Dear New World Investor:

This week I want to review some TechBio companies applying Artificial Intelligence (AI) and Machine Learning (ML) to biotech. These are speculative positions, and I haven’t done enough work to recommend one yet, but this is going to be a HUGE investment theme for the next decade.

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Notes: “Growth Flow” is total R&D spending for the last 5 years (2023 estimated) divided by fully-diluted shares. Px/GF is a way to value development-stage technology companies.
“Runway (#Q)” is the number of quarters a company’s current cash will last at their current burn rate. CFOs rarely let the runway get under 2 quarters.

First, some definitions and use cases. Artificial Intelligence (AI) refers to the broader field of computer science that aims to create machines or systems that can perform tasks typically requiring human intelligence. These tasks may include problem-solving, decision-making, understanding natural language, and more. One of the biggest advantages of applying AI to biotech drug discovery is the sheer speed it offers in organizing, analyzing, and correlating data.

Machine Learning (ML) is a subset of AI that focuses on the development of algorithms and models that enable computers to learn and make predictions or decisions from data without being explicitly programmed. ML algorithms improve their performance through experience and data, which usually means the more data you can assemble or – better yet – generate, the more accurate your AI can be.

Deep Machine Learning, usually referred to as Deep Learning (DL), is a specialized branch of ML that uses neural networks with multiple layers (deep neural networks) to process and analyze data. Deep learning has been particularly successful in tasks like image and speech recognition, natural language processing, and reinforcement learning.

AI, ML, and DL have significant applications in biotech drug discovery, revolutionizing the process by making it more efficient, cost-effective, and accurate. They can be applied for:

1. Target Identification and Validation:
AI-based Predictive Models: AI can analyze biological data to identify potential drug targets by predicting their relevance to a disease.
Natural Language Processing (NLP): ML-driven NLP techniques can extract valuable information from scientific literature, patents, and clinical trial data to validate potential targets.

2. Drug Screening:
High-Throughput Screening (HTS): ML algorithms can analyze HTS data to identify compounds with the highest probability of binding to a specific target.
Virtual Screening: DL models can simulate the interaction between drug candidates and target proteins to predict their binding affinity, saving pre-clinical time and resources.

3. Drug Design:
Generative Models: DL-based generative models can design novel drug-like molecules with desired properties, such as high binding affinity and low toxicity.
Quantum Machine Learning: Quantum ML can optimize molecular structures and predict their properties, enabling the design of more effective drugs.

4. Clinical Trial Optimization:
Patient Recruitment: AI can analyze patient data to identify suitable candidates for clinical trials, increasing recruitment efficiency.
Predictive Analytics: ML models can predict patient responses to treatment, helping optimize trial protocols and reduce costs.

5. Drug Repurposing:
Data Mining: AI can analyze large datasets to identify existing drugs with potential new uses or applications in different diseases.
Network Analysis: DL models can analyze complex biological networks to discover connections between drugs and diseases.

6. Drug Manufacturing:
Quality Control: AI-driven image analysis can enhance quality control in drug manufacturing by detecting defects and ensuring product consistency.
Process Optimization: ML can optimize manufacturing processes to improve yield and reduce production costs.

7. Personalized Medicine:
Genomic Medicine: AI can analyze a patient’s genetic data to tailor drug therapies for maximum effectiveness and minimal side effects.
Pharmacogenomics: ML models can predict how an individual will respond to a specific drug based on their genetic profile.

8. Drug Safety and Pharmacovigilance:
Adverse Event Detection: ML can analyze real-world data, such as electronic health records, to detect and assess adverse drug reactions.
Signal Detection: AI can identify potential safety signals early in the drug development process.

Incorporating AI, ML, and DL into drug discovery not only accelerates the process but also enhances the likelihood of discovering innovative therapies while reducing costs and the risk of failure. All biotechs will use these technologies to advance drug research. Many or most of the larger companies probably will develop their own, but the TechBios will develop and sell tools to the rest of the industry. In the early days, even the big companies will reach out for leading-edge tools.

AbCellera (ABCL) uses AI, ML, and DL to streamline and enhance various aspects of the antibody drug discovery and development process. They uses AI-driven high-throughput screening to rapidly analyze large libraries of antibody candidates. ML algorithms help identify potential therapeutic antibodies by predicting their binding affinity to target proteins.

