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Snoop Dogg’s Casa Verde gets into the sleep space, backing NY-based Proper

Snoop Dogg’s Casa Verde gets into the sleep space, backing NY-based Proper

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Helping Americans get their forty winks has never been more necessary as the country faces what some health experts have called a sleep epidemic, and Snoop Dogg’s cannabis-focused firm Casa Verde Capital wants to help.

The firm is leading a $9.5 million investment into a company called Proper, which is launching with a combination of sleep coaching and supplements, pitching a “holistic” sleep health solution.

One-third of US adults don’t get enough sleep according to Proper’s estimates, and the company’s chief executive, Nancy Ramamurthi, says that the COVID-19 epidemic has only made the problem worse.

“Proper aims to help solve what the CDC has identified as a public health crisis – insufficient sleep — with a truly more holistic and personalized solution,” said Ramamurthi, founder and CEO of Proper, in a statement. “Proper has combined the best of natural, safe, evidence-based sleep supplements with expert behavioral coaching, which consumers have not traditionally been able to access. Now, thanks to the increasing popularity of telehealth, sleep coaching can be delivered online.”

The sleep coaching services from Proper are provided by board-certified health and wellness coaches under the guidance of a clinical psychologist and behavioral sleep medicine specialist, according to a statement from the company.

Ramamurthi said that clinical validation is a core component of the company’s business. Indeed, the company is currently running its formulations through a clinical trial to prove their efficacy. It’s an additional step that the company doesn’t need to take, she said, because the supplements have all been studied with clinical trials supporting the use of the ingredients as treatments for sleep therapy. “That’s in addition to them being used for thousands of years,” said Ramamurthi.

Proper was incubated within the consumer health venture studio Redesign Health and will use the new capital from investors led by Snoop Dogg’s Casa Verde to boost its sales and marketing efforts and continue its research and development activities.

While sleep aids may seem like a strange market for a cannabis-focused investment firm, Casa Verde partner Karan Wadhera says it’s a highly strategic investment for the firm.

[Cannabis] is an input as well and its use case will go beyond how people think of cannabis stigmatically,” Wadhera said. “At its core, [Proper] is a company that’s helping us target this sleep epidemic. We think CBD and cannabis at large can play a big role in addressing that in a way that traditional products haven’t been able to.”

The investment in Proper, then, points to a maturation of the cannabis industry, as investors look at the various chemical components of the cannabis plant and try to tease out a broader range of health and wellness applications. “We are starting to shift how we think about the business. It doesn’t have to be a core, specific cannabis product,” Wadhera said. 

Ramamurthi says that her company will be exploring applications for cannabinoids in its supplements later. “As we continue our product development process one of the things we are looking at is CBD,” she said. “CBD is one of the more effective ingredients at reducing stress and anxiety and stress and anxiety are one of the main reasons why people can’t get to sleep.”

Proper’s studies are supported by a scientific advisory board that includes Dr. Adam Perlman, the director of integrative health and wellbeing at the Mayo Clinic, and Dr. Allison Siebern, a clinical psychologist and board-certified sleep medicine specialist at the VA Medical Center in North Carolina.

There’s a reason why sleep is so poorly understood and ignored as a health issue in America. Around 90 percent of primary care physicians rate their understanding of sleep’s impact on the body as “poor to fair” and there’s only one board-certified sleep specialist for every 43,000 Americans, according to Proper’s data.

Customers who sign up for Proper’s service can select one of five sleep formulations available for $39.99 per bottle or for a subscription with a ten percent discount. New users also get a free 30-minute consultation with a Proper sleep coach, the company said.

The five versions of Proper’s sleep products include a core sleep product made from GABA, valerian root extract, rafuma leaf extract, and ashwagandha root and leaf extract; a sleep and restore product that includes melatonin; a calming pill with L-theanine added to the core sleep product; and a clarity product that includes concentrated grape extracts; and, finally, an immunity product with added zinc, vitamin C, B6, and D.

 

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John Lewis relies too heavily on its heritage – here’s what it could do instead

The company has returned to profit by making cuts, but there are things it could do to reinvent itself.

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Road to recovery? Jevanto Productions/Shutterstock

In a tricky economic climate, the British department store John Lewis has managed to deliver some good news. The retail partnership – owned by its 80,000 employees – posted pre-tax profits of £56 million after a £234 million loss the year before.

The positive announcement was somewhat tarnished by the fact that those employees (known as partners) would not receive a bonus for the second year in a row. There were also hints of job cuts.

But what more could this giant of UK retail, which also owns Waitrose supermarkets, do to endure its survival? Does its increasing reliance on grocery sales mean its own brand has become less valuable?

For over 160 years on the high street, John Lewis has worked hard on that brand. Its slogan (scrapped in 2022) about being “never knowingly undersold” was well known, it remains a trusted supplier of an extensive range of household hoods, rates highly for customer service, and runs Christmas TV adverts which have became a media event in themselves.

