<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>

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.

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

The General Pharmaceutical Council has said it is “double, treble, quadruple-checking” for any “flexibility” that would allow all overseas candidates to sit the March 2021 registration assessment exam in their countries of residence.

Some 180 women were prescribed valproate, a medicine used to treat epilepsy and bipolar disorder, during their pregnancy within a 2.5 year interval, NHS data has revealed.

The General Pharmaceutical Council has said most candidates living in countries with a two-hour or more time difference from the UK will be able to apply to sit the registration assessment at home.

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 […]

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.]

[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

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.
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

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.

The Wall Street Journal has an interesting article on the use of “Big Data” to identify and solicit potential clinical trial participants. The premise is that large consumer data aggregators like Experian can target patients with certain diseases through correlations with non-health behavior. Examples given include “a preference for jazz” being associated with arthritis and “shopping online for clothes” being an indicator of obesity.

We've seen this story before.

In this way, allegedly, clinical trial patient recruitment companies can more narrowly target their solicitations* for patients to enroll in clinical trials.

In the spirit of full disclosure, I should mention that I was interviewed by the reporter of this article, although I am not quoted. My comments generally ran along three lines, none of which really fit in with the main storyline of the article:

1. I am highly skeptical that these analyses are actually effective at locating patients
   
2. These methods aren't really new – they’re the same tactics that direct marketers have been using for years
   
3. Most importantly, the clinical trials community can – and should – be moving towards open and collaborative patient engagement. Relying on tactics like consumer data snooping and telemarketing is an enormous step backwards.

The first point is this: certainly some diseases have correlates in the real world, but these correlates tend to be pretty weak, and are therefore unreliable predictors of disease. Maybe it’s true that those struggling with obesity tend to buy more clothes online (I don’t know if it’s true or not – honestly it sounds a bit more like an association built on easy stereotypes than on hard data). But many obese people will not shop online (they will want to be sure the clothes actually fit), and vast numbers of people with low or average BMIs will shop for clothes online.  So the consumer data will tend to have very low predictive value. The claims that liking jazz and owning cats are predictive of having arthritis are even more tenuous. These correlates are going to be several times weaker than basic demographic information like age and gender. And for more complex conditions, these associations fall apart.

Marketers claim to solve this by factoring a complex web of associations through a magical black box – th WSJ article mentions that they “applied a computed algorithm” to flag patients. Having seen behind the curtain on a few of these magic algorithms, I can confidently say that they are underwhelming in their sophistication. Hand-wavy references to Big Data and Algorithms are just the tools used to impress pharma clients. (The down side to that, of course, is that you can’t help but come across as big brotherish – see this coverage from Forbes for a taste of what happens when people accept these claims uncritically.)

But the effectiveness of these data slice-n-dicing activities is perhaps beside the point. They are really just a thin cover for old-fashioned boiler room tactics: direct mail and telemarketing. When I got my first introduction to direct marketing in the 90’s, it was the exact same program – get lead lists from big companies like Experian, then aggressively mail and call until you get a response.

The limited effectiveness and old-school aggressiveness of these programs comes is nicely illustrated in the article by one person’s experience:

Larna Godsey, of Wichita, Kan., says she received a dozen phone calls about a diabetes drug study over the past year from a company that didn't identify itself. Ms. Godsey, 63, doesn't suffer from the disease, but she has researched it on the Internet and donated to diabetes-related causes. "I don't know if it's just a coincidence or if they're somehow getting my information," says Ms. Godsey, who filed a complaint with the FTC this year.

The article notes that one recruitment company, Acurian, has been the subject of over 500 FTC complaints regarding its tactics. It’s clear that Big Data is just the latest buzzword lipstick on the telemarketing pig. And that’s the real shame of it.

We have arrived at an unprecedented opportunity for patients, researchers, and private industry to come together and discuss, as equals, research priorities and goals. Online patient communities like Inspire and PatientsLikeMe have created new mechanisms to share clinical trial opportunities and even create new studies. Dedicated disease advocates have jumped right into the world of clinical research, with groups like the Cystic Fibrosis Foundation and Michael J. Fox Foundation no longer content with raising research funds, but actively leading the design and operations of new studies.

Some – not yet enough – pharmaceutical companies have embraced the opportunity to work more openly and honestly with patient groups. The scandal of stories like this is not the Wizard of Oz histrionics of secret computer algorithms, but that we as an industry continue to take the low road and resort to questionable boiler room tactics.

It’s past time for the entire patient recruitment industry to drop the sleaze and move into the 21st century. I would hope that patient groups and researchers will come together as well to vigorously oppose these kinds of tactics when they encounter them.