The company uses Deep Learning models to analyze vast amounts of sequencing data generated during antibody discovery. These models can identify key sequence features associated with antibody functionality and therapeutic potential. The use ML algorithms to integrates data from multiple ‘omics’ sources (genomics, proteomics, transcriptomics) to help identify and prioritize potential drug targets and leads. ML also analyzes immune repertoires and identifies rare antibodies with unique properties that can become novel drug candidates.

They use AI-driven computational methods to design and engineer antibodies with improved properties, such as higher binding affinity and reduced immunogenicity. Then they use both AI and ML to analyze patient data, including clinical and genetic information, to identify potential patient-specific treatment options. This supports personalized medicine approaches.

AbCellera’s strategy is to use their techbio skills to partner with bigger companies in return for financial support and, usually, a small royalty on any successful drugs. In the June quarter conference call (SLIDES HERE and TRANSCRIPT HERE), they said they’ve had 177 programs under contract and have started work on 106 of them. They have nine molecules in the clinic:

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Absci (ABSI) specializes in synthetic biology (“The Google of Synthetic Biology”) and protein expression technologies. AI and ML can be used to design and engineer proteins with specific properties, such as increased stability, improved binding affinity, or reduced immunogenicity. These engineered proteins can be potential drug candidates. ML can analyze biological data to identify potential protein drug targets associated with diseases to guide drug discovery efforts.

In their Introduction to Absci & AI Drug Discovery presentation (SLIDES HERE) and July Corporate Presentation (SLIDES HERE), they say instead of finding the needle in the haystack, Absci is creating the needle.

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If you are interested, they are presenting at the H.C. Wainwright Global Investment Conference on September 11 at 2:00pm EDT, the Morgan Stanley Global Healthcare Conference on September 13 at 7:30am EDT, and the Cantor Fitzgerald Global Healthcare Conference on September 26 at 8:10am EDT.

Exscienta (EXAI) is a drug discovery company with expertise in applying AI and ML to accelerate and optimize the drug discovery process. They integrates a wide range of data sources, including biological, chemical, and clinical data, to create comprehensive datasets for analysis and model development. They were the first company to get AI-designed drugs into clinical trials. They uses AI algorithms to analyze High-Throughput Screening biological data more efficiently, including genomics and proteomics, to identify active compounds and potential drug targets faster. Then ML models can help prioritize these targets based on their relevance to specific diseases.

AI-driven generative models design and generate novel small molecules with desired properties, such as high binding affinity and low toxicity, for specific drug targets. Then ML algorithms are applied to optimize drug candidates based on multiple parameters, including efficacy, safety, pharmacokinetics, and to predict the binding affinity of drug candidates to target proteins. This virtual screening approach identifies promising compounds for further development, reducing the need for extensive laboratory testing.

AI and ML are used to optimize clinical trial designs, including patient stratification and dosing regimens, to increase the chances of successful trials and accelerate drug development.

Their excellent Corporate Presentation is HERE.

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They will be presenting at the Morgan Stanley Global Healthcare Conference on September 12 at 8:10am.

Relay Pharmaceuticals (RLAY) applies AI and ML to structure-based drug design. Their platform integrates computational and experimental approaches to accelerate the discovery of novel therapeutics. They predict the 3D structures of target proteins and drug candidates to understanding the binding interactions between proteins and potential drugs.

AI-driven virtual screening uses computational models to simulate the binding of drug candidates to target proteins. ML algorithms prioritize compounds based on their predicted binding affinity and interaction patterns. Then they can design and optimize novel compound structures with desired properties or modify existing molecules for improved efficacy and safety.

ML algorithms can analyze biophysical data, such as X-ray crystallography and cryo-electron microscopy, to extract valuable insights about protein structures and their dynamics that aids in rational drug design. AI, can analyze the interactions between drugs and their target proteins at the atomic level, helping to design drugs with high specificity and minimal off-target effects.

On their Corporate Presentation (HERE), they define themselves as a clinical-stage precision medicines company transforming the drug discovery process by combining leading-edge computational and experimental technologies with the goal of bringing life-changing therapies to patients. Their Dynamo platform integrates an array of leading-edge computational and experimental approaches designed to drug protein targets that have previously been intractable. Their initial focus is on enhancing small molecule therapeutic discovery in targeted oncology and genetic disease.