In doing all of those things, John Lewis seemed to be in a much better place than its rivals. BHS (founded in 1928) and Debenhams (1778) have disappeared from the high street. House of Fraser (1849) was taken over and has a much-reduced physical presence.

John Lewis’s nearest rival, Marks & Spencer (1884), is now doing well, but only after it underwent a fairly brutal restructuring which involved cutting thousands of jobs during the pandemic, closing 67 stores, and slashing its operations in France.

So John Lewis’s “brand heritage” – its history, tradition and pedigree – has worked pretty well for a pretty long time. But its recent return to profit was the combined effort of reinvesting and streamlining, according to some reports.

Also known as “trimming the fat” in the business world, the retailer’s streamlining endeavours consisted of cutting more than 1,500 jobs, and closing underperforming stores, such as the branch in Sheffield, which had served residents for nearly 80 years and was much mourned, including by my own mother-in-law.

It has also been reported that more job cuts are imminent, with up to 11,000 jobs to go in the next five years.

And perhaps these measures highlight some of the harsh realities of running a department store in the always-open and effortless world of online shopping. Maybe employees (even those considered partners, as under John Lewis’s employee-ownership model) have become expendable.

Maybe physical stores, where consumers go to explore and seek advice, have become expendable. Maybe all traditions are expendable when they are not commercially viable.

People first

Yet the world of retail is filled with examples of heritage brands reinventing themselves to stay relevant, buoyant and competitive.

John Lewis will need to do the same if it wants to retain its legacy on the British high street. And it could do worse than taking a leaf out of Waitrose’s playbook.

For the company’s return to profit was largely due to the buoyant sales generated by Waitrose supermarkets, which increased by 4%. The department store business meanwhile, suffered a 2% fall.

Part of Waitrose’s success comes from providing a sense of indulgence and enjoyment – including healthy food – through carefully curated and often locally sourced products. It works closely with local farmers, supports regional suppliers (an approach that has also contributed to M&S’s success), and reinvests in stores and product offers.

Essentially, as part of UK’s grocery sector, Waitrose extended its partnership ethos to include people and groups beyond the shop walls – to build a “local retail ecosystem” that promotes and leverages a community spirit around their stores.

M&S shop front.
Appealing to appetites. Simon Vayro/Shutterstock

John Lewis department stores could try and do something similar. They could focus more on products that help customers live healthier and more active lives, and which are relevant to their interests. They could sell products created by local small businesses, and make a determined approach to be a supportive presence in the regions they serve.

Research suggests that heritage brands benefit from having a moral standing – when they show they care about the people they make money from, the local communities they operate in, and the people they employ.

So perhaps John Lewis should make moral values a part of its evolving heritage. It needs to show it cares not just for the people who work for the company directly, but also the people on whom it relies for success – the customers – and people it can build new relationships with. All of them could prove critical to its future success.

Kokho Jason Sit is affiliated with the Chartered Institute of Marketing.

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“Are you better off than you were four years ago?”

  – by New Deal democratNo economic news today, so let me take a look at the supposed killer recent GOP meme that they claim is completely unanswerable:…

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 - by New Deal democrat


No economic news today, so let me take a look at the supposed killer recent GOP meme that they claim is completely unanswerable: “Are you better off today than you were four years ago?”


This is based primarily on consumer sentiment reading as well as polling that has consistently shown that most people think that the economy is poor, even though they rate their own situation as doing well. Dan Guild has a model comparing consumer sentiment with Presidential approval ratings. He concludes that Biden will lose re-election unless consumer sentiment as measured by the University of Michigan does not improve to the index level of 82.

As I’ve pointed out in the past, Presidential approval correlates quite well with the price of gas. Here’s the historical record updated through last month:



Except for those periods late in recessions and shortly thereafter, when the price of gas has typically declined sharply but the unemployment rate is very high, generally speaking, the lower the cost of gas, the higher the consumer sentiment. Interestingly, except for the early part of the 1990s, when gas prices were ridiculously low, the correlation holds better nominally than adjusted for income.

But perceptions aside, are most people in fact worse off than 4 years ago? Here are two ways of looking at that.

First, as I noted several months ago, Motio Research has produced very good monthly estimates of median household income, that track very well with the (unfortunately) annual measure, which is only reported in September of the next year (thus, for example, the most recent official report even now is for the year 2022). Here’s their update through February:



Note that they recommend (in the small print at the bottom) ignoring the results from March through October 2020, when response rates were very skewed. Leaving those out, only three months during Trump’s term were better than the current reading, and two of those, at 112.7, were equaled by January’s reading. Only February 2020 scored higher, at 112.9.