This new 10-minute TEDMED talk is getting quite a bit of attention:


 (if embedded video does not work, try the TED site itself.)

In it, Roger Stein claims to have created an approach to advancing drugs through clinical trials that will "fundamentally change the way research for cancer and lots of other things gets done".

Because the costs of bringing a drug to market are so high, time from discovery to marketing is so long, and the chances of success of any individual drug are so grim, betting on any individual drug is foolish, according to Stein. Instead, risks for a large number of potential assets should be pooled, with the eventual winners paying for the losers.

To do this, Stein proposes what he calls a "megafund" - a large collection of assets (candidate therapies). Through some modeling and simulations, Stein suggests some of the qualities of an ideal megafund: it would need in the neighborhood of $3-15 billion to acquire and manage 80-150 drugs. A fund of this size and with these assets would be able to provide an equity yield of about 12%, which would be "right in the investment sweet spot of pension funds and 401(k) plans".

Here's what I find striking about those numbers: let's compare Stein's Megafund to everyone's favorite Megalosaurus, the old-fashioned Big Pharma dinosaur sometimes known as Pfizer:

	Megafund (Stein)	Megalosaurus (Pfizer)
Funding	$3-15 billion	$9 billion estimated 2013 R&D spend
Assets	80-150	81 (in pipeline, plus many more in preclinical)
Return on Equity	12% (estimated)	9.2% (last 10 years) to 13.2% (last 5)

Since Pfizer's a dinosaur, it can't possibly compete with the sleek, modern Megafund, right? Right?

These numbers look remarkably similar. Pfizer - and a number of its peers - are spending Megafund-sized budget each year to shepherd through a Megafund-sized number of compounds. (Note many of Pfizer's peers have substantially fewer drugs in their published pipelines, but they own many times more compounds - the pipeline is just the drugs what they've elected to file an IND on.)

What am I missing here? I understand that a fund is not a company, and there may be some benefits to decoupling asset management decisions from actual operations, but this won't be a tremendous gain, and would presumably be at least partially offset by increased transaction costs (Megafund has to source, contract, manage, and audit vendors to design and run all its trials, after all, and I don't know why I'd think it could do that any more cheaply than Big Pharma can). And having a giant drug pipeline's go/no go decisions made by "financial engineers" rather than pharma industry folks would seem like a scenario that's only really seen as an upgrade by the financial engineers themselves.
A tweet from V.S. Schulz pointed me to a post on Derek Lowe's In the Pipeline blog. which lead to a link to this paper by Stein and 2 others in Nature Biotechnology from a year and a half ago. The authors spend most of their time differentiating themselves from other structures in the technical, financial details rather than explaining why megafund would work better at finding new drugs. However, they definitely think this is qualitatively different from existing pharma companies, and offer a couple reasons. First,

[D]ebt financing can be structured to be more “patient” than private or public equity by specifying longer maturities; 10- to 20-year maturities are not atypical for corporate bonds. ... Such long horizons contrast sharply with the considerably shorter horizons of venture capitalists, and the even shorter quarterly earnings cycle and intra-daily price fluctuations faced by public companies.

I'm not sure where this line of though is coming from. Certainly all big pharma companies' plans extend decades into the future - there may be quarterly earnings reports to file, but that's a force exerted far more on sales and marketing teams than on drug development. The financing of pharmaceutical development is already extremely long term.

Even in the venture-backed world, Stein and team are wrong if they believe there is pervasive pressure to magically deliver drugs in record time. Investors and biotech management are both keenly aware of the tradeoffs between speed and regulatory success. Even this week's came-from-nowhere Cinderella story, Intercept Pharmaceuticals, was founded with venture money over a decade ago - these "longer maturities" are standard issue in biotech. We aren't making iPhone apps here, guys.

Second,

Although big pharma companies are central to the later stages of drug development and the marketing and distributing of approved drugs, they do not currently play as active a role at the riskier preclinical and early stages of development

Again, I'm unsure why this is supposed to be so. Of Pfizer's 81 pipeline compounds, 55 are in Phase 1 or 2 - a ratio that's pretty heavy on early, risky project, and that's not too different from industry as a whole. Pfizer does not publish data on the number of compounds it currently has undergoing preclinical testing, but there's no clear reason I can think of to assume it's a small number.

So, is Megafund truly a revolutionary idea, or is it basically a mathematical deck-chair-rearrangement for the "efficiencies of scale" behemoths we've already got?