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Recursion Pharmaceuticals (RXRX) just got a $50 million investment from Nvidia, the leading AI semiconductor company. I first recommended Nvidia stock in 2000 and continue to recommend it in Boomberg. Recursion’s platform combines AI-driven automation, cellular imaging, and data analysis to identify potential drug candidates for a wide range of diseases. Automated cellular imaging systems capture detailed images of cells and tissues treated with various compounds. These images are used to create a very large, proprietary dataset.

AI and ML then rapidly analyze these large-scale biological data and cellular responses to identify potential drug candidates and gain insights into disease mechanisms. Their approach is aimed at accelerating the drug discovery process and uncovering novel therapeutic opportunities.

ML algorithms are applied to analyze the cellular images and extract relevant features. These features may include cell morphology, changes in protein expression, and other cellular responses to drug compounds. Then they build disease models in vitro using cells and tissues to simulate various diseases. ML models analyze the phenotypic changes induced by different compounds, helping to identify potential drug candidates. Recursion maintains extensive libraries of cellular images and data, which can be used to screen and identify compounds with therapeutic potential across a wide range of diseases.

ML models predict the efficacy, safety, and mechanism of action of potential drug candidates to prioritize compounds for further testing and development. AI and ML can identify patient subpopulations that are most likely to respond to specific treatments, enabling personalized medicine approaches.

Take a look at their very detailed, 92-page Corporate Deck HERE.

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Schrödinger (SDGR) is a leading computational chemistry and drug discovery software company that has been at the forefront of applying AI and ML to accelerate drug discovery processes. They primarily sell physics-based computational software, which can be a great business – they have about 1,750 customers – but also have 19 drug development programs that, as we all know, potentially is a risky money pit.

Their software uses ML algorithms to improve molecular dynamics simulations and quantum mechanics calculations. This enables researchers to gain a deeper understanding of the interactions between molecules and target proteins, leading to more accurate predictions of binding affinities and drug behavior. Their software platform include AI-driven tools for designing and optimizing drug-like compounds. ML models assist in generating novel molecular structures that are more likely to be effective as drug candidates.

ML techniques are used to create predictive models for virtual screening, allowing researchers to identify potential drug candidates from large compound libraries based on their likelihood of binding to a target protein. AI and ML help develop pharmacophore models that describe the essential features a molecule must have to interact with a specific target. These models guide the design of new compounds. Schrödinger’s software incorporates AI and ML models for predicting the pharmacokinetic and toxicity profiles of drug candidates. This aids in selecting compounds with favorable properties for further development.

Schrödinger’s software suite includes tools for structure-based drug design, which utilize AI and ML to optimize the binding of drug candidates to their target proteins. They integrate diverse biological and chemical data sources, allowing researchers to create comprehensive datasets for analysis and model development.

The June quarter slides (HERE) show their balanced business model:

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Market Outlook

The S&P 500 lost 1.3% since last Thursday as investors worried the economy is too strong. The Index is up 15.9% year-to-date. The Nasdaq Composite lost 2.0% and is up 31.3% for the year. The small-cap Russell 2000 dropped 2.3% and is up 5.4% in 2023.

The fractal dimension is approaching full consolidation. Historically, September is a tough month for the market, so I expect the fractals to be fully consolidated by the end of the month.

Top 5

Changes this week: None

Near-Term – chronological order
TGTX TG Therapeutics – Rapid recovery from overdone pullback
EQT EQT –natural gas price rebound
USL United States 12 Month Oil Fund, LP – crude should rise quickly
FCX Freeport McMoRan – copper shortage this fall
SFTBY SoftBank – for ARM IPO this fall
AKBA Akebia – Vadadustat NDA filing 2023; approval 2024
VLD Velo3D – Rapid revenue growth; low market cap

Long-Term – alphabetical order
EQT EQT – largest US natural gas company
GBTC Grayscale Bitcoin Trust – Bitcoin is headed for $100,000
NVTA Invitae – the winner-take-most of genetic testing
META Meta – a (the?) leader in the metaverse
RKLB Rocket Lab – #2 to SpaceX in space
SCYX ScyNexis –First new antifungal in 20 years
VLD Velo3D – Return manufacturing to the US

Economy

The Atlanta Fed’s GDPNow model for September quarter real GDP is still at +5.6%. The economy is running hot, in part due to some large one-offs like “Barbenheimer,” Taylor Swift’s “The Eras” tour, and Beyoncé’s “Renaissance” tour.

