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NOW AVAILABLE: 2024–25 Economic Report on Pharmaceutical Wholesalers and Specialty Distributors

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.
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.
Read more »
       




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Informa Connect’s Trade and Channel Strategies

Informa Connect’s Trade and Channel Strategies
December 10-12, 2024 at the W Hotel in Philadelphia, PA
Drug Channels readers save 10% with code 24DC10*

Pharmacy and distribution models are growing increasingly complex. Stop running in circles—It’s time to unlock proven strategies to propel market access.

What is the secret to success? Trade and Channel Strategies is bringing together industry experts to deliver specific strategies and talk best practices in tackling the latest industry challenges.

As the landscape rapidly evolves, there are only two choices—Adapt or risk falling behind. With policy changes and market fluctuations, specifically surrounding the DSCSA and IRA, the loss of exclusivity wave, adoption of low-WAC products affecting GTN and the rise of innovations within the pharmacy sector, there has never been a more important time for industry to unite. A program driven by market dynamics and led by champions of channel strategy, join your peers now to master the complexities of pharmacy and distribution models to accelerate market access—It's all happening December 10-12.

Why do trade and channel professionals choose this pivotal event?

The challenge of staying viable among shifting market dynamics while meeting business objectives is heavy. Professionals are left with many questions, including:
  • How will the new administration affect the distribution channel?
  • Is my organization haemorrhaging money to stay afloat with the shift to alternative distribution and pharmacy models?
  • Does the DSCSA deadline change affect my organization? Am I still prepared?
Join the experts for three dedicated days of collaborative discussions that will give you the answers to these questions and so many more. Leaders in the landscape are uniting and will dive into the top trends for innovative distribution, integrated pharmacy models and talk the truth about the future of trade.

WHAT CAN YOU EXPECT?

Vital insights from industry’s leading pharmacy and distribution experts, including:
  • Bill Roth, Senior Vice President of Consulting, Blue Fin Group, An IntegriChain Company
  • Patrick Lupo Group Vice President, Pharmacy Trade and Specialty, Walgreens
  • Amanda Salindong, Associate Director, Channel & Distribution, Alnylam Pharmaceuticals
  • Chris Rocco, Senior Director, Market Access Data, Reporting & Analytics, GSK
  • Eliane Maalouf, Director Trade and Fulfillment, Mass General Brigham Specialty Pharmacy
  • Stephanie Wirkes, Head of Distribution and Strategy Execution, Bayer
  • John Harlow, Chief Commercial Officer, Melinta Therapeutics
  • Aria Cohen, Vice President, Head of Market Access, Alkeus Pharmaceuticals, Inc.
  • Elizabeth Cherry, Program Director for Trade Relations, Vanderbilt Specialty Pharmacy
  • Danielle Bryan, PharmD, CSP, Program Director, Specialty Pharmacy Trade Relations, Vanderbilt University Medical Center
  • Thomas Scalone, Director, Trade Strategy and Operations, Bristol Myers Squibb
  • Dina Lynch, VP, Market Access and Reimbursement, Renibus Therapeutics
  • And more!
Tackle the hottest topics facing industry right now, including:
  • Keynote Address: Access and Channel 2024 In-Review and Preview of 2025
  • Pharmacy Evolved—Aligning Commercialization to the Changing Pharmacy Channel
  • Advanced Trade Leaders Executive Session
  • Navigate and Operationalize the IRA
  • Focused Multi-Track Offerings:
    • Supply Chain, Distribution and Logistics
    • Pharmacy Models and Reimbursement Strategies
    • Data, Innovation and Analytics
    • Health Systems and Pharma Partnering Symposium
  • Balancing the GTN Bubble with Market Access Priorities
  • What’s Happening in Retail—Brick and Morter, Home Delivery and Cash Pay Pharmacies
  • Navigating Post Deadline Challenges—DSCSA Compliance and Serialization Updates
  • Four Roundtable Breakout Discussions:
    • What Good Looks Like in a 3PL/Manufacturer Partnership
    • Optimizing Healthcare Partnerships
    • Women in Trade
    • GLP-1s and New Product Archetypes
  • Actions Needed to Mitigate and Prevent Drug Shortages
  • Case Study: Master Your Organization Chart—Ensuring Higher Cross Functional Interactions
  • Three Interactive Workshops:
    • Trade 101
    • Advanced Trade Leaders Executive Session
    • Health Systems Fundamentals
  • And more!
Exclusive Offer—Download the agenda and register today—Be sure to use your exclusive promo 24DC10 to save 10% off* of your registration.

See you there!

* Cannot be combined with other offers, promotions or applied to an existing registration. Other restrictions may apply.


The content of Sponsored Posts does not necessarily reflect the views of HMP Omnimedia, LLC, Drug Channels Institute, its parent company, or any of its employees. To find out how you can promote an event on Drug Channels, please contact Paula Fein (paula@DrugChannels.net).
       




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Transparency Shocker: Biosimilars Are Getting Cheaper—But Hospitals and Insurers Can Make Them Expensive

Here on Drug Channels, we have long highlighted the boom in provider-administered biosimilars. In contrast to the pharmacy market, adoption of these biosimilars is growing, prices are dropping, and formulary barriers continue to fall.

Novel transparency information reveals that this good news doesn’t always translate into savings. Below, we rely on a unique data set from Turquoise Health to examine how much four national commercial health plans—Aetna, Anthem, Cigna, and UnitedHealthcare—paid hospitals for Avastin and its two most significant biosimilar competitors.

As we demonstrate, health plans pay hospitals far above acquisition costs for biosimilars. What’s more, plans can pay hospitals more for a biosimilar than for the higher-cost reference product. The U.S. drug channel system is warping hospitals’ incentives to adopt biosimilars, while simultaneously raising costs for commercial plans.

The namesake of my alma mater once said: “Sunlight is said to be the best of disinfectants.” What would happen if we disinfected the entire channel?
Read more »
       




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New On-Demand Training Platform




I am pleased to announce the availability of on-demand training about FDA's regulation of advertising and promotion. So, you are now able to learn about the wonderful world of FDA ad-promo from the comfort of your home, office, or campsite. 

At PhillyCooke.Thinkific.com, you can see the courses that are currently available and sign up. In the video above, there's a special discount code to celebrate the launch of this new platform.

If you are interested in providing access to the training for your full team, then please email me at DCooke@PhillyCooke.com or fill out the contact form on the website. I can provide all of the information about the corporate licensing.
 
Every course comes with access for a full year. You can view, and review, the content as often as you like. In addition, every module on the platform is reviewed in its entirety at least twice per year. If something changes, new modules will replace the old ones, and students will be notified of the update. Those new modules will be available at no additional cost! That way you can rest assured that the information you are learning is always current with the latest developments in the world of ad-promo.




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FDA Post-Election: Continuity and Progress Likely to Mark 2013

Looking back over the last 40 years at FDA (as I have), there are three characteristics that create a more progressive environment at the agency: continuity of leadership, presidential support, and increased funding. For FDA in 2013 (as the saying goes): 2 out of 3 ain’t bad. In particular, medical innovation seems poised to flourish in an FDA environment where there is continuity of policy and leadership, instead of a new team learning the ropes. I explore this and other themes in the latest issue of Pharmaphorum.com. You can read my thoughts at: http://www.pharmaphorum.com/2013/01/29/fda-post-election-continuity-and-progress-likely-to-mark-2013/.




