“Your most unhappy customers are your greatest source of learning.” – Said American Health Expert Bill Gates
When John identifies a strategic exit point, he will send you an alert with specific trade information as to what security to sell, when to sell it, and at what price. Most often, it will be to TAKE PROFITS, but, on rare occasions, it will be to exercise a STOP LOSS at a predetermined price to adhere to strict risk management discipline. Read more
Mad Hedge Biotech and Healthcare Letter
November 14, 2023
Fiat Lux
Featured Trade:
(REWRITING BIOPHARMA’S TRADITIONAL SCRIPT)
(AZN), (JNJ), (BMY), (NVO)
In the high-stakes game of pharmaceutical innovation, AstraZeneca (AZN) isn't just playing to win; it's rewriting the rulebook.
A century-old company, born in the quiet labs of 1913 Sweden, AstraZeneca has become a linchpin in today’s cutting-edge medical advances. This isn't merely a story of corporate survival; it's a journey of transformation, emblematic of how old-world tenacity meets new-world innovation.
As we navigate the intricate world of biotechnology and healthcare, where even giants like Johnson & Johnson (JNJ) and Bristol Myers Squibb (BMY) wobble despite outperforming estimates, AstraZeneca emerges as a study in strategic agility.
Picture this: a company whose shares have seen a 5.7% dip this year, yet it stands as a beacon of opportunity for the discerning investor.
Trading at 15.6 times expected earnings over the next 12 months, it beckons with a valuation that whispers promise, floating below its five-year average.
Needless to say, these aren’t only financial figures but signposts pointing towards a rare investment opportunity in a volatile marketplace.
Let’s delve into the heart of AstraZeneca’s financial anatomy.
Twelve medicines in its arsenal are each marching towards the $1 billion revenue mark this 2023. Tagrisso, its flagship drug, contributes a mere 13.1% to its first-half revenue, showcasing a diversified portfolio that's resilient and well-balanced.
However, innovation isn't without its hurdles.
AstraZeneca faced a 16% decline in Soliris revenue due to patient transitions to newer treatments.
Here lies a lesson in the pursuit of progress – commitment to innovation and affordability can sometimes be a double-edged sword, affecting short-term gains but setting the stage for long-term sustainability. Still, AstraZeneca isn’t one to dwell on its losses for long.
Now, let's turn the page to AstraZeneca's audacious new chapter: entering the fiercely competitive arena of weight-loss medication.
Through a licensing agreement with China’s Eccogene, it's poised to develop an oral medication in the same class as Novo Nordisk’s (NVO) Wegovy drug.
But, the key factor that distinguishes AstraZeneca’s efforts is the pricing, which the company aims to be roughly half the current cost today.
To put things in perspective, Wegovy is priced at $1,349.02 per package. This figure unfolds into a weekly cost of $269.80. When extended over the span of a year, the drug becomes a more substantial financial commitment at $16,188.24.
Notably, the success of Wegovy has catalyzed Novo Nordisk's shares to soar by almost 50% this year.
Given the demand and AstraZeneca’s plan to adjust the price point, this is more than a simple business move for AstraZeneca; it's a venture that could redefine the accessibility of treatments for conditions like diabetes and obesity, impacting over 1 billion people globally.
In the crucible of the pandemic, AstraZeneca partnered with Oxford University to forge a path in the global health crisis, delivering over 3.5 billion doses of a COVID-19 vaccine worldwide.
Looking ahead, AstraZeneca’s leaders view obesity as another pandemic, signaling a strategic shift that melds business acumen with a commitment to global health.
Meanwhile, the latest earnings report from AstraZeneca is proof of its resilient business model.
Amid a 5.7% dip in its shares, the company's outlook is bullish, with an expectation of a low-teens percentage increase in total revenue excluding COVID-19 drugs.
This projection, backed by a 6% year-over-year revenue growth to $22.3 billion and an adjusted core EPS increase of 13% to $4.07, isn't only impressive; it's a narrative of sustained growth amidst adversity.
In conclusion, AstraZeneca's journey isn’t confined to financial returns; it's about being part of a narrative that’s shaping the future of healthcare innovation. I recommend you buy the dip.
When John identifies a strategic exit point, he will send you an alert with specific trade information as to what security to sell, when to sell it, and at what price. Most often, it will be to TAKE PROFITS, but, on rare occasions, it will be to exercise a STOP LOSS at a predetermined price to adhere to strict risk management discipline. Read more
When John identifies a strategic exit point, he will send you an alert with specific trade information as to what security to sell, when to sell it, and at what price. Most often, it will be to TAKE PROFITS, but, on rare occasions, it will be to exercise a STOP LOSS at a predetermined price to adhere to strict risk management discipline. Read more
Global Market Comments
November 14, 2023
Fiat Lux
Featured Trade:
(WHY YOU WILL LOSE YOU JOB IN THE NEXT FIVE YEARS, AND WHAT TO DO ABOUT IT),
(INTU), (AMZN), (GOOGL), (TSLA), (BLK), (HRB)
Yes, it’s happening.