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But it’s about to cool quickly as student loan payments restart and credit cards are maxed out. There are signs that wage growth and inflation may soon slow further. The Fed’s Beige Book revealed yesterday that businesses in several districts struggled during August to pass on costs to consumers, as costs of making goods are growing faster than prices. Most districts reported price growth slowed overall, decelerating faster specifically in manufacturing and consumer goods sectors.

Last Friday we got August payroll growth of +187,000, a bit above the +170,000 expected. But payroll growth for June was revised down by 80,000, from +185,000 to +105,000, and the change for July was revised down by 30,000, from +187,000 to +157,000. With these revisions, employment in June and July combined was a whopping 110,000 lower than previously reported. Job creation for the last three months has averaged 150,000. During 2022, the average number of new jobs created each month was 400,000.

The revisions are so large it’s almost funny that the first estimate can move markets.

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On September 13 we get the August Consumer Price Index, the last data point before the Fed’s next meeting announcement on September 20. The Cleveland Fed updated their inflation nowcast, and the August CPI is now projected at +0.79% month-over-month, pushing the year-over-year to 3.82%. September CPI is now projected at 0.45% MoM, pushing the YoY to 3.91%. Driving this has been the rise in gasoline prices.

The Cleveland Fed has overstated CPI in recent months by 0.1% or 0.2%. Even factoring in an overstate again, August and September CPI are looking at relatively large numbers. YoY CPI bottomed at 3.0% in June. If YoY CPI is pushing 4.0% by September (reported in mid-October), a pause is the best we’ll get. Any 2024 rate cut is out of the question.

Wall Street’s total confusion over the direction of inflation was on display Wednesday on the Yahoo Finance home page.

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The Fed has reduced its balance sheet by running off $1 trillion in debt with little impact on markets.

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The Fed is letting up to $60 billion of Treasuries and $35 billion of mortgage-backed debt mature each month without replacement. Money-market funds and other buyers have been happy to snap up the slew of Treasury bills Washington has been offering to fund the monster deficits. If I’m right and it’s “Not Much Higher, But For Much Longer,” stocks of companies that execute well will be the only winners.

Coming Events
All times below are ET, and most presentations and slides are archived on the companies’ websites so you can listen to them.

Monday, September 11
AG – First Majestic – Through 9/13 – H.C. Wainwright Global Investment Conference
AKBA – Akebia – 9:30am – H.C. Wainwright Global Investment Conference
TGTX – TG Therapeutics – 10:30am – H.C. Wainwright Global Investment Conference
APTO – Aptose Therapeutics – 2:00pm – H.C. Wainwright Global Investment Conference
CMPS – Compass Pathways – 3:30pm – H.C. Wainwright Global Investment Conference

Tuesday, September 12
QUIK – QuickLogic – Unspec – H.C. Wainwright Global Investment Conference
CMPS – Compass Pathways – 1on1s – Morgan Stanley Global Healthcare Conference
SCYX – ScyNexis – 9:00am – H.C. Wainwright Global Investment Conference
AAPL – Apple – 1:00pm – iPhone 15 introduction
Short Interest – After the close
INO – Inovio – 4:30pm – H.C. Wainwright Global Investment Conference

Wednesday, September 13
SFTBY – SoftBank – Before the open – ARM plc IPO
ENVX – Enovix – Unspec – Podcast launch
Consumer Price Index – 8:30am
MDNA – Medicenna – 2:30pm – H.C. Wainwright Global Investment Conference
FSLY – Fastly – 3:00pm – Piper Sandler Growth Frontiers Conference

Thursday, September 14
ENVX – Enovix – 2:05pm – Morgan Stanley Laguna Conference

Big Tech: The Biotech & Digital Dominators MegaShift
There are at least four ways to make money in the stocks of these large, growing, dominant companies. You can:
* * Buy a stock and hold it
* * Buy a stock and write a call option against it
* * With a Level IV options account, write an out-of-the-money put option
* * With a Level IV options account, write an out-of-the-money put option and use part of the premium to buy an out-of-the-money call option

Last week, bullish investors poured money into tech stocks for the 10^th straight week, the longest streak in two years BofA Global Research said, while US Treasuries are set for their worst yearly performance since the Declaration of Independence. There were a net $10.3 billion of inflows into equity funds in the week to Wednesday, August 30, with investors putting $5.1 billion into tech stocks, the most since May, and $4.9 billion into emerging market stocks.