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FTC Finalizes “Click-to-Cancel” Rule to Make It Easier for Consumers to End Recurring Subscriptions and Memberships

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Former CHC Board Chairs Sharon Callahan and Nick Colucci Named as 2025 MAHF Inductees

Two former board chairs of the Coalition for Healthcare Communication (CHC) were named as the Medical Advertising Hall of Fame (MAHF) 2025 inductees – Sharon Callahan, former Chief Client Officer at Omnicom Health Group (OHG), and Nick Colucci, former Chairman and CEO of Publicis Health/COO of Publicis Groupe North America. The inductees will be honored […]




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Massachusetts High Court Rules Online Tracking Doesn’t Violate State Wiretap Law

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  • Courts/First Amendment

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Don’t Confuse the Art and Science of Medicine: PCI vs CABG for Left Main Disease

It is often said that medicine is both an art and a science. In an imperfect world this is both inevitable and desirable. But it is extremely important that the two should not be confused with each other. In particular, because the “science” side of the equation has achieved overwhelming prestige and authority, it is...

Click here to continue reading...




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EMA recommends approval of aflibercept biosimilars Afqlir and Opuviz

<p>On 19&nbsp;September 2024, the European Medicines Agency’s (EMA) Committee for Medicinal Products for Human Use (CHMP)&nbsp;adopted a positive opinion,&nbsp;recommending the granting of marketing authorization&nbsp;for&nbsp;two aflibercept biosimilars:&nbsp;&nbsp;Sandoz’s Afqlir and Samsung Bioepis’s Opuviz.&nbsp;These products are biosimilars of the reference product Eylea, developed by Regeneron and Bayer.</p>




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FDA approves biosimilars: ustekinumab Otulfi and eculizumab Epysqli

<p>The US Food and Drug Administration (FDA) granted approval for two&nbsp;biosimilars, Formycon’s FYB202/Otulfi (ustekinumab-aauz) and Samsung Bioepis’ Soliris biosimilar, Epysqli (eculizumab-aagh), on 27 September and 22 July 2024, respectively. FYB202/Otulfi, a biosimilar referencing&nbsp;Johnson &amp; Johnson’s Stelara, while Epysqli is a biosimilar referencing Alexion’s Soliris.</p>




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NPRA Malaysia trials new timelines for variation applications

<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>




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EC approval for three ustekinumab biosimilar: Eksunbi, Fymskina, Otulfi

<p>The European Commission (EC) granted marketing authorization for<b>&nbsp;</b>three ustekinumab biosimilars<b>:&nbsp;</b>Samsung Bioepis’ Eksunbi on 12 September 2024; Formycon’s Fymskina, and Fresenius Kabi’s&nbsp;Otulfi on 25 September 2024.</p>




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Transforming healthcare: CinnaGen’s leadership in follow-on biologicals/ biosimilars development and market expansion

<p> <b>Abstract</b><br />CinnaGen, the largest biopharmaceutical company in the MENA region, is a leader in developing follow-on biologicals/biosimilars. Dr&nbsp;Haleh Hamedifar, Chairperson of CinnaGen, spoke to GaBI<i>&nbsp;</i>(Generics and Biosimilars Initiative) about the company’s strategic focus, which includes expanding its product portfolio, entering highly regulated global markets, and advancing affordable treatments for conditions such as multiple sclerosis and&nbsp;immunological diseases—transforming healthcare in underserved regions.</p><p><b>Keywords</b>: Biosimilars, clinical development, commercialization, MENA</p>




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RPS and pharmacy students' association call for rethink over overseas exam decision

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.




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Government 'miscommunicated' PPE stock levels to pharmacies during first COVID-19 wave, MPs told

The government implied wholesalers had more personal protective equipment in stock than was the case during the first wave of the COVID-19 pandemic, the Healthcare Distribution Association has said.




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Pharmacy negotiators in talks over plans to distribute COVID-19 treatments in primary care

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




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Prime minister vows to reimburse community pharmacy's COVID-19 costs 'as soon as possible'

Community pharmacies should be reimbursed for their additional costs during the COVID-19 pandemic “as soon as possible”, the prime minister has told The Pharmaceutical Journal.




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Semaglutide effective for weight loss in non-diabetic adults, research suggests

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.




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MHRA to consult on making two progestogen-only contraceptives available without a prescription

Consultations on the reclassification of two progestogen-only contraceptive pills from prescription-only to pharmacy medicines have been launched.




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Pharmacies estimated to receive one referral per month through hospital-to-pharmacy referral service

Community pharmacies will receive an estimated 12 referrals from the Discharge Medicines Service per year.




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Health boards say around half of pharmacies have expressed interest in providing COVID-19 vaccines

Around half of Wales’ community pharmacies have expressed interest to health boards in providing COVID-19 vaccinations as part of the national programme.




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Chiesi launches postal asthma inhaler recycling scheme

The UK’s first postal inhaler recycling scheme has been launched by pharmaceutical company Chiesi to support a more sustainable way of living for people with respiratory illnesses.




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Pharmacy negotiators discuss patient registration with community pharmacies

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




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Half of asthma patients in the UK overusing SABAs, study finds

More than half of patients with asthma in the UK are “potentially overusing” short-acting β2-agonists, according to research.




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RPS pays tribute to pharmacy law and ethics pioneer Joy Wingfield

The Royal Pharmaceutical Society has expressed its sadness at the death of Joy Wingfield, honorary professor of Pharmacy Law and Ethics at the University of Nottingham.




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Pharmacology: The Anchor for Nearly Every Diligence

By Haojing Rong and Aimee Raleigh, as part of the From The Trenches feature of LifeSciVC This blog post is the second in a series on key diligence concepts and questions. If you missed the intro blog post yesterday, click

The post Pharmacology: The Anchor for Nearly Every Diligence appeared first on LifeSciVC.




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Mariana Oncology’s Radiopharm Platform Acquired By Novartis

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.




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Boiling It Down: Conveying Complexity For Decision-makers

By Ankit Mahadevia, former CEO of Spero Therapeutics, as part of the From The Trenches feature of LifeSciVC Drug development is complex. So is running a business. Sometimes, the work of doing both can make your head spin. In my

The post Boiling It Down: Conveying Complexity For Decision-makers appeared first on LifeSciVC.




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A Biotech Midsummer’s Madness

By Arthur Tzianabos, CEO of Lifordi Immunotherapeutics, as part of the From The Trenches feature of LifeSciVC Greetings from Lake Winnipesaukee in NH where I am at this time every year. It’s midsummer and vacation time for me and the

The post A Biotech Midsummer’s Madness appeared first on LifeSciVC.




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Keeping It Simple: What Really Matters For Emerging Enterprises  

By Ankit Mahadevia, chairman of Spero Therapeutics, as part of the From The Trenches feature of LifeSciVC A common theme in startup literature is that by cutting a range of unnecessary tasks, a step-change in results will follow.  I’ve found

The post Keeping It Simple: What Really Matters For Emerging Enterprises   appeared first on LifeSciVC.




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Brazen Scofflaws? Are Pharma Companies Really Completely Ignoring FDAAA?

Results reporting requirements are pretty clear. Maybe critics should re-check their methods?

Ben Goldacre has rather famously described the clinical trial reporting requirements in the Food and Drug Administration Amendments Act of 2007 as a “fake fix” that was being thoroughly “ignored” by the pharmaceutical industry.

Pharma: breaking the law in broad daylight?
He makes this sweeping, unconditional proclamation about the industry and its regulators on the basis of  a single study in the BMJ, blithely ignoring the fact that a) the authors of the study admitted that they could not adequately determine the number of studies that were meeting FDAAA requirements and b) a subsequent FDA review that identified only 15 trials potentially out of compliance, out of a pool of thousands.