A second way of measuring is to compare real average and aggregate wages. Below I show average hourly wages (blue), average weekly wages (red), and aggregate payrolls divided by population (black), all deflated by the CPI, and normed to 100 as of February 2020:



Most of the surge in average hourly and weekly earnings in 2020 and early 2021 were compositional. That is, most of the workers laid off during the worst of the pandemic were low wage service workers, in places like restaurants, bars, and entertainment venues. When those workers were rehired during 2021 and 2022, the averages went down, with a very big assist from gas prices spiking to $5/gallon. Since then, both measures have exceeded their levels from just before the pandemic.

Aggregate payrolls, even divided by population, and so including everyone who is not working, and not even in the labor force, hit their pre-pandemic level late in 2021 and haven’t looked back. They are *not* affected by compositional issues. And they are currently 2.9% higher, even on this per capita basis, than they were just before the pandemic.

So the truthful answer for most people to “Are you better off than you were four years ago?” is by any reasonable measure, “Yes.”

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AI can help predict whether a patient will respond to specific tuberculosis treatments, paving way for personalized care

People have been battling tuberculosis for thousands of years, and drug-resistant strains are on the rise. Analyzing large datasets with AI can help humanity…

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Tuberculosis typically infects the lungs but can spread to the rest of the body. stockdevil/iStock via Getty Images Plus

Tuberculosis is the world’s deadliest bacterial infection. It afflicted over 10 million people and took 1.3 million lives in 2022. These numbers are predicted to increase dramatically because of the spread of multidrug-resistant TB.

Why does one TB patient recover from the infection while another succumbs? And why does one drug work in one patient but not another, even if they have the same disease?

People have been battling TB for millennia. For example, researchers have found Egyptian mummies from 2400 BCE that show signs of TB. While TB infections occur worldwide, the countries with the highest number of multidrug-resistant TB cases are Ukraine, Moldova, Belarus and Russia.

The COVID-19 pandemic set back progress in addressing many health conditions, including TB.

Researchers predict that the ongoing war in Ukraine will result in an increase in multidrug-resistant TB cases because of health care disruptions. Additionally, the COVID-19 pandemic reduced access to TB diagnosis and treatment, reversing decades of progress worldwide.

Rapidly and holistically analyzing available medical data can help optimize treatments for each patient and reduce drug resistance. In our recently published research, my team and I describe a new AI tool we developed that uses worldwide patient data to guide more personalized and effective treatment of TB.

Predicting success or failure

My team and I wanted to identify what variables can predict how a patient responds to TB treatment. So we analyzed more than 200 types of clinical test results, medical imaging and drug prescriptions from over 5,000 TB patients in 10 countries. We examined demographic information such as age and gender, prior treatment history and whether patients had other conditions. Finally, we also analyzed data on various TB strains, such as what drugs the pathogen is resistant to and what genetic mutations the pathogen had.

Looking at enormous datasets like these can be overwhelming. Even most existing AI tools have had difficulty analyzing large datasets. Prior studies using AI have focused on a single data type – such as imaging or age alone – and had limited success predicting TB treatment outcomes.

We used an approach to AI that allowed us to analyze a large and diverse number of variables simultaneously and identify their relationship to TB outcomes. Our AI model was transparent, meaning we can see through its inner workings to identify the most meaningful clinical features. It was also multimodal, meaning it could interpret different types of data at the same time.

Microscopy image of rod-shaped TB bacteria stained green
Mycobacterium tuberculosis spreads through aerosol droplets. NIAID/NIH via Flickr

Once we trained our AI model on the dataset, we found that it could predict treatment prognosis with 83% accuracy on newer, unseen patient data and outperform existing AI models. In other words, we could feed a new patient’s information into the model and the AI would determine whether a specific type of treatment will either succeed or fail.

We observed that clinical features related to nutrition, particularly lower BMI, are associated with treatment failure. This supports the use of interventions to improve nourishment, as TB is typically more prevalent in undernourished populations.

We also found that certain drug combinations worked better in patients with certain types of drug-resistant infections but not others, leading to treatment failure. Combining drugs that are synergistic, meaning they enhance each other’s potency in the lab, could result in better outcomes. Given the complex environment in the body compared with conditions in the lab, it has so far been unclear whether synergistic relationships between drugs in the lab hold up in the clinic. Our results suggest that using AI to weed out antagonistic drugs, or drugs that inhibit or counteract each other, early in the drug discovery process can avoid treatment failures down the line.

Ending TB with the help of AI

Our findings may help researchers and clinicians meet the World Health Organization’s goal to end TB by 2035, by highlighting the relative importance of different types of clinical data. This can help prioritize public health efforts to mitigate TB.

While the performance of our AI tool is promising, it isn’t perfect in every case, and more training is needed before it can be used in the clinic. Demographic diversity can be high within a country and may even vary between hospitals. We are working to make this tool more generalizable across regions.

Our goal is to eventually tailor our AI model to identify drug regimens suitable for individuals with certain conditions. Instead of a one-size-fits-all treatment approach, we hope that studying multiple types of data can help physicians personalize treatments for each patient to provide the best outcomes.

Sriram Chandrasekaran receives funding from the US National Institutes of Health.

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