Apple (AAPL – $177.56) was hit this week as the Chinese government said government employees can’t use their iPhones at work. Thus making them even more desirable after hours? And for non-government employees?

According to the ARM plc prospectus, Apple signed a licensing agreement with ARM that “extends beyond 2040.” That’s no surprise – Apple was one of the initial companies that partnered to found ARM in 1990, before the release of its Newton handheld computer in 1993, which used an Arm-based processor. They use ARM’s technology to design the custom chips for iPhones, iPads and Macs.

Also, Apple is taking a fair-sized chunk of the IPO next week. AAPL is a Buy under $150 for new iPhone rollouts and augmented/virtual reality products.

Corning (GLW – $31.52) EVP & Chief Strategy Officer Dr. Jeffrey Evenson did a fireside chat at the Citi Global Technology Conference (TRANSCRIPT HERE). Replying to the question of how Corning copes with widespread consumer weakness, he said: “Yes, three of our five segments have some significant consumer focus. I’ll start with automotive. There are two parts to what we are doing. Both of them support $100 per car opportunities for Corning, which is significantly higher than our opportunity historically. So one way we get growth is we deliver on those opportunities.

“The big opportunities for us right now are gas particulate filters, which are continuing to be implemented around the world and continuing to require higher performance to meet evolving regulations. Most recently, in the second quarter, we saw some good growth in that business as China rolls out a new round of regulations that require a higher level of filtration.

“Gas particulate filters are also really important for hybrid vehicles because the on/off process between the electric and gas engines actually emit more particulate matter. So it’s usually a larger and more technical filter, which means we have opportunities to add more value.

“The other way that we are pursuing automotive is through our advanced glass. Historically, the glass industry has utilized glasses that were invented for architecture or something else and figured out how to use them in the automotive space. We’ve stepped back and thought about the real needs of customers in that space on both the interior and the exterior.

“On the interior, we are delivering thin, tough glass that meets the head impact tests without further reinforcement behind it, and it can take on curve shapes that are necessary for the interior vehicle without using additional heat. So it’s a cheaper, greener alternative to what people have been doing and plays on to the design characteristics of the car as well as the functional characteristics that you need for modern controls and over-the-air software updates.

“We are also working on some really exciting exterior opportunities that cut down noise in electric vehicles and better protect the sensors for autonomous vehicles.

“So in automotive, it will be great when the auto market starts to grow again, but I think we are pursuing some pretty powerful S-curves that allow us to do a little bit better than that growth overall.

“Similar stories for our other two segments that are consumer-facing. In display, the trend is toward larger TVs and higher resolutions. Our glass is critical in making that happen…And then our third business that has consumer exposure is mobile consumer electronics, where we sell Gorilla Glass and glass ceramics to the world’s leading flagship phone providers…And we have a couple of exciting products coming out in the next six to eight months. And we look forward to the benefits of those in our sales.”

GLW is a Buy under $33 for the 5G cellular buildout, followed by the smartphone upgrade to use 5G services. My target is $60 in 2024.

Gilead Sciences (GILD – $73.94) did a fireside presentation at the Wells Fargo Healthcare Conference (TRANSCRIPT HERE). CFO Andrew Dickinson said for HIV: “We have the flagship treatment product in Biktarvy. 46% of patients in the United States takes Biktarvy, it’s still growing. We have the flagship treatment for prevention in Descovy. And then we have some incredibly important new treatment and prevention options that are in our pipeline, all of which will drive continued growth, not only through the end of the decade but beyond.”

On oncology, he said: “It’s a $3 billion business and growing, growing rapidly. And then when you kind of think of oncology, and I think this is lost on people. Let’s say there are three or four areas of real promise and interest in oncology today. Three of those four, Gilead is a leader or one of the leaders. So three of the most exciting areas…”

GILD is a Long-Term Buy under $80 for a first target of $120.

Meta Platforms (META – $298.67) published For Those Using Metaverse Technologies, the Impact Is Real. They showed that virtual, mixed, and augmented reality are reaching new levels of impact as surgeons, athletes, industrial workers, and more come to rely on immersive technologies in their fields. They shared some examples of how people are using immersive technologies today.