Despite the fact that the FDA, which has access to more data, says that only a tiny fraction of studies are potentially noncompliant, Goldacre's frequently repeated claims that the law is being ignored seems to have caught on in the general run of journalistic and academic discussions about FDAAA.

And now there appears to be additional support for the idea that a large percentage of studies are noncompliant with FDAAA results reporting requirements, in the form of a new study in the Journal of Clinical Oncology: "Public Availability of Results of Trials Assessing Cancer Drugs in the United States" by Thi-Anh-Hoa Nguyen, et al.. In it, the authors report even lower levels of FDAAA compliance – a mere 20% of randomized clinical trials met requirements of posting results on clinicaltrials.gov within one year.

Unsurprisingly, the JCO results were immediately picked up and circulated uncritically by the usual suspects.

I have to admit not knowing much about pure academic and cooperative group trial operations, but I do know a lot about industry-run trials – simply put, I find the data as presented in the JCO study impossible to believe. Everyone I work with in pharma trials is painfully aware of the regulatory environment they work in. FDAAA compliance is a given, a no-brainer: large internal legal and compliance teams are everywhere, ensuring that the letter of the law is followed in clinical trial conduct. If anything, pharma sponsors are twitchily over-compliant with these kinds of regulations (for example, most still adhere to 100% verification of source documentation – sending monitors to physically examine every single record of every single enrolled patient - even after the FDA explicitly told them they didn't have to).

I realize that’s anecdotal evidence, but when such behavior is so pervasive, it’s difficult to buy into data that says it’s not happening at all. The idea that all pharmaceutical companies are ignoring a highly visible law that’s been on the books for 6 years is extraordinary. Are they really so brazenly breaking the rules? And is FDA abetting them by disseminating incorrect information?

Those are extraordinary claims, and would seem to require extraordinary evidence. The BMJ study had clear limitations that make its implications entirely unclear. Is the JCO article any better?

Some Issues


In fact, there appear to be at least two major issues that may have seriously compromised the JCO findings:

1. Studies that were certified as being eligible for delayed reporting requirements, but do not have their certification date listed.

The study authors make what I believe to be a completely unwarranted assumption:

In trials for approval of new drugs or approval for a new indication, a certification [permitting delayed results reporting] should be posted within 1 year and should be publicly available.

It’s unclear to me why the authors think the certifications “should be” publicly available. In re-reading FDAAA section 801, I don’t see any reference to that being a requirement. I suppose I could have missed it, but the authors provide a citation to a page that clearly does not list any such requirement.

But their methodology assumes that all trials that have a certification will have it posted:

If no results were posted at ClinicalTrials.gov, we determined whether the responsible party submitted a certification. In this case, we recorded the date of submission of the certification to ClinicalTrials.gov.

If a sponsor gets approval from FDA to delay reporting (as is routine for all drugs that are either not approved for any indication, or being studied for a new indication – i.e., the overwhelming majority of pharma drug trials), but doesn't post that approval on the registry, the JCO authors deem that trial “noncompliant”. This is not warranted: the company may have simply chosen not to post the certification despite being entirely FDAAA compliant.

2. Studies that were previously certified for delayed reporting and subsequently reported results

It is hard to tell how the authors treated this rather-substantial category of trials. If a trial was certified for delayed results reporting, but then subsequently published results, the certification date becomes difficult to find. Indeed, it appears in the case where there were results, the authors simply looked at the time from study completion to results posting. In effect, this would re-classify almost every single one of these trials from compliant to non-compliant. Consider this example trial:


  • Phase 3 trial completes January 2010
  • Certification of delayed results obtained December 2010 (compliant)
  • FDA approval June 2013
  • Results posted July 2013 (compliant)


In looking at the JCO paper's methods section, it really appears that this trial would be classified as reporting results 3.5 years after completion, and therefore be considered noncompliant with FDAAA. In fact, this trial is entirely kosher, and would be extremely typical for many phase 2 and 3 trials in industry.

Time for Some Data Transparency


The above two concerns may, in fact, be non-issues. They certainly appear to be implied in the JCO paper, but the wording isn't terribly detailed and could easily be giving me the wrong impression.

However, if either or both of these issues are real, they may affect the vast majority of "noncompliant" trials in this study. Given the fact that most clinical trials are either looking at new drugs, or looking at new indications for new drugs, these two issues may entirely explain the gap between the JCO study and the unequivocal FDA statements that contradict it.

I hope that, given the importance of transparency in research, the authors will be willing to post their data set publicly so that others can review their assumptions and independently verify their conclusions. It would be more than a bit ironic otherwise.

[Image credit: Shamless lawlessness via Flikr user willytronics.]


Thi-Anh-Hoa Nguyen, Agnes Dechartres, Soraya Belgherbi, and Philippe Ravaud (2013). Public Availability of Results of Trials Assessing Cancer Drugs in the United States JOURNAL OF CLINICAL ONCOLOGY DOI: 10.1200/JCO.2012.46.9577




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Questionable Enrollment Math at the UK's NIHR

There has been considerable noise coming out of the UK lately about successes in clinical trial enrollment.

First, a couple months ago came the rather dramatic announcement that clinical trial participation in the UK had "tripled over the last 6 years". That announcement, by the chief executive of the

Sweet creature of bombast: is Sir John
writing press releases for the NIHR?
National Institute of Health Research's Clinical Research Network, was quickly and uncritically picked up by the media.

That immediately caught my attention. In large, global trials, most pharmaceutical companies I've worked with can do a reasonable job of predicting accrual levels in a given country. I like to think that if participation rates in any given country had jumped that heavily, I’d have heard something.

(To give an example: looking at a quite-typical study I worked on a few years ago: UK sites were overall slightly below the global average. The highest-enrolling countries were about 2.5 times as fast. So, a 3-fold increase in accruals would have catapulted the UK from below average to the fastest-enrolling country in the world.)

Further inquiry, however, failed to turn up any evidence that the reported tripling actually corresponded to more human beings enrolled in clinical trials. Instead, there is some reason to believe that all we witnessed was increased reporting of trial participation numbers.

Now we have a new source of wonder, and a new giant multiplier coming out of the UK. As the Director of the NIHR's Mental Health Research Network, Til Wykes, put it in her blog coverage of her own paper:
Our research on the largest database of UK mental health studies shows that involving just one or two patients in the study team means studies are 4 times more likely to recruit successfully.
Again, amazing! And not just a tripling – a quadrupling!

Understand: I spend a lot of my time trying to convince study teams to take a more patient-focused approach to clinical trial design and execution. I desperately want to believe this study, and I would love having hard evidence to bring to my clients.

At first glance, the data set seems robust. From the King's College press release:
Published in the British Journal of Psychiatry, the researchers analysed 374 studies registered with the Mental Health Research Network (MHRN).
Studies which included collaboration with service users in designing or running the trial were 1.63 times more likely to recruit to target than studies which only consulted service users.  Studies which involved more partnerships - a higher level of Patient and Public Involvement (PPI) - were 4.12 times more likely to recruit to target.
But here the first crack appears. It's clear from the paper that the analysis of recruitment success was not based on 374 studies, but rather a much smaller subset of 124 studies. That's not mentioned in either of the above-linked articles.

And at this point, we have to stop, set aside our enthusiasm, and read the full paper. And at this point, critical doubts begin to spring up, pretty much everywhere.