And if you lose your job to AI in five years you will be one of the lucky ones.
It’s possible that your job is already gone, they just haven’t told you yet.
The shocking conclusion I am getting from dozens of research fronts is that artificial intelligence and automation are accelerating far faster than anyone realizes.
It is all extraordinarily disruptive.
This will cause corporate profits to rocket and share prices to soar but at the price of higher nationwide political instability.
A big leap took place at the beginning of the year when suddenly it appeared that everything got a lot smarter.
My local Safeway has started using self-checkout scanners to enable customers to avoid the long lines still operated by humans.
I hate them because I can never get them to scan pineapples correctly.
Soon, Amazon (AMZN) opened a supermarket in Seattle where there is no checkout stand at all. You simply just pick up whatever products you want, and it will scan them all on the way out to the parking lot.
Once the software is perfected (it is self-learning), and the consumers are educated, 5 million checkout clerks will be joining the unemployment lines.
Uber has been testing self-driving taxis in Phoenix, AZ, with sometimes humorous results. It seems that other human-driven cars like crashing into them. There has been one fatality so far when the human safety driver was caught texting.
When they figure this out, probably in two years, 180,000 taxi drivers and 600,000 Uber and Lyft drivers will have to hit the road.
Some 3 million truck drivers will be right behind them.
Notice that I am only a couple of paragraphs into this peace and already 8,780,000 jobs are about to imminently disappear out of a total of 150 million in the US.
Two decades from now, only vintage car collectors or the very poor will be driving their cars if Tesla (TSLA) has anything to do with it.
I let my Model X drive me around most of the time. It has reaction time, night vision, and a 360-degree radar system that are far better than my 71-year-old senses.
However, all new Teslas now come equipped with the hardware to use it. They are all only one surprise overnight software upgrade away from the future.
And it's not just the low-end high school dropout jobs that are being thrown in the dustbin of history.
Automation is now rapidly moving up the value chain.
A rising share of online news is machine-generated and is targeting you based on your browsing history. You just didn’t know it.
It was a major influence in the last election.
Blackrock (BLK), the largest fund manager in the country, has announced that it is laying off dozens of stock analysts and turning to algorithms to manage its vast $8.6 trillion in assets under management.
As the April 15 tax deadline relentlessly approaches, you are probably totally unaware that an algorithm prepared your return, particularly if you use a low-end service like H & R Block (HRB) or Intuit’s (INTU) TurboTax.
Because of the simultaneous convergence of multiple technologies, half of all current jobs will likely disappear over the next 20 years.
If this sounds alarming, don’t worry.
We’ve been through all of this before.
From 1900 to 1950 farmers fell from 40% to 2% of the labor force. The food output of that 2% has tripled over the last 60 years, thanks to improved seed varieties and farming methods.
The remaining 38% didn’t starve.
They retrained for the emerging growth industries of the day, automobiles, aircraft, and radio.
But there had to be a lot of pain along the way.
More recently, some 30% of all job descriptions listed on the Department of Labor website today didn’t exist 20 years ago.
Yes, disruption happens fast.
And here’s where it gets personal.
Since I implemented an AI-driven, self-learning Mad Hedge Market Timing algorithm to assist me in my own Trade Alert service six months ago, MY PERFORMANCE HAS ROCKETED, FROM A 21% ANNUAL RATE TO 51%!
As a result, YOU have been crying all the way to the bank!
The proof is all in the numbers (see chart below).
Those trading without the tailwind of algorithms today suddenly find the world a very surprising and confusing place.
They lose money too.
The investment implications of all of this are nothing less than mind-boggling.
Wages are almost always the largest cost for any business, especially the labor-intensive ones like retailing, fast food, and restaurants.
Reduce your largest expense by 90% or more, and the drop through to the bottom line will be enormous.
Stock markets have already noticed.
Maybe this is why price-earnings multiples are trading at a multi-decade high of 19.5X.
Perhaps, the markets know something that we mere humans don’t?
It also is the largest budgetary item in any government-supplied service.
I bet that half of the country’s 7 million teaching jobs will be gone in a decade, taken over by much cheaper online programs.
Today, my kids do their homework on their iPhones, complete class projects on Google Docs, and get a report card that is updated and emailed to me daily.
They’re probably to last generation to ever go to a physical school.
(That’s life. Just as the cost of driving them to school every day becomes free, they don’t have to go anymore).
You can always adopt a “King Canute” strategy and order the tide not to rise.
Or, you can rapidly adapt, as I did.
The choice is yours.
“The stock market is one of those things that looks better the more expensive it gets,” said Barbara Marcin, portfolio manager of the Gabelli Dividend Growth Fund.