For example, Richard Vincent, CEO & Co-Founder of FundamentalVR, winner of Frost & Sullivan’s 2023 Company of the Year Award as best in class in the global VR surgical simulation and training industry, said: “With more than 5 billion people worldwide lacking access to safe surgery due in part to a shortage of trained surgeons, the ability to train in a safe and accessible environment can make a significant impact in countries where access to advanced surgical training is limited. Studies have shown a remarkable improvement in the quality of training and patient outcomes when using immersive surgical training. Our virtual learning platform, Fundamental Surgery, enables medical teams to perfect their precision skills in a risk-free environment, instilling confidence in them to operate in real-life scenarios with the utmost competence. With the integration of haptic feedback, we have observed a significant improvement in surgical proficiency.”

META is a Buy under $150 for a $400 target in 2024.

SoftBank (SFTBY – $21.35) unveiled pricing on Tuesday for the $52 billion, 95.5 million share initial public offering of ARM plc. It will be the largest US IPO this year. Lead underwriters Goldman Sachs, Barclays, JPMorgan Chase, and Mizuho Financial Group and selling brokers will share about $100 million in underwriting fees.

Apple and several other large technology companies invested $735 million in the deal. Apple, Google, Samsung, Nvidia, and AMD are ARM clients. Intel, Taiwan Semiconductor, MediaTek, Cadence, and Synopsys also will buy stock.

Following the IPO, SoftBank will own approximately 90.6% of ARM,or approximately 89.9% if the underwriters exercise in full their “green shoe”option to purchase additional shares. SFTBY is a Buy under $25 for a first target of $50 in the next two years.

Small Tech

Enovix (ENVX – $14.11) will launch its first podcast, “Journey to Scale,” on September 13 to provide in-depth and frequent updates as it scales to high-volume manufacturing. The podcast is being launched following commencement of Factory Acceptance Testing of the company’s Gen2 production equipment, a key milestone.

The podcast will be available on major podcast platforms and can be found HERE. The next day, the company will present at the Morgan Stanley Laguna Conference. Adam Jonas, Head of Global Auto & Shared Mobility Research at Morgan Stanley recently said: “I brought together my research colleagues across Autos, Batteries, Mining and Clean Tech to assess implications for sectors and stocks that are better positioned or more challenged based on our scenario framework. We assess policy gaps and breakdown capex spend totaling up to $7-10 Trillion.” Morgan Stanley owns roughly 3 million shares of ENVX, but has not initiated coverage – yet. Buckle up! ENVX is a Buy up to $20 for a 4-year hold to $100+ as their BrakeFlow lithium-ion battery takes market share.
Primary Risk: A new competitor invents a better battery.

QuickLogic (QUIK – $8.20) presented at the Jefferies Semiconductor, IT Hardware & Communications Technology Summit. (SLIDES HERE).

They said their SensiML Artificial Intelligence and Machine Learning tools for the Internet of Things edge are gaining traction.

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Leading to 2023 being their breakout year:

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Wall Street doesn’t believe it yet or just isn’t paying attention, but its finally happening. QUIK is a Buy up to $10 for my $40 target as their sensor hub is widely adopted in smartphones, tablets and wearables.
Primary Risk: New sensor hub competitor emerges.

Biotech MegaShift: The $20-For-$1 Stocks

Say you put $2,000 into a stock that goes from 50¢ a share to $10. The $2,000 turns into $40,000. Then you put the $40,000 into another stock that goes from 50¢ to $10. That turns the $40,000 into $800,000. You did it with two stocks and never risked going negative more than $2,000. (Not that you won’t be mad at me if the first one works and then the second one doesn’t, taking your $40,000 to Money Heaven.)

If you can afford it – and it would not be too big a position in your portfolio – putting $2,000 into each of these speculative biotechs might be a good way to start. Buying these out-of-favor, fallen, or forgotten companies that can get important products through the FDA at very low market capitalizations seems like a good strategy to me.

Risks

Development-stage biotechs are subject to investor sentiment swings from wildly optimistic to excessively pessimistic – mostly the latter recently. After the Primary Risk for each company, I’ve added the clinical stage of their lead product, the probable time of their first FDA approval, and the probable time of their next financing.