First and foremost: I don’t know any nice way to say this, but the "4 times more likely" line is, quite clearly, a fiction. What is reported in the paper is a 4.12 odds ratio between "low involvement" studies and "high involvement" studies (more on those terms in just a bit).  Odds ratios are often used in reporting differences between groups, but they are unequivocally not the same as "times more likely than".

This is not a technical statistical quibble. The authors unfortunately don’t provide the actual success rates for different kinds of studies, but here is a quick example that, given other data they present, is probably reasonably close:

  • A Studies: 16 successful out of 20 
    • Probability of success: 80% 
    • Odds of success: 4 to 1
  • B Studies: 40 successful out of 80
    • Probability of success: 50%
    • Odds of success: 1 to 1

From the above, it’s reasonable to conclude that A studies are 60% more likely to be successful than B studies (the A studies are 1.6 times as likely to succeed). However, the odds ratio is 4.0, similar to the difference in the paper. It makes no sense to say that A studies are 4 times more likely to succeed than B studies.

This is elementary stuff. I’m confident that everyone involved in the conduct and analysis of the MHRN paper knows this already. So why would Dr Wykes write this? I don’t know; it's baffling. Maybe someone with more knowledge of the politics of British medicine can enlighten me.

If a pharmaceutical company had promoted a drug with this math, the warning letters and fines would be flying in the door fast. And rightly so. But if a government leader says it, it just gets recycled verbatim.

The other part of Dr Wykes's statement is almost equally confusing. She claims that the enrollment benefit occurs when "involving just one or two patients in the study team". However, involving one or two patients would seem to correspond to either the lowest ("patient consultation") or the middle level of reported patient involvement (“researcher initiated collaboration”). In fact, the "high involvement" categories that are supposed to be associated with enrollment success are studies that were either fully designed by patients, or were initiated by patients and researchers equally. So, if there is truly a causal relationship at work here, improving enrollment would not be merely a function of adding a patient or two to the conversation.

There are a number of other frustrating aspects of this study as well. It doesn't actually measure patient involvement in any specific research program, but uses just 3 broad categories (that the researchers specified at the beginning of each study). It uses an arbitrary and undocumented 17-point scale to measure "study complexity", which collapses and quite likely underweights many critical factors into a single number. The enrollment analysis excluded 11 studies because they weren't adequate for a factor that was later deemed non-significant. And probably the most frustrating facet of the paper is that the authors share absolutely no descriptive data about the studies involved in the enrollment analysis. It would be completely impossible to attempt to replicate its methods or verify its analysis. Do the authors believe that "Public Involvement" is only good when it’s not focused on their own work?

However, my feelings about the study and paper are an insignificant fraction of the frustration I feel about the public portrayal of the data by people who should clearly know better. After all, limited evidence is still evidence, and every study can add something to our knowledge. But the public misrepresentation of the evidence by leaders in the area can only do us harm: it has the potential to actively distort research priorities and funding.

Why This Matters

We all seem to agree that research is too slow. Low clinical trial enrollment wastes time, money, and the health of patients who need better treatment options.

However, what's also clear is that we lack reliable evidence on what activities enable us to accelerate the pace of enrollment without sacrificing quality. If we are serious about improving clinical trial accrual, we owe it to our patients to demand robust evidence for what works and what doesn’t. Relying on weak evidence that we've already solved the problem ("we've tripled enrollment!") or have a method to magically solve it ("PPI quadrupled enrollment!") will cause us to divert significant time, energy, and human health into areas that are politically favored but less than certain to produce benefit. And the overhyping those results by research leadership compounds that problem substantially. NIHR leadership should reconsider its approach to public discussion of its research, and practice what it preaches: critical assessment of the data.

[Update Sept. 20: The authors of the study have posted a lengthy comment below. My follow-up is here.]
 
[Image via flikr user Elliot Brown.]


Ennis L, & Wykes T (2013). Impact of patient involvement in mental health research: longitudinal study. The British journal of psychiatry : the journal of mental science PMID: 24029538





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Questionable Enrollment Math(s) - the Authors Respond

The authors of the study I blogged about on Monday were kind enough to post a lengthy comment, responding in part to some of the issues I raised. I thought their response was interesting, and so reprint it in its entirety below, interjecting my own reactions as well.

There were a number of points you made in your blog and the title of questionable maths was what caught our eye and so we reply on facts and provide context.

Firstly, this is a UK study where the vast majority of UK clinical trials take place in the NHS. It is about patient involvement in mental health studies - an area where recruitment is difficult because of stigma and discrimination.

I agree, in hindsight, that I should have titled the piece “questionable maths” rather than my Americanized “questionable math”. Otherwise, I think this is fine, although I’m not sure that anything here differs from my post.

1. Tripling of studies - You dispute NIHR figures recorded on a national database and support your claim with a lone anecdote - hardly data that provides confidence. The reason we can improve recruitment is that NIHR has a Clinical Research Network which provides extra staff, within the NHS, to support high quality clinical studies and has improved recruitment success.

To be clear, I did not “dispute” the figures so much as I expressed sincere doubt that those figures correspond with an actual increase in actual patients consenting to participate in actual UK studies. The anecdote explains why I am skeptical – it's a bit like I've been told there was a magnitude 8 earthquake in Chicago, but neither I nor any of my neighbors felt anything. There are many reasons why reported numbers can increase in the absence of an actual increase. It’s worth noting that my lack of confidence in the NIHR's claims appears to be shared by the 2 UK-based experts quoted by Applied Clinical Trials in the article I linked to.

2. Large database: We have the largest database of detailed study information and patient involvement data - I have trawled the world for a bigger one and NIMH say there certainly isn't one in the USA. This means few places where patient impact can actually be measured
3. Number of studies: The database has 374 studies which showed among other results that service user involvement increased over time probably following changes by funders e.g. NIHR requests information in the grant proposal on how service users have been and will be involved - one of the few national funders to take this issue seriously.

As far as I can tell, neither of these points is in dispute.

4. Analysis of patient involvement involves the 124 studies that have completed. You cannot analyse recruitment success unless then.

I agree you cannot analyze recruitment success in studies that have not yet completed. My objection is that in both the KCL press release and the NIHR-authored Guardian article, the only number mentioned in 374, and references to the recruitment success findings came immediately after references to that number. For example:

Published in the British Journal of Psychiatry, the researchers analysed 374 studies registered with the Mental Health Research Network (MHRN).
Studies which included collaboration with service users in designing or running the trial were 1.63 times more likely to recruit to target than studies which only consulted service users.  Studies which involved more partnerships - a higher level of Patient and Public Involvement (PPI) - were 4.12 times more likely to recruit to target.

The above quote clearly implies that the recruitment conclusions were based on an analysis of 374 studies – a sample 3 times larger than the sample actually used. I find this disheartening.

The complexity measure was developed following a Delphi exercise with clinicians, clinical academics and study delivery staff to include variables likely to be barriers to recruitment. It predicts delivery difficulty (meeting recruitment & delivery staff time). But of course you know all that as it was in the paper.

Yes, I did know this, and yes, I know it because it was in the paper. In fact, that’s all I know about this measure, which is what led me to characterize it as “arbitrary and undocumented”. To believe that all aspects of protocol complexity that might negatively affect enrollment have been adequately captured and weighted in a single 17-point scale requires a leap of faith that I am not, at the moment, able to make. The extraordinary claim that all complexity issues have been accounted for in this model requires extraordinary evidence, and “we conducted a Delphi exercise” does not suffice.  

