinical Trials conference in Boston this September. In my second article -Buzzword Innovation: The Patient Centricity “Fad” and the Token Patient - I went over some concerns I have regarding the sudden burst of enthusiasm for patient centricity in the clinical trial world.

Apparently, that hit a nerve – in an email, Ulrich Neumann tells me that “your last post elicited quite a few responses in my inbox (varied, some denouncing it as a fad, others strongly protesting the notion, hailing it as the future).”

In preparing my follow up post, I’ve spoken to a couple people on the leading edge of patient engagement:

• Abbe Steel, CEO of HealthiVibe, which is focused on bringing greater patient input into the earliest stages of trial design through focus groups and patient surveys
• Casey Quinlan, co-founder of Patients for Clinical Research, which aims to be a force in patient education and engagement for clinical trials

In addition to their thoughts, eyeforpharma is keenly interested in hearing from more people. They've even posted a survey – from Ulrich:

To get a better idea of what other folks think of the idea, I am sending out a little ad hoc survey. Only 4 questions (so people hopefully do it). Added benefit: There is a massive 50% one-time discount for completed surveys until Friday connected to it as an incentive).

So, here are two things for you to do:

1. Complete the survey and share your thoughts
2. Come to the conference and tell us all exactly what you think

Look forward to seeing you there.

[Conflict of Interest Disclosure: I am attending the Patient Centered Clinical Trials conference. Having everyone saying the same thing at such conferences conflicts with my ability to find them interesting.]

But while we can all agree that "patient engagement is good" in a highly general sense, we don't have much consensus on what the implications of that idea might be. There is precious little hard evidence about how to either attract engaged patients, or how we might effectively turn "regular patients" into "engaged patients".

Maybe those pesky sites are good for something after all. 

It's been six years since Pfizer boldly announced the launch of its "clinical trial in a box". The REMOTE trial was designed to be entirely online, and involved no research sites: study information and consent was delivered via the web, and medications and diaries were shipped directly to patients' homes.

Despite the initial fanfare, within a month REMOTE's registration on ClinicalTrials.gov was quietly reduced from 600 to 283. The smaller trial ended not with a bang but a whimper, having randomized only 18 patients in over a year of recruiting.

Still, the allure of direct to patient clinical trials remains strong, due to a confluence of two factors. First, a frenzy of interest in running "patient centric clinical trials". Sponsors are scrambling to show they are doing something – anything – to show they have shifted to a patient-centered mindset. We cannot seem to agree what this means (as a great illustration of this, a recent article in Forbes on "How Patients Are Changing Clinical Trials" contained no specific examples of actual trials that had been changed by patients), but running a trial that directly engages patients wherever they are seems like it could work.

The less-openly-discussed other factor leading to interest in these DIY trials is sponsors' continuing willingness to heap almost all of the blame for slow-moving studies onto their research sites. If it’s all the sites’ fault – the reasoning goes – then cutting them out of the process should result in trials that are both faster and cheaper. (There are reasons to be skeptical about this, as I have discussed in the past, but the desire to drop all those pesky sites is palpable.)

However, while a few proof-of-concept studies have been done, there really doesn't seem to have been another trial to attempt a full-blown direct-to-patient clinical trial. Other pilots have been more successful, but had fairly lightweight protocols. For all its problems, REMOTE was a seriously ambitious project that attempted to package a full-blown interventional clinical trial, not an observational study.

In this context, it's great to see published results of the TAPIR Trial in vasculitis, which as far as I can tell is the first real attempt to run a DIY trial of a similar magnitude to REMOTE.

TAPIR was actually two parallel trials, identical in every respect except for their sites: one trial used a traditional group of 8 sites, while the other was virtual and recruited patients from anywhere in the country. So this was a real-time, head-to-head assessment of site performance.

And the results after a full two years of active enrollment?

• Traditional sites: 49 enrolled
• Patient centric: 10 enrolled

Even though we’re six years later, and online/mobile communications are even more ubiquitous, we still see the exact same struggle to enroll patients.