As always, you need to think about an appropriate position size. You could buy a full position upfront and then just hold on, or buy some upfront and leave room to add more on the inevitable financings, transient clinical trial setbacks, and the like.

Aptose Biosciences (APTO – $3.83) closed a $3 million investment by Hanmi Pharmaceutical at $4.488 per share, the first tranche of a private equity investment for up to a maximum of $7 million or 19.99%.

The closing of the second tranche for up to $4 million will be triggered by Aptose achieving, prior to July 1, 2024, certain manufacturing and data milestones related to tuspetinib. They anticipate achieving the milestones by yearend. APTO is a Buy under $2.50 for a $30 target in a buyout.
Primary Risk: Either drug fails in clinical trials.
   Clinical stage of lead product: Phase 2
   Probable time of first FDA approval: 2025
   Probable time of next financing: Late 2025

Arch Therapeutics (ARTH – $0.55) dropped 31% today after a series of SEC filings. On September 1 they filed a Form 14C informing us that certain actions were taken by the written consent of the holders of a majority of the outstanding voting stock in lieu of a meeting. They increased the number of authorized shares of stock from 12,000,000 to 350,000,000 shares. Then said the Board can approve another reverse split between 1-for-1.5 and 1-for-20.

On September 6 they filed an 8-K to amend the convertible notes to extend the date of the required uplist to Nasdaq from August 31 to September 30. That means another reverse split is imminent because they need a stock price over $4 to uplist.

At this point, we may as well wait for the uplist to see if the stock gets a bump. ARTH is a Hold for a buyout.
Primary Risk: AC5 fails to sell or the internal trial fails.
   Clinical stage of lead product: External approved. Internal trial 2024
   Probable time of first FDA approval: External done. Internal 2025
   Probable time of next financing: December 2023 quarter

Compass Pathways (CMPS – $9.62) published a peer-reviewed paper in Pyschopharmacology that showed the results of a retrospective study that evaluated the potential of its AI technologies to support investigational COMP360 psilocybin treatment in treatment-resistant depression (TRD). The AI model has the potential to predict outcomes of COMP360 treatment in people with TRD up to 12 weeks after treatment using recordings taken during the integration session 24 hours after administration. CMPS is a Buy under $20 for a very long-term hold to a 10x.
Primary Risk: Their drugs fail in the clinic.
   Clinical stage of lead product: Phase 2
   Probable time of first FDA approval: 2025
   Probable time of next financing: Late 2025

Inovio (INO – $0.45) got FDA Breakthrough Therapy designation for INO-3107 as a potential treatment for patients with Recurrent Respiratory Papillomatosis (RRP). Breakthrough Therapy designation is a process designed to expedite the development and review of drug candidates that are intended to treat a serious or life-threatening condition and for which preliminary clinical evidence indicates that the drug may demonstrate substantial improvement over available therapy on clinically significant endpoints. INO is a Buy under $7 for a very long-term hold.
Primary Risk: Their drugs fail in the clinic.
   Clinical stage of lead product: Phase 3
   Probable time of first FDA approval: 2024
   Probable time of next financing: Early 2025

Medicenna (MDNA – $0.32) will hold a stockholder’s meeting on September 28. Item 5 is to approve a reverse stock split between 1-for-5 and 1-for-15. Vote NO. Buy MDNA under $3 for a first target of $20, then maybe $40.
Primary Risk: Their drugs fail in the clinic.
   Clinical stage of lead product: Entering Phase 3
   Probable time of first FDA approval: 2024
   Probable time of next financing: March 2024

Inflation MegaShift

Gold ($1,943.60) continues its consolidation around the $1,950 level. The fractal dimension is almost completely consolidated – one more week should do it. As we know, it can always get even more consolidated, but a new trend can start anytime after the 55 level is hit.

Miners & Related

Sprott Inc. (SII – $32.83) said that the Sprott Private Resource Streaming and Royalty Annex Fund completed its final closing, raising a total of $310 million. With the close of the Annex Fund, total assets under management of Sprott Resource Streaming and Royalty Corp. stand at $1.1 billion within the Company’s private strategies segment. This competes with our Sandstorm Gold (SAND) recommendation, which offers more liquidity. Buy SII under $40 for a $70 target price.
Primary Risk: Prices of precious metals fall due to US dollar strength.