6. All studies funded by NIHR partners were included – we only excluded studies funded without peer review, not won competitively. For the involvement analysis we excluded industry studies because of not being able to contact end users and where inclusion compromised our analysis reliability due to small group sizes.

It’s only that last bit I was concerned about. Specifically, the 11 studies that were excluded due to being in “clinical groups” that were too small, despite the fact that “clinical groups” appear to have been excluded as non-significant from the final model of recruitment success.

(Also: am I being whooshed here? In a discussion of "questionable math" the authors' enumeration goes from 4 to 6. I’m going to take the miscounting here as a sly attempt to see if I’m paying attention...)

I am sure you are aware of the high standing of the journal and its robust peer review. We understand that our results must withstand the scrutiny of other scientists but many of your comments were unwarranted. This is the first in the world to investigate patient involvement impact. No other databases apart from the one held by the NIHR Mental Health Research Network is available to test – we only wish they were.

I hope we can agree that peer review – no matter how "high standing" the journal – is not a shield against concern and criticism. Despite the length of your response, I’m still at a loss as to which of my comments specifically were unwarranted.

In fact, I feel that I noted very clearly that my concerns about the study’s limitations were minuscule compared to my concerns about the extremely inaccurate way that the study has been publicized by the authors, KCL, and the NIHR. Even if I conceded every possible criticism of the study itself, there remains the fact that in public statements, you
  1. Misstated an odds ratio of 4 as “4 times more likely to”
  2. Overstated the recruitment success findings as being based on a sample 3 times larger than it actually was
  3. Re-interpreted, without reservation, a statistical association as a causal relationship
  4. Misstated the difference between the patient involvement categories as being a matter of merely “involving just one or two patients in the study team”
And you did these consistently and repeatedly – in Dr Wykes's blog post, in the KCL press release, and in the NIHR-written Guardian article.

To use the analogy from my previous post: if a pharmaceutical company had committed these acts in public statements about a new drug, public criticism would have been loud and swift.

Your comment on the media coverage of odds ratios is an issue that scientists need to overcome (there is even a section in Wikipedia).

It's highly unfair to blame "media coverage" for the use of an odds ratio as if it were a relative risk ratio. In fact, the first instance of "4 times more likely" appears in Dr Wykes's own blog post. It's repeated in the KCL press release, so you yourselves appear to have been the source of the error.

You point out the base rate issue but of course in a logistic regression you also take into account all the other variables that may impinge on the outcome prior to assessing the effects of our key variable patient involvement - as we did – and showed that the odds ratio is 4.12 - So no dispute about that. We have followed up our analysis to produce a statement that the public will understand. Using the following equations:
Model predicted recruitment lowest level of involvement exp(2.489-.193*8.8-1.477)/(1+exp(2.489-.193*8.8-1.477))=0.33
Model predicted recruitment highest level of involvement exp(2.489-.193*8.8-1.477+1.415)/(1+exp(2.489-.193*8.8-1.477+1.415)=0.67
For a study of typical complexity without a follow up increasing involvement from the lowest to the highest levels increased recruitment from 33% to 66% i.e. a doubling.

So then, you agree that your prior use of “4 times more likely” was not true? Would you be willing to concede that in more or less direct English?

This is important and is the first time that impact has been shown for patient involvement on the study success.
Luckily in the UK we have a network that now supports clinicians to be involved and a system for ensuring study feasibility.
The addition of patient involvement is the additional bonus that allows recruitment to increase over time and so cutting down the time for treatments to get to patients.

No, and no again. This study shows an association in a model. The gap between that and a causal relationship is far too vast to gloss over in this manner.

In summary, I thank the authors for taking the time to response, but I feel they've overreacted to my concerns about the study, and seriously underreacted to my more important concerns about their public overhyping of the study. 

I believe this study provides useful, though limited, data about the potential relationship between patient engagement and enrollment success. On the other hand, I believe the public positioning of the study by its authors and their institutions has been exaggerated and distorted in clearly unacceptable ways. I would ask the authors to seriously consider issuing public corrections on the 4 points listed above.





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Will Your Family Make You a Better Trial Participant?

It is becoming increasing accepted within the research community that patient engagement leads to a host of positive outcomes – most importantly (at least practically speaking) improved clinical trial recruitment and retention.

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".

That latter point - that we could improve trial enrollment and completion rates by converting the (very large) pool of less-engaged patient - is a central tenet of the mHealth movement in clinical trials. Since technology can now accompany us almost anywhere, it would seem that we have an unprecedented opportunity to reach out and connect with current and potential trial participants.

However, there are signs that this promised revolution in patient engagement hasn't come about. From the decline of new apps being downloaded to the startlingly high rate of people abandoning their wearable health devices, there's a growing body of evidence suggesting that we aren't in fact making very good progress towards increasing engagement. We appear to have underestimated the inertia of the disengaged patient.

So what can we do? We know people like their technology, but if they're not using it to engage with their healthcare decisions, we're no better off as a result.

Daniel Calvert, in a recent blog post at Parallel 6 offers an intriguing solution: he suggests we go beyond the patient and engage their wider group of loved ones. By engaging what Calvert calls the Support Circle - those people most likely to "encourage the health and well being of that patient as they undergo a difficult period of their life" - trial teams will find themselves with a more supported, and therefore more engaged, participant, with corresponding benefits to enrollment and retention. 

Calvert outlines a number of potential mechanisms to get spouses, children, and other loved ones involved in the trial process:
During the consent process the patient can invite their support team in with them. A mobile application can be put on their phones enabling encouraging messages, emails, and texts to be sent. Loved ones can see if their companion or family member did indeed take today’s medication or make last Monday’s appointment. Gamification offers badges or pop-ups: “Two months of consecutive appointments attended” or “perfect eDiary log!” Loved ones can see those notifications, like/comment, and constantly encourage the patients. 
Supporting materials can also be included in the Support Circle application. There are a host of unknown terms to patients and their team. Glossaries, videos, FAQs, contact now, and so much more can be made available at their fingertips.
I have to admit I'm fascinated by Calvert's idea. I want him to be right: the picture of supportive, encouraging, loving spouses and children standing by to help a patient get through a clinical trial is an attractive one. So is the idea that they're just waiting for us to include them - all we need to do is a bit of digital communication with them to get them fully on board as members of the study team.

The problem, however, remains: we have absolutely no evidence that this approach will work. There is no data showing that it is superior to other approaches to engage trial patients.

(In fact, we may even have some indirect evidence that it may hinder enrollment: in trials that require active caregiver participation, such as those in Alzheimer's Disease, caregivers are believed to often contribute to the barriers to patient enrollment).

Calvert's idea is a good one, and it's worthy of consideration. More importantly, it's worthy of being rigorously tested against other recruitment and retention approaches. We have a lot of cool new technologies, and even more great ideas - we're not lacking for those. What we're lacking is hard data showing us how these things perform. What we especially need is comparative data showing how new tactics work relative to other approaches.

Over 5 years ago, I wrote a blog post bemoaning the sloppy approaches we take in trial recruitment - a fact made all the more painfully ironic by the massive intellectual rigor of the trials themselves. I'm not at all sure that we've made any real progress in those 5 years.

In my next post, I'll outline what I believe are some of the critical steps we need to take to improve the current situation, and start bringing some solid evidence to the table along with our ideas.

[Photo credit: Flikr user Matthew G, "Love (of technology)"]







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Jerry Matczak

Jerry Matczak passed away suddenly last Thursday at the much-too-young age of 54.