Maybe it’s time to stop blaming the sites? To be fair, they didn’t exactly set the world on fire – and I’m guessing the total cost of activating the 8 sites significantly exceeded the costs of setting up the virtual recruitment and patient logistics. But still, the site-less, “patient centric” approach once again came up astonishingly short.
Krischer J, Cronholm PF, Burroughs C, McAlear CA, Borchin R, Easley E, Davis T, Kullman J, Carette S, Khalidi N, Koening C, Langford CA, Monach P, Moreland L, Pagnoux C, Specks U, Sreih AG, Ytterberg S, Merkel PA, & Vasculitis Clinical Research Consortium. (2017). Experience With Direct-to-Patient Recruitment for Enrollment Into a Clinical Trial in a Rare Disease: A Web-Based Study. Journal of medical Internet research, 19 (2) PMID: 28246067

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Nearly every day since she was a child, Alex Leow, a psychiatrist and computer scientist at the University of Illinois Chicago, has played the piano. Some days she plays well, and other days her tempo lags and her fingers hit the wrong keys. Over the years, she noticed a pattern: How well she plays depends on her mood. A bad mood or lack of sleep almost always leads to sluggish, mistake-prone music.

In 2015, Leow realized that a similar pattern might be true for typing. She wondered if she could help people with psychiatric conditions track their moods by collecting data about their typing style from their phones. She decided to turn her idea into an app.

After conducting a pilot study, in 2018 Leow launched BiAffect, a research app that aims to understand mood-related symptoms of bipolar disorder through keyboard dynamics and sensor data from users’ smartphones. Now in use by more than 2,700 people who have volunteered their data to the project, the app tracks typing speed and accuracy by swapping the phone’s onscreen keyboard with its own nearly identical one.

The software then generates feedback for users, such as a graph displaying hourly keyboard activity. Researchers get access to the donated data from users’ phones, which they use to develop and test machine learning algorithms that interpret data for clinical use. One of the things Leow’s team has observed: When people are manic—a state of being overly excited that accompanies bipolar disorder—they type “ferociously fast,” says Leow.

Compared to a healthy user [top], a person experiencing symptoms of bipolar disorder [middle] or depression [bottom] may use their phone more than usual and late at night. BiAffect measures phone usage and orientation to help track those symptoms. BiAffect

BiAffect is one of the few mental-health apps that take a passive approach to collecting data from a phone to make inferences about users’ mental states. (Leow suspects that fewer than a dozen are currently available to consumers.) These apps run in the background on smartphones, collecting different sets of data not only on typing but also on the user’s movements, screen time, call and text frequency, and GPS location to monitor social activity and sleep patterns. If an app detects an abrupt change in behavior, indicating a potentially hazardous shift in mental state, it could be set up to alert the user, a caretaker, or a physician.

Such apps can’t legally claim to treat or diagnose disease, at least in the United States. Nevertheless, many researchers and people with mental illness have been using them as tools to track signs of depression, schizophrenia, anxiety, and bipolar disorder. “There’s tremendous, immediate clinical value in helping people feel better today by integrating these signals into mental-health care,” says John Torous, director of digital psychiatry at Beth Israel Deaconess Medical Center, in Boston. Globally, one in 8 people live with a mental illness, including 40 million with bipolar disorder.

These apps differ from most of the more than 10,000 mental-health and mood apps available, which typically ask users to actively log how they’re feeling, help users connect to providers, or encourage mindfulness. The popular apps Daylio and Moodnotes, for example, require journaling or rating symptoms. This approach requires more of the user’s time and may make these apps less appealing for long-term use. A 2019 study found that among 22 mood-tracking apps, the median user-retention rate was just 6.1 percent at 30 days of use.

App developers are trying to avoid the pitfalls of previous smartphone-psychiatry startups, some of which oversold their capabilities before validating their technologies.

But despite years of research on passive mental-health apps, their success is far from guaranteed. App developers are trying to avoid the pitfalls of previous smartphone psychiatry startups, some of which oversold their capabilities before validating their technologies. For example, Mindstrong was an early startup with an app that tracked taps, swipes, and keystrokes to identify digital biomarkers of cognitive function. The company raised US $160 million in funding from investors, including $100 million in 2020 alone, and went bankrupt in February 2023.

Mindstrong may have folded because the company was operating on a different timeline from the research, according to an analysis by the health-care news website Stat. The slow, methodical pace of science did not match the startup’s need to return profits to its investors quickly, the report found. Mindstrong also struggled to figure out the marketplace and find enough customers willing to pay for the service. “We were first out of the blocks trying to figure this out,” says Thomas Insel, a psychiatrist who cofounded Mindstrong.

Now that the field has completed a “hype cycle,” Torous says, app developers are focused on conducting the research needed to prove their apps can actually help people. “We’re beginning to put the burden of proof more on those developers and startups, as well as academic teams,” he says. Passive mental-health apps need to prove they can reliably parse the data they’re collecting, while also addressing serious privacy concerns.