[Image: the world's first known dino, Megalosaurus, via Wikipedia.]

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Over the past 20 years, technological advances have enabled inventors to go from strength to strength. And yet, according to the legendary inventor Dean Kamen, innovation has stalled. Kamen made a name for himself with inventions including the first portable insulin pump for diabetics, an advanced wheelchair that can climb steps, and the Segway mobility device. Here, he talks about his plan for enabling innovators.

How has inventing changed since you started in the 1990s?

Dean Kamen: Kids all over the world can now be inventing in the world of synthetic biology the way we played with Tinkertoys and Erector Sets and Lego. I used to put pins and smelly formaldehyde in frogs in high school. Today in high school, kids will do experiments that would have won you the Nobel Prize in Medicine 40 years ago. But none of those kids are likely in any short time to be on the market with a pharmaceutical that will have global impact. Today, while invention is getting easier and easier, I think there are some aspects of innovation that have gotten much more difficult.

Can you explain the difference?

Kamen: Most people think those two words mean the same thing. Invention is coming up with an idea or a thing or a process that has never been done that way before. [Thanks to] more access to technology and 3D printers and simulation programs and virtual ways to make things, the threshold to be able to create something new and different has dramatically lowered.

Historically, inventions were only the starting point to get to innovation. And I’ll define an innovation as something that reached a scale where it impacted a piece of the world, or transformed it: the wheel, steam, electricity, Internet. Getting an invention to the scale it needs to be to become an innovation has gotten easier—if it’s software. But if it’s sophisticated technology that requires mechanical or physical structure in a very competitive world? It’s getting harder and harder to do due to competition, due to global regulatory environments.

[For example,] in proteomics [the study of proteins] and genomics and biomedical engineering, the invention part is, believe it or not, getting a little easier because we know so much, because there are development platforms now to do it. But getting a biotech product cleared by the Food and Drug Administration is getting more expensive and time consuming, and the risks involved are making the investment community much more likely to invest in the next version of Angry Birds than curing cancer.

A lot of ink has been spilled about how AI is changing inventing. Why hasn’t that helped?

Kamen: AI is an incredibly valuable tool. As long as the value you’re looking for is to be able to collect massive amounts of data and being able to process that data effectively. That’s very different than what a lot of people believe, which is that AI is inventing and creating from whole cloth new and different ideas.

How are you using AI to help with innovation?

Kamen: Every medical school has incredibly brilliant professors and grad students with petri dishes. “Look, I can make nephrons. We can grow people a new kidney. They won’t need dialysis.” But they only have petri dishes full of the stuff. And the scale they need is hundreds and hundreds of liters.

I started a not-for-profit called ARMI—the Advanced Regenerative Manufacturing Institute—to help make it practical to manufacture human cells, tissues, and organs. We are using artificial intelligence to speed up our development processes and eliminate going down frustratingly long and expensive [dead-end] paths. We figure out how to bring tissue manufacturing to scale. We build the bioreactors, sensor technologies, robotics, and controls. We’re going to put them together and create an industry that can manufacture hundreds of thousands of replacement kidneys, livers, pancreases, lungs, blood, bone, you name it.

So ARMI’s purpose is to help would-be innovators?

Kamen: We are not going to make a product. We’re not even going to make a whole company. We’re going to create baseline core technologies that will enable all sorts of products and companies to emerge to create an entire new industry. It will be an innovation in health care that will lower costs because cures are much cheaper than chronic treatments. We have to break down the barriers so that these fantastic inventions can become global innovations.

This article appears in the November 2024 print issue as “The Inventor’s Inventor.”

Mental health experts are hopeful about the de-stigmatization of behavioral health, the promise of AI and other areas, they shared at a recent conference.

The post 4 Areas Within Mental Health Care that Give Executives Hope appeared first on MedCity News.

Three ways health plans can engage, connect with, and delight their pregnant members to nurture goodwill, earn long-term trust, and foster loyal relationships that last.

The post Pregnant and Empowered: Why Trust is the Latest Form of Member Engagement appeared first on MedCity News.

Many companies are entering the digital youth mental health space, but it’s important to know which ones are effective, according to a panel of investors at the Behavioral Health Tech conference.

The post Measuring Impact in Digital Youth Mental Health: What Investors Look For appeared first on MedCity News.

During a recent panel, experts discussed the Massachusetts Child Psychiatry Access Program (MCPAP) for Moms and how it achieved scale.

The post How One Massachusetts Maternal Mental Health Program Scaled Across the Country appeared first on MedCity News.