I can say, without exaggeration, that Jerry embodied pretty much everything I aspire to be in my professional life. The MedCityNews headline called him a “social media guru”, but in reality he was temperamentally the exact opposite of a "guru":

He was constantly curious; it seemed that every conversation I had with him was composed mainly of questions. Many of us try to be “listen first, talk second” types, but Jerry was a “listen first, ask questions, listen some more, then talk” type.

He also never stopped trying to figure out how to improve whatever he was working on. He participated in a lot of pilot projects, which means he was a part of a lot of projects that didn’t meet their objectives – but I never witnessed Jerry being the least bit negative or frustrated. Every project was just another opportunity to learn more.

Mostly, though, Jerry was remarkable in his ability to connect with patients, even patients who were deeply distrustful of his employer and industry. If nothing else, I hope you read the words of two such patients, coming from very different places, with remarkably similar reactions to Jerry:


Jerry, thank you for your service and your example. I carry it with me.





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Establishing efficacy - without humans?

The decade following passage of FDAAA has been one of easing standards for drug approvals in the US, most notably with the advent of “breakthrough” designation created by FDASIA in 2012 and the 21st Century Cures Act in 2016.

Although, as of this writing, there is no nominee for FDA Commissioner, it appears to be safe to say that the current administration intends to accelerate the pace of deregulation, mostly through further lowering of approval requirements. In fact, some of the leading contenders for the position are on record as supporting a return to pre-Kefauver-Harris days, when drug efficacy was not even considered for approval.

Build a better mouse model, and pharma will
beat a path to your door - no laws needed.

In this context, it is at least refreshing to read a proposal to increase efficacy standards. This comes from two bioethicists at McGill University, who make the somewhat-startling case for a higher degree of efficacy evaluation before a drug begins any testing in humans.
We contend that a lack of emphasis on evidence for the efficacy of drug candidates is all too common in decisions about whether an experimental medicine can be tested in humans. We call for infrastructure, resources and better methods to rigorously evaluate the clinical promise of new interventions before testing them on humans for the first time.
The author propose some sort of centralized clearinghouse to evaluate efficacy more rigorously. It is unclear what they envision this new multispecialty review body’s standards for green-lighting a drug to enter human testing. Instead they propose three questions:
  • What is the likelihood that the drug will prove clinically useful?
  • Assume the drug works in humans. What is the likelihood of observing the preclinical results?
  • Assume the drug does not work in humans. What is the likelihood of observing the preclinical results?
These seem like reasonable questions, I suppose – and are likely questions that are already being asked of preclinical data. They certainly do not rise to the level of providing a clear standard for regulatory approval, though perhaps it’s a reasonable place to start.

The most obvious counterargument here is one that the authors curiously don’t pick up on at all: if we had the ability to accurately (or even semiaccurately) predict efficacy preclinically, pharma sponsors would already be doing it. The comment notes: “More-thorough assessments of clinical potential before trials begin could lower failure rates and drug-development costs.” And it’s hard not to agree: every pharmaceutical company would love to have even an incrementally-better sense of whether their early pipeline drugs will be shown to work as hoped.

The authors note
Commercial interests cannot be trusted to ensure that human trials are launched only when the case for clinical potential is robust. We believe that many FIH studies are launched on the basis of flimsy, underscrutinized evidence.
However, they do not produce any evidence that industry is in any way deliberately underperforming their preclinical work, merely that preclinical efficacy is often difficult to reproduce and is poorly correlated with drug performance in humans.

Pharmaceutical companies have many times more candidate compounds than they can possibly afford to put into clinical trials. Figuring out how to lower failure rates – or at least the total cost of failure - is a prominent industry obsession, and efficacy remains the largest source of late-stage trial failure. This quest to “fail faster” has resulted in larger and more expensive phase 2 trials, and even to increased efficacy testing in some phase 1 trials. And we do this not because of regulatory pressure, but because of hopes that these efforts will save overall costs. So it seems beyond probable that companies would immediately invest more in preclinical efficacy testing, if such testing could be shown to have any real predictive power. But generally speaking, it does not.

As a general rule, we don’t need regulations that are firmly aligned with market incentives, we need regulations if and when we think those incentives might run counter to the general good. In this case, there are already incredibly strong market incentives to improve preclinical assessments. Where companies have attempted to do something with limited success, it would seem quixotic to think that regulatory fiat will accomplish more.

(One further point. The authors try to link the need for preclinical efficacy testing to the 2016 Bial tragedy. This seems incredibly tenuous: the authors speculate that perhaps trial participants would not have been harmed and killed if Bial had been required to produce more evidence of BIA102474’s clinical efficacy before embarking on their phase 1 trials. But that would have been entirely coincidental in this case: if the drug had in fact more evidence of therapeutic promise, the tragedy still would have happened, because it had nothing at all to do with the drug’s efficacy.

This is to some extent a minor nitpick, since the argument in favor of earlier efficacy testing does not depend on a link to Bial. However, I bring it up because a) the authors dedicate the first four paragraphs of their comment to the link, and b) there appears to be a minor trend of using the death and injuries of that trial to justify an array of otherwise-unrelated initiatives. This seems like a trend we should discourage.)

[Update 2/23: I posted this last night, not realizing that only a few hours earlier, John LaMattina had published on this same article. His take is similar to mine, in that he is suspicious of the idea that pharmaceutical companies would knowingly push ineffective drugs up their pipeline.]

Kimmelman, J., & Federico, C. (2017). Consider drug efficacy before first-in-human trials Nature, 542 (7639), 25-27 DOI: 10.1038/542025a




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Hospitals face months of IV fluid shortages after Helene damages N.C. factory

Hospitals have been forced to innovate with new ways of hydrating patients and giving them medications, after a key factory that produces IV fluid bags flooded during Hurricane Helene. (This story first aired on Morning Edition on Nov. 7, 2024.)




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A human bird flu case is thought to be found in Canada for the first time

A person has tested positive in British Columbia, Canadian health officials said, though the results must be sent to another lab for confirmation.




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Remarkably resilient refugees: A teen on his own, a woman who was raped

Sudan's civil war has displaced 10 million citizens. Here are profiles of two young people from the most vulnerable groups: an unaccompanied minor caring for twin brothers, a woman who was raped.




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MRI Sheds Its Shielding and Superconducting Magnets



Magnetic resonance imaging (MRI) has revolutionized healthcare by providing radiation-free, non-invasive 3-D medical images. However, MRI scanners often consume 25 kilowatts or more to power magnets producing magnetic fields up to 1.5 tesla. These requirements typically limits scanners’ use to specialized centers and departments in hospitals.

A University of Hong Kong team has now unveiled a low-power, highly simplified, full-body MRI device. With the help of artificial intelligence, the new scanner only requires a compact 0.05 T magnet and can run off a standard wall power outlet, requiring only 1,800 watts during operation. The researchers say their new AI-enabled machine can produce clear, detailed images on par with those from high-power MRI scanners currently used in clinics, and may one day help greatly improve access to MRI worldwide.

To generate images, MRI applies a magnetic field to align the poles of the body’s protons in the same direction. An MRI scanner then probes the body with radio waves, knocking the protons askew. When the radio waves turn off, the protons return to their original alignment, transmitting radio signals as they do so. MRI scanners receive these signals, converting them into images.

More than 150 million MRI scans are conducted worldwide annually, according to the Organization for Economic Cooperation and Development. However, despite five decades of development, clinical MRI procedures remain out of reach for more than two-thirds of the world’s population, especially in low- and middle-income countries. For instance, whereas the United States has 40 scanners per million inhabitants, in 2016 there were only 84 MRI units serving West Africa’s population of more than 370 million.