Passive sensing catches mood swings early

A crucial component of managing psychiatric illness is tracking changes in mental states that can lead to more severe episodes of the disease. Bipolar disorder, for example, causes intense swings in mood, from extreme highs during periods of mania to extreme lows during periods of depression. Between 30 and 50 percent of people with bipolar disorder will attempt suicide at least once in their lives. Catching early signs of a mood swing can enable people to take countermeasures or seek help before things get bad.

But detecting those changes early is hard, especially for people with mental illness. Observations by other people, such as family members, can be subjective, and doctor and counselor sessions are too infrequent.

That’s where apps come in. Algorithms can be trained to spot subtle deviations from a person’s normal routine that might indicate a change in mood—an objective measure based on data, like a diabetic tracking blood sugar. “The ability to think objectively about my own thinking is really key,” says retired U.S. major general Gregg Martin, who has bipolar disorder and is an advisor for BiAffect.

The data from passive sensing apps could also be useful to doctors who want to see objective data on their patients in between office visits, or for people transitioning from inpatient to outpatient settings. These apps are “providing a service that doesn’t exist,” says Colin Depp, a clinical psychologist and professor at the University of California, San Diego. Providers can’t observe their patients around the clock, he says, but smartphone data can help close the gap.

Depp and his team have developed an app that uses GPS data and microphone-based sensing to determine the frequency of conversations and make inferences about a person’s social interactions and isolation. The app also tracks “location entropy,” a metric of how much a user moves around outside of routine locations. When someone is depressed and mostly stays home, location entropy decreases.

Depp’s team initially developed the app, called CBT2go, as a way to test the effectiveness of cognitive behavioral therapy in between therapy sessions. The app can now intervene in real time with people experiencing depressive or psychotic symptoms. This feature helps people identify when they feel lonely or agitated so they can apply coping skills they’ve learned in therapy. “When people walk out of the therapist’s office or log off, then they kind of forget all that,” Depp says.

Another passive mental-health-app developer, Ellipsis Health in San Francisco, uses software that takes voice samples collected during telehealth calls to gauge a person’s level of depression, anxiety, and stress symptoms. For each set of symptoms, deep-learning models analyze the person’s words, rhythms, and inflections to generate a score. The scores indicate the severity of the person’s mental distress, and are based on the same scales used in standard clinical evaluations, says Michael Aratow, cofounder and chief medical officer at Ellipsis.

Aratow says the software works for people of all demographics, without needing to first capture baseline measures of an individual’s voice and speech patterns. “We’ve trained the models in the most difficult use cases,” he says. The company offers its platform, including an app for collecting the voice data, through health-care providers, health systems, and employers; it’s not directly available to consumers.

In the case of BiAffect, the app can be downloaded for free by the public. Leow and her team are using the app as a research tool in clinical trials sponsored by the U.S. National Institutes of Health. These studies aim to validate whether the app can reliably monitor mood disorders, and determine whether it could also track suicide risk in menstruating women and cognition in people with multiple sclerosis.

BiAffect’s software tracks behaviors like hitting the backspace key frequently, which suggests more errors, and an increase in typing “@” symbols and hashtags, which suggest more social media use. The app combines this typing data with information from the phone’s accelerometer to determine how the user is oriented and moving—for example, whether the user is likely lying down in bed—which yields more clues about mood.

Ellipsis Health analyzes audio captured during telehealth visits to assign scores for depression, anxiety, and stress.Ellipsis Health

The makers of BiAffect and Ellipsis Health don’t claim their apps can treat or diagnose disease. If app developers want to make those claims and sell their product in the United States, they would first have to get regulatory approval from the U.S. Food and Drug Administration. Getting that approval requires rigorous and large-scale clinical trials that most app makers don’t have the resources to conduct.

Digital-health software depends on quality clinical data

The sensing techniques upon which passive apps rely—measuring typing dynamics, movement, voice acoustics, and the like—are well established. But the algorithms used to analyze the data collected by the sensors are still being honed and validated. That process will require considerably more high-quality research among real patient populations.

Greg Mably

For example, clinical studies that include control or placebo groups are crucial and have been lacking in the past. Without control groups, companies can say their technology is effective “compared to nothing,” says Torous at Beth Israel.