Fort Health’s $5.5 million in funding was led by Twelve Below and Vanterra and included participation from Redesign Health, Blue Venture Fund and True Wealth Ventures.

The post Fort Health Secures $5.5M to Expand Access to Integrated Pediatric Mental Health Care appeared first on MedCity News.

The Pew Charitable Trusts sent comments Jan. 4 to the Office of the National Coordinator for Health Information Technology (ONC) and the Centers for Medicare & Medicaid Services (CMS) urging them to support the easy exchange of individuals’ health records through a pair of regulations.

Breaking COVID-19’s chain of transmission requires effective physical distancing, contact tracing and rapid analyses of demographic data to reveal illness clusters and populations at high risk, such as people older than 65, Latinos and Blacks.

Between 1999 and 2014, opioid use disorder (OUD) among pregnant women more than quadrupled, risking the health of the women—before and after giving birth—and their infants. As states grapple with COVID-19’s exacerbation of the opioid crisis, several are taking innovative steps to address the needs of high-risk groups, including low-income, postpartum patients with OUD.

As the coronavirus pandemic grips the world, the opioid epidemic continues to affect millions of Americans. Several states are developing innovative ways to tackle this public health issue. In this episode, we speak with Beth Connolly, who leads Pew’s research on substance use disorders, and Louisiana Representative Paula Davis, who helped ensure effective treatment in her state.

The United States is grappling with two severe health crises: the COVID-19 pandemic and an opioid epidemic that appears to be worsening as more people deal with stress and isolation as they face increased barriers to medical care. Preliminary numbers for 2020 show that overdose deaths were outpacing the record-setting number of more than 71,000 fatalities in 2019.

Hospitals across the U.S. have significantly restricted the use of pain medications containing narcotics. This shift comes amid […]

The post Pain Management in Crisis: Why Hospitals Are Limiting Pain Medications and What This Means for Patients appeared first on World of DTC Marketing.

The Centers for Medicare and Medicaid Services (CMS) recently announced a 2.9% cut to Medicare physician payments for […]

The post CMS Cuts Medicare Physician Payments: What It Means appeared first on World of DTC Marketing.

SAS admins need to know about these menu options that may not be available in SAS Visual Analytics Viewer.

This SAS Usage Note illustrates fitting a model containing a spline effect in PROC GLIMMIX. It discusses the spline basis output, the interpretation of the output, how to use the spline model to make predictions, and how to use the LSMEANS and ESTIMATE statements to compute quantities of interest.

Denzel Washington has confirmed he will star in Black Panther 3 before his retirement. The 69-year-old actor is the first to talk about the existence of a third film in the blockbuster Marvel franchise — which will follow the 2018 original and 2022 sequel Black Panther: Wakanda Forever — and has also revealed the film will be among a handful of roles he will take on before he bows out of acting after a career spanning four decades. Confirming director Ryan Coogler has written a role just for the Oscar-winner for the third instalment, Denzel told Australia's Today show: "At this point in my career, I'm only interested in working with the best, I don't know how many more films I will make, probably not that many. I want to do things that I haven't done." Sharing the roles he has lined up before he bids farewell to his Hollywood career, he said: "I played Othello at 22, I'm now going to play it at 70. After that, I'm playing Hannibal. After that, I've been talking with Steve McQueen about a film. After that, Ryan Coogler is writing a part for me in the next Black Panther.

UNITED NATIONS — The United States stressed at the United Nations (UN) on Tuesday (Nov 12) that "there must be no forcible displacement, nor policy of starvation in Gaza" by Israel, warning such policies would have grave implications under US and international law. The remarks by US Ambassador to the UN Linda Thomas-Greenfield came just hours after Washington said its ally Israel was doing enough to address the humanitarian crisis in Israel to avoid facing potential restrictions on US military aid. "Still, Israel must ensure its actions are fully implemented - and its improvements sustained over time," Thomas-Greenfield told the UN Security Council. It was also urgently important that Israel pause implementation of a law banning the operation of the UN Palestinian relief agency UNRWA, she added.

WASHINGTON — US President-elect Donald Trump said on Nov 12 that Elon Musk and former Republican presidential hopeful Vivek Ramaswamy will lead the newly created Department of Government Efficiency. Musk and Ramaswamy "will pave the way for my Administration to dismantle Government Bureaucracy, slash excess regulations, cut wasteful expenditures, and restructure Federal Agencies", Trump said in a statement. Trump said their work would conclude by July 4, 2026, adding that a smaller and more efficient government would be a "gift" to the country on the 250th anniversary of the signing of the Declaration of Independence. Businessman and former Republican presidential candidate Vivek Ramaswamy attends Donald Trump's campaign event sponsored by conservative group Turning Point Action, in Las Vegas, Nevada, US, Oct 24, 2024. PHOTO: Reuters file The appointments reward two Trump supporters from the private sector.