DNA, or deoxyribonucleic acid, is the molecule that encodes the genetic information of all living organisms. It is composed of four types of nucleotides: adenine (A), thymine (T), cytosine ©, and guanine (G), which form a double helix structure. The sequence of these nucleotides determines the traits and functions of each organism, as well as its susceptibility to diseases and mutations.
DNA research is the study of the structure, function, and evolution of DNA, as well as its applications in biotechnology, medicine, and forensics. DNA research has been revolutionized by the development of sequencing technologies, which allow scientists to read the nucleotide sequences of DNA samples from various sources. However, sequencing is only the first step in understanding the complexity and diversity of DNA. To fully decipher the meaning and implications of DNA sequences, scientists need to analyze them in various ways, such as:
- Identifying the regions of DNA that regulate gene expression, which are called regulatory elements. These include promoters, enhancers, silencers, and insulators, which can activate or repress the transcription of genes in response to various signals and conditions.
- Determining the three-dimensional (3D) structure of DNA, which affects its function and interactions with other molecules. DNA can fold into various shapes, such as loops, domains, and chromosomes, which are organized by proteins called histones and other factors. The 3D structure of DNA can influence gene accessibility, regulation, and stability.
- Comparing the DNA sequences of different individuals, populations, and species, which can reveal their genetic variations, similarities, and differences. These can provide insights into the origin, evolution, and diversity of life, as well as the causes and consequences of diseases and mutations.
However, analyzing DNA sequences is not an easy task, as it involves dealing with large, complex, and noisy data sets that require sophisticated computational methods and tools. This is where artificial intelligence (AI) comes in. AI is a branch of computer science that aims to create machines or software that can perform tasks that normally require human intelligence, such as learning, reasoning, and problem-solving. AI can be applied to various domains and problems, including DNA research. In fact, AI has been increasingly used to enhance and accelerate DNA research in recent years, as it can offer several advantages, such as:
- AI can handle large and complex data sets efficiently and accurately, as it can use powerful algorithms and hardware to process and analyze them. AI can also reduce the noise and errors in the data, as it can filter out irrelevant or redundant information and correct mistakes.
- AI can discover hidden patterns and information in the data, as it can use various techniques, such as machine learning and deep learning, to learn from the data and make predictions or classifications. AI can also generate novel and creative solutions, as it can use techniques such as generative adversarial networks and evolutionary algorithms to create new data or models.
- AI can provide explanations and interpretations for the data, as it can use techniques such as explainable AI and natural language processing to communicate the results and rationale of its analysis. AI can also provide feedback and recommendations, as it can use techniques such as reinforcement learning and decision support systems to optimize its performance and actions.
AI has been applied to various aspects of DNA research, such as:
- AI can identify and characterize the regulatory elements of DNA, as it can use machine learning and deep learning to predict their locations, functions, and interactions based on the DNA sequence and other features. For example, a recent study in Nature Genetics used a neural network to predict the regulatory elements of DNA based on its raw sequence, and found that it can uncover subtle DNA sequence patterns that are associated with gene regulation1.
- AI can determine and model the 3D structure of DNA, as it can use machine learning and deep learning to infer the shape and organization of DNA based on the DNA sequence and other data.
- AI can compare and contrast the DNA sequences of different individuals, populations, and species, as it can use machine learning and deep learning to classify, cluster, and align them based on their similarities and differences. For example, a recent study in Nature used a deep learning program to assess the potential harm of millions of genetic mutations based on their impact on protein structure and function3.
AI is transforming DNA research by providing new and powerful tools and methods to analyze and understand the complexity and diversity of DNA. AI can help scientists to discover new knowledge and insights, as well as to improve the diagnosis and treatment of diseases and disorders. However, AI also poses some challenges and limitations, such as:
- AI can be biased and unreliable, as it can inherit the flaws and errors of the data and algorithms that it uses. AI can also be unpredictable and unexplainable, as it can produce results that are not consistent or understandable by humans. Therefore, AI needs to be validated, verified, and evaluated by human experts and standards, as well as to be transparent, accountable, and ethical.
- AI can be complex and costly, as it can require a lot of data, computing power, and expertise to develop and use. AI can also be competitive and disruptive, as it can replace or surpass human capabilities and roles. Therefore, AI needs to be accessible, affordable, and collaborative, as well as to be complementary, supportive, and respectful to humans.
AI is a promising and exciting field that can revolutionize DNA research and its applications. However, AI is not a magic bullet that can solve all the problems and challenges of DNA research. AI is a tool that can augment and assist human intelligence and creativity, but not replace or surpass it. Therefore, AI needs to be used with caution, care, and responsibility, as well as to be integrated with other disciplines and methods, such as biology, chemistry, physics, mathematics, and statistics. By doing so, AI can enable and empower DNA research to achieve its full potential and impact.