Torous and his team aim to build software that is backed by this kind of quality evidence. With participants’ consent, their app, called mindLAMP, passively collects data from their screen time and their phone’s GPS and accelerometer for research use. It’s also customizable for different diseases, including schizophrenia and bipolar disorder. “It’s a great starting point. But to bring it into the medical context, there’s a lot of important steps that we’re now in the middle of,” says Torous. Those steps include conducting clinical trials with control groups and testing the technology in different patient populations, he says.

How the data is collected can make a big difference in the quality of the research. For example, the rate of sampling—how often a data point is collected—matters and must be calibrated for the behavior being studied. What’s more, data pulled from real-world environments tends to be “dirty,” with inaccuracies collected by faulty sensors or inconsistencies in how phone sensors initially process data. It takes more work to make sense of this data, says Casey Bennett, an assistant professor and chair of health informatics at DePaul University, in Chicago, who uses BiAffect data in his research.

One approach to addressing errors is to integrate multiple sources of data to fill in the gaps—like combining accelerometer and typing data. In another approach, the BiAffect team is working to correlate real-world information with cleaner lab data collected in a controlled environment where researchers can more easily tell when errors are introduced.

Who participates in the studies matters too. If participants are limited to a particular geographic area or demographic, it’s unclear whether the results can be applied to the broader population. For example, a night-shift worker will have different activity patterns from those with nine-to-five jobs, and a city dweller may have a different lifestyle from residents of rural areas.

After the research is done, app developers must figure out a way to integrate their products into real-world medical contexts. One looming question is when and how to intervene when a change in mood is detected. These apps should always be used in concert with a professional and not as a replacement for one, says Torous. Otherwise, the app’s assessments could be dangerous and distressing to users, he says.

When mood tracking feels like surveillance

No matter how well these passive mood-tracking apps work, gaining trust from potential users may be the biggest stumbling block. Mood tracking could easily feel like surveillance. That’s particularly true for people with bipolar or psychotic disorders, where paranoia is part of the illness.

Keris Myrick, a mental-health advocate, says she finds passive mental-health apps “both cool and creepy.” Myrick, who is vice president of partnerships and innovation at the mental-health-advocacy organization Inseparable, has used a range of apps to support her mental health as a person with schizophrenia. But when she tested one passive sensing app, she opted to use a dummy phone. “I didn’t feel safe with an app company having access to all of that information on my personal phone,” Myrick says. While she was curious to see if her subjective experience matched the app’s objective measurements, the creepiness factor prevented her from using the app enough to find out.

Keris Myrick, a mental-health advocate, says she finds passive mental-health apps “both cool and creepy.”

Beyond users’ perception, maintaining true digital privacy is crucial. “Digital footprints are pretty sticky these days,” says Katie Shilton, an associate professor at the University of Maryland focused on social-data science. It’s important to be transparent about who has access to personal information and what they can do with it, she says.

“Once a diagnosis is established, once you are labeled as something, that can affect algorithms in other places in your life,” Shilton says. She cites the misuse of personal data in the Cambridge Analytica scandal, in which the consulting firm collected information from Facebook to target political advertising. Without strong privacy policies, companies producing mental-health apps could similarly sell user data—and they may be particularly motivated to do so if an app is free to use.

Conversations about regulating mental-health apps have been ongoing for over a decade, but a Wild West–style lack of regulation persists in the United States, says Bennett of DePaul University. For example, there aren’t yet protections in place to keep insurance companies or employers from penalizing users based on data collected. “If there aren’t legal protections, somebody is going to take this technology and use it for nefarious purposes,” he says.

Some of these concerns may be mediated by confining all the analysis to a user’s phone, rather than collecting data in a central repository. But decisions about privacy policies and data structures are still up to individual app developers.

Leow and the BiAffect team are currently working on a new internal version of their app that incorporates natural-language processing and generative AI extensions to analyze users’ speech. The team is considering commercializing this new version in the future, but only following extensive work with industry partners to ensure strict privacy safeguards are in place. “I really see this as something that people could eventually use,” Leow says. But she acknowledges that researchers’ goals don’t always align with the desires of the people who might use these tools. “It is so important to think about what the users actually want.”

This article appears in the July 2024 print issue as “The Shrink in Your Pocket.”

Acadia Pharmaceuticals did not disclose the buyer of the priority review voucher. The biotech received the voucher last year alongside the regulatory decision that made its drug Daybue the first FDA-approved treatment for the rare disease Rett syndrome.

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