The Public Service has expressed its commitment to implementing flexible work arrangements (FWAs) for its employees, taking into account the workforce's changing needs. In a written answer to a Parliamentary question posed by Choa Chu Kang GRC MP Zhulkarnain Abdul Rahim on Monday (Nov 11), Minister-in-charge of the Public Service Chan Chun Sing said the Government recognises the growing need for FWAs, given Singapore's demographic changes and its ever-changing demands on Singaporeans. Zhulkarnain had asked whether the Civil Service will continue to support flexible working arrangements despite some companies in the private sector requiring employees to work from the office five days a week. Grab Singapore, for example, said it will enforce its five-day return-to-office mandate starting Dec 2, reported CNA. Referencing the Tripartite Guidelines on FWA Requests (TG-FWAR), which will be enforced starting Dec 1, Chan stressed the importance of such arrangements in supporting working caregivers, encouraging workforce re-entry, sustaining labour force participation, and attracting and retaining talent.

The Community Disputes Resolution Tribunals (CDRT) will be able to mandate mental health treatment for those who cause unreasonable interferences in the community if a bill to amend the Community Disputes Resolution Act (CDRA) goes through.  The bill was proposed in Parliament by Minister for Community, Culture and Youth Edwin Tong on Tuesday (Nov 12). The CDRT currently hears disputes under CDRA between neighbours involving acts of unreasonable interference with the enjoyment or use of places of residence. Under the bill, the tribunal will be able to issue Mandatory Treatment Orders (MTO) should there be a belief that the acts of disturbance stem from an underlying psychiatric condition. "In those cases, the issue therefore is not just a disamenity one," Minister Tong said. "Hence, the MTO is intended to address the root cause of certain acts that a resident may engage in." Tong added that their priority remains in persuading the resident to go for treatment voluntarily, and that the CDRT-issued MTO is a measure of last resort. There are also criteria that must be met for the MTO to be issued.

JAKARTA — Indonesia said on Monday (Nov 11) it does not recognise China's claims over the South China Sea despite signing a joint maritime development deal with Beijing, as some analysts warned the agreement risked compromising the country's sovereign rights. Beijing has long clashed with its Southeast Asian neighbours over territory in the South China Sea, which it claims sovereignty over in almost its entirety via a "nine-dash line" on its maps that cuts into the exclusive economic zones (EEZ) of several countries. Joint agreements with China in the strategic waterway have for years been sensitive, with some claimant states wary of entering into deals they fear could be interpreted as legitimising Beijing's vast claims. An arbitral tribunal in 2016 said the Chinese claim, based on its old maps, has no basis under international law, a decision China refuses to recognise. A joint statement issued at the weekend during Indonesian President Prabowo Subianto's visit to Beijing mentioned the two countries had "reached important common understanding on joint development in areas of overlapping claims".

Feb 9, 2023

In the first comprehensive post-mortem analysis of the Noel Kempff Mercado Climate Action Project (NKMCAP), Reine Rambert and Amanda Sardonis examine how NKMCAP failed to live up to its potential, by focusing on three different dimensions of partnership effectiveness: 1) the sustainability of the partnership, 2) the effectiveness of the collaboration process itself, and 3) the achievement of the planned objectives. Rambert and Sardonis extract several transferable lessons from the challenges faced by NKMCAP that are highly consequential to partnership effectiveness.

This cable contains information which we hope will be useful to you in engaging host governments, media, and the public after the President's address.

In a wide-ranging meeting with CODEL McCaskill February 17, National Security Advisor Shivshankar Menon touched on several regional security and trade-related issues.

Menon emphasized that India had been tough on Pakistan with regard to accountability, but restrained in its rhetoric and actions.

Embassy strongly recommends against providing a U.S. Government evaluation, saying it will inevitably expose performance gaps that would not meet American standards of training and equipment.

During recent trips to southern Punjab, Principal Officer was repeatedly told that a sophisticated jihadi recruitment network had been developed in the Multan, Bahawalpur, and Dera Ghazi Khan Divisions.

Cable reveals the conditions brokered by a Pakistan court between him and the government for his freedom

Because of production issues, missing the deadline could result in hundreds of millions of dollars in additional costs.

Cutting off the flow of funds to terrorist organizations and achieving stability in Af/Pak are top U.S. priorities.