Cryptocurrencies

Cryptocurrencies are a diversifying asset that offer a unique opportunity to make (or lose!) a lot of money quickly. You can easily buy bitcoin and other cryptocurrencies at Coinbase, Block, or Robinhood.

Bitcoin (BTC-USD on Yahoo – $26,308.66) is waiting for the inevitable SEC approval of spot exchange-traded funds. Last Thursday, the SEC postponed its decisions on seven fund proposals from BlackRock, WisdomTree, Invesco Galaxy, Wise Origin, VanEck, Bitwise, and Valkyrie Digital Assets. The SEC was scheduled to rule on all seven applications by September 4, but postponed by 45 days to mid-October. I suspect that gives them time to negotiate a face-saving deal to approve all seven, plus Ark’s and Grayscale’s applications.

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BTC-USD, ETH-USD, GBTC, and ETHE are Strong Buys.
Primary Risk: Bitcoin falls due to over-regulation or is surpassed by another cryptocurrency.

Grayscale Bitcoin Trust (GBTC- $19.30) is a way to buy bitcoin at a discount before the SEC approves their application to convert to an exchange-traded fund. Don’t turn down free money. GBTC is a Buy under net asset value.
Primary Risk: Bitcoin falls due to over-regulation or is surpassed by another cryptocurrency.

Commodities

Oil – $86.81

Oil rallied over $85, its highest in more than 10 months, as reality struck. According to the Energy Information Administration, the weekly crude draw from Cushing, Oklahoma, was a hefty 6.307 million barrels. It should build back some next week as crude exports drop and imports surge.

According to the latest data from AAA, the national average price for a gallon of regular unleaded reached $3.80 on September 6, surpassing last year’s high price and earning the title of the second-highest nationwide average gasoline price. The draw on gasoline was 1.75 million barrels, bringing storage back to 2022 levels:

Click for larger graphic h/t @HFI_Research

And the same is true of the Big 4:

Click for larger graphic h/t @HFI_Research

Brent oil rose above $90 a barrel for the first time since last November as Saudi Arabia said it will continue its unilateral production cutback of one million barrels a day until December. They will hold output at about 9 million barrels a day — the lowest level in several years — for six months in total. Russia said it would curb 300,000 barrels a day of exports through yearend, aligning with Riyadh.

Click for larger graphic

Meanwhile, the biggest US oil exchange-traded fund is reviving the pre-pandemic investment strategy that drew the scrutiny of regulators and helped roil markets in 2020. The $1.2 billion United States Oil Fund will, in September, begin reallocating the majority of its holdings to the nearest oil futures contract, rather than spread exposure across the futures curve.

Regulators believe the fund’s decision to pile into the front of the curve prior to the 2020 oil crash exacerbated the market turmoil that followed. USO at the time had ballooned to more than $3 billion, at times holding 20% of all positions in near-term oil contracts. After the crash, CME Group ordered the fund to reallocate its funds across contracts.

About 20% of USO’s current holdings are invested in October 2023 contracts, 20% in November, 15% in December, 15% in January 2024 contracts, 10% in February, 5% in March, and 15% in June.
USO said in a statement it retains the ability to invest in later-dated contracts and other products such as OTC swaps if market conditions, regulatory requirements or other factors require it.

Oil finally broke out after a sneaky grind up over the last few months with front month West Texas Intermediate (WTI) hovering around $87 a barrel. The graphic below tells the long term story. This does not look like demand destruction to me.

Click for larger graphic h/t @topdowncharts

Nothing short of shutting down the entire global economy is going to stop oil demand growth driven by emerging markets – or insisting their citizens must live lives of desperation and poverty. Mix that in with a market that refuses to acknowledge this reality, under-investment in new production, and an emboldened OPEC+ and you’ve got a perfect storm for a structural bull market in oil.

For a few decades, the US has enough reserves to make a difference to the price of oil with a sensible fossil fuels policy. But in the long run, it’s OPEC+.

Click for larger graphic h/t @@WinfieldSmart

The current energy bull market is progressing nicely, with the recovery in 2020/21, incredible outperformance in 2022, and slight pullback plus a bounce in 2023. Political and structural changes put OPEC+ back in driver’s seat and US shale growth behind us. Those are major tailwinds as the cycle continues along. And how big could this be?

Click for larger graphic h/t @WhiteTundraSG

Got oil? I am raising my oil buy limits – again. The