This disparity largely stems from the high costs and specialized settings required for standard MRI scanners. They use powerful superconducting magnets that require a lot of space, power, and specialized infrastructure. They also need rooms shielded from radio interference, further adding to hardware costs, restricting their mobility, and hampering their availability in other medical settings.

Scientists around the globe have already been exploring low-cost MRI scanners that operate at ultra-low-field (ULF) strengths of less than 0.1 T. These devices may consume much less power and prove potentially portable enough for bedside use. Indeed, as the Hong Kong team notes, MRI development initially focused on low fields of about 0.05 T, until the introduction of the first whole-body 1.5 T superconducting scanner by General Electric in 1983.

The new MRI scanner (top left) is smaller than conventional scanners, and does away with bulky RF shielding and superconducting magnetics. The new scanner’s imaging resolution is on par with conventional scanners (bottom).Ed X. Wu/The University of Hong Kong

Current ULF MRI scanners often rely on AI to help reconstruct images from what signals they gather using relatively weak magnetic fields. However, until now, these devices were limited to solely imaging the brain, extremities, or single organs, Udunna Anazodo, an assistant professor of neurology and neurosurgery at McGill University in Montreal who did not take part in the work, notes in a review of the new study.

The Hong Kong team have now developed a whole-body ULF MRI scanner in which patients are placed between two permanent neodymium ferrite boron magnet plates—one above the body and the other below. Although these permanent magnets are far weaker than superconductive magnets, they are low-cost, readily available, and don’t require liquid helium or to be cooled to superconducting temperatures. In addition, the amount of energy ULF MRI scanners deposit into the body is roughly one-thousandth that from conventional scanners, making heat generation during imaging much less of a concern, Anazodo notes in her review. ULF MRI is also much quieter than regular MRI, which may help with pediatric scanning, she adds.

The new machine consists of two units, each roughly the size of a hospital gurney. One unit houses the MRI device, while the other supports the patient’s body as it slides into the scanner.

To account for radio interference from both the outside environment and the ULF MRI’s own electronics, the scientists deployed 10 small sensor coils around the scanner and inside the electronics cabinet to help the machine detect potentially disruptive radio signals. They also employed deep learning AI methods to help reconstruct images even in the presence of strong noise. They say this eliminates the need for shielding against radio waves, making the new device far more portable than conventional MRI.

In tests on 30 healthy volunteers, the device captured detailed images of the brain, spine, abdomen, heart, lung, and extremities. Scanning each of these targets took eight minutes or less for image resolutions of roughly 2 by 2 by 8 cubic millimeters. In Anazodo’s review, she notes the new machine produced image qualities comparable to those of conventional MRI scanners.

“It’s the beginning of a multidisciplinary endeavor to advance an entirely new class of simple, patient-centric and computing-powered point-of-care diagnostic imaging device,” says Ed Wu, a professor and chair of biomedical engineering at the University of Hong Kong.

The researchers used standard off-the-shelf electronics. All in all, they estimate hardware costs at about US $22,000. (According to imaging equipment company Block Imaging in Holt, Michigan, entry-level MRI scanners start at $225,000, and advanced premium machines can cost $500,000 or more.)

The prototype scanner’s magnet assembly is relatively heavy, weighing about 1,300 kilograms. (This is still lightweight compared to a typical clinical MRI scanner, which can weigh up to 17 tons, according to New York University’s Langone Health center.) The scientists note that optimizing the hardware could reduce the magnet assembly’s weight to about 600 kilograms, which would make the entire scanner mobile.

The researchers note their new device is not meant to replace conventional high-magnetic-field MRI. For instance, a 2023 study notes that next-generation MRI scanners using powerful 7 T magnets could yield a resolution of just 0.35 millimeters. Instead, ULF MRI can complement existing MRI by going to places that can’t host standard MRI devices, such as intensive care units and community clinics.

In an email, Anazodo adds this new Hong Kong work is just one of a number of exciting ULF MRI scanners under development. For instance, she notes that Gordon Sarty at the University of Saskatchewan and his colleagues are developing that device that is potentially even lighter, cheaper and more portable than the Hong Kong machine, which they are researching for use in whole-body imaging on the International Space Station.

Wu and his colleagues detailed their findings online 10 May in the journal Science.

This article appears in the July 2024 print issue as “Compact MRI Ditches Superconducting Magnets.”




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“Snake-like” Probe Images Arteries from Within



Neurosurgeon Vitor Mendes Pereira has grown accustomed to treating brain aneurysms with only blurry images for guidance.

Equipped with a rough picture of the labyrinthine network of arteries in the brain, he does his best to insert mesh stents or coils of platinum wire—interventions intended to promote clotting and to seal off a bulging blood vessel.

The results are not always perfect. Without a precise window into the arterial architecture at the aneurysm site, Pereira says that he and other neurovascular specialists occasionally misplace these implants, leaving patients at a heightened risk of stroke, clotting, inflammation, and life-threatening ruptures. But a new fiber-optic imaging probe offers hope for improved outcomes.

Pereira et al./Science Translational Medicine

According to Pereira’s early clinical experience, the technology—a tiny snake-like device that winds its way through the intricate maze of brain arteries and, using spirals of light, captures high-resolution images from the inside-out—provides an unprecedented level of structural detail that enhances the ability of clinicians to troubleshoot implant placement and better manage disease complications.

“We can see a lot more information that was not accessible before,” says Pereira, director of endovascular research and innovation at St. Michael’s Hospital in Toronto. “This is, for us, an incredible step forward.”

And not just for brain aneurysms. In a report published today in Science Translational Medicine, Pereira and his colleagues describe their first-in-human experience using the platform to guide treatment for 32 people with strokes, artery hardening, and various other conditions arising from aberrant blood vessels in the brain.

Whereas before, with technologies such as CT scans, MRIs, ultrasounds, and x-rays, clinicians had a satellite-like view of the brain’s vascular network, now they have a Google Street View-like perspective, complete with in-depth views of artery walls, plaques, immune cell aggregates, implanted device positions, and more.

“The amount of detail you could get you would never ever see with any other imaging modality,” says Adnan Siddiqui, a neurosurgeon at the University at Buffalo, who was not involved in the research. “This technology holds promise to be able to really transform the way we evaluate success or failure of our procedures, as well as to diagnose complications before they occur.”

A Decade of Innovation

The new fiber-optic probe is flexible enough to snake through the body’s arteries and provide previously unavailable information to surgeons.Pereira et al./Science Translational Medicine

The new imaging platform is the brainchild of Giovanni Ughi, a biomedical engineer at the University of Massachusetts’ Chan Medical School in Worcester. About a decade ago, he set out to adapt a technique called optical coherence tomography (OCT) for imaging inside the brain’s arteries.

OCT relies on the backscattering of near-infrared light to create cross-sectional images with micrometer-scale spatial resolution. Although OCT had long been used in clinical settings to generate pictures from the back of the eye and from inside the arteries that supply blood to the heart, the technology had proven difficult to adapt for brain applications owing to several technical challenges.

One major challenge is that the fiber-optic probes used in the technology are typically quite stiff, making them too rigid to twist and bend through the convoluted passageways of the brain’s vasculature. Additionally, the torque cables—traditionally used to rotate the OCT lens to image surrounding vessels and devices in three dimensions as the probe retracts—were too large to fit inside the catheters that are telescopically advanced into the brain’s arteries to address blockages or other vascular issues.

“We had to invent a new technology,” Ughi explains. “Our probe had to be very, very flexible, but also very, very small to be compatible with the clinical workflow.”

To achieve these design criteria, Ughi and his colleagues altered the properties of the glass at the heart of their fiber-optic cables, devised a new system of rotational control that does away with torque cables, miniaturized the imaging lens, and made a number of other engineering innovations.

The end result: a slender probe, about the size of a fine wire, that spins 250 times per second, snapping images as it glides back through the blood vessel. Researchers flush out blood cells with a tablespoon of liquid, then manually or automatically retract the probe, revealing a section of the artery about the length of a lip balm tube.

St. Michael’s Foundation

Clinical Confirmation

After initial testing in rabbits, dogs, pigs, and human cadavers, Ughi’s team sent the device to two clinical groups: Pereira’s in Toronto and Pedro Lylyk’s at the Sagrada Familia Clinic in Buenos Aires, Argentina. Across the two groups, neurosurgeons treated the 32 participants in the latest study, snaking the imaging probe through the patients’ groins or wrists and into their brains.

The procedure was safe and well-tolerated across different anatomies, underlying disease conditions, and the complexity of prior interventions. Moreover, the information provided frequently led to actionable insights—in one case, prompting clinicians to prescribe anti-platelet drugs when hidden clots were discovered; in another, aiding in the proper placement of stents that were not flush against the arterial wall.

“We were successful in every single case,” Ughi says. “So, this was a huge confirmation that the technology is ready to move forward.”

“We can see a lot more information that was not accessible before.” —Vitor Mendes Pereira, St. Michael’s Hospital

A startup called Spryte Medical aims to do just that. According to founder and CEO David Kolstad, the company is in discussions with regulatory authorities in Europe, Japan, and the United States to determine the steps necessary to bring the imaging probe to market.

At the same time, Spryte—with Ughi as senior director of advanced development and software engineering—is working on machine learning software to automate the image analysis process, thus simplifying diagnostics and treatment planning for clinicians.

Bolstered by the latest data, cerebrovascular specialists like Siddiqui now say they are chomping at the bit to get their hands on the imaging probe once it clears regulatory approval.

“I’m really impressed,” Siddiqui says. “This is a tool that many of us who do these procedures wish they had.”




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Is AI Search a Medical Misinformation Disaster?



Last month when Google introduced its new AI search tool, called AI Overviews, the company seemed confident that it had tested the tool sufficiently, noting in the announcement that “people have already used AI Overviews billions of times through our experiment in Search Labs.” The tool doesn’t just return links to Web pages, as in a typical Google search, but returns an answer that it has generated based on various sources, which it links to below the answer. But immediately after the launch users began posting examples of extremely wrong answers, including a pizza recipe that included glue and the interesting fact that a dog has played in the NBA.

Renée DiResta has been tracking online misinformation for many years as the technical research manager at Stanford’s Internet Observatory.

While the pizza recipe is unlikely to convince anyone to squeeze on the Elmer’s, not all of AI Overview’s extremely wrong answers are so obvious—and some have the potential to be quite harmful. Renée DiResta has been tracking online misinformation for many years as the technical research manager at Stanford’s Internet Observatory and has a new book out about the online propagandists who “turn lies into reality.” She has studied the spread of medical misinformation via social media, so IEEE Spectrum spoke to her about whether AI search is likely to bring an onslaught of erroneous medical advice to unwary users.

I know you’ve been tracking disinformation on the Web for many years. Do you expect the introduction of AI-augmented search tools like Google’s AI Overviews to make the situation worse or better?

Renée DiResta: It’s a really interesting question. There are a couple of policies that Google has had in place for a long time that appear to be in tension with what’s coming out of AI-generated search. That’s made me feel like part of this is Google trying to keep up with where the market has gone. There’s been an incredible acceleration in the release of generative AI tools, and we are seeing Big Tech incumbents trying to make sure that they stay competitive. I think that’s one of the things that’s happening here.

We have long known that hallucinations are a thing that happens with large language models. That’s not new. It’s the deployment of them in a search capacity that I think has been rushed and ill-considered because people expect search engines to give them authoritative information. That’s the expectation you have on search, whereas you might not have that expectation on social media.

There are plenty of examples of comically poor results from AI search, things like how many rocks we should eat per day [a response that was drawn for an Onion article]. But I’m wondering if we should be worried about more serious medical misinformation. I came across one blog post about Google’s AI Overviews responses about stem-cell treatments. The problem there seemed to be that the AI search tool was sourcing its answers from disreputable clinics that were offering unproven treatments. Have you seen other examples of that kind of thing?

DiResta: I have. It’s returning information synthesized from the data that it’s trained on. The problem is that it does not seem to be adhering to the same standards that have long gone into how Google thinks about returning search results for health information. So what I mean by that is Google has, for upwards of 10 years at this point, had a search policy called Your Money or Your Life. Are you familiar with that?

I don’t think so.

DiResta: Your Money or Your Life acknowledges that for queries related to finance and health, Google has a responsibility to hold search results to a very high standard of care, and it’s paramount to get the information correct. People are coming to Google with sensitive questions and they’re looking for information to make materially impactful decisions about their lives. They’re not there for entertainment when they’re asking a question about how to respond to a new cancer diagnosis, for example, or what sort of retirement plan they should be subscribing to. So you don’t want content farms and random Reddit posts and garbage to be the results that are returned. You want to have reputable search results.

That framework of Your Money or Your Life has informed Google’s work on these high-stakes topics for quite some time. And that’s why I think it’s disturbing for people to see the AI-generated search results regurgitating clearly wrong health information from low-quality sites that perhaps happened to be in the training data.

So it seems like AI overviews is not following that same policy—or that’s what it appears like from the outside?

DiResta: That’s how it appears from the outside. I don’t know how they’re thinking about it internally. But those screenshots you’re seeing—a lot of these instances are being traced back to an isolated social media post or a clinic that’s disreputable but exists—are out there on the Internet. It’s not simply making things up. But it’s also not returning what we would consider to be a high-quality result in formulating its response.

I saw that Google responded to some of the problems with a blog post saying that it is aware of these poor results and it’s trying to make improvements. And I can read you the one bullet point that addressed health. It said, “For topics like news and health, we already have strong guardrails in place. In the case of health, we launched additional triggering refinements to enhance our quality protections.” Do you know what that means?

DiResta: That blog posts is an explanation that [AI Overviews] isn’t simply hallucinating—the fact that it’s pointing to URLs is supposed to be a guardrail because that enables the user to go and follow the result to its source. This is a good thing. They should be including those sources for transparency and so that outsiders can review them. However, it is also a fair bit of onus to put on the audience, given the trust that Google has built up over time by returning high-quality results in its health information search rankings.

I know one topic that you’ve tracked over the years has been disinformation about vaccine safety. Have you seen any evidence of that kind of disinformation making its way into AI search?

DiResta: I haven’t, though I imagine outside research teams are now testing results to see what appears. Vaccines have been so much a focus of the conversation around health misinformation for quite some time, I imagine that Google has had people looking specifically at that topic in internal reviews, whereas some of these other topics might be less in the forefront of the minds of the quality teams that are tasked with checking if there are bad results being returned.

What do you think Google’s next moves should be to prevent medical misinformation in AI search?

DiResta: Google has a perfectly good policy to pursue. Your Money or Your Life is a solid ethical guideline to incorporate into this manifestation of the future of search. So it’s not that I think there’s a new and novel ethical grounding that needs to happen. I think it’s more ensuring that the ethical grounding that exists remains foundational to the new AI search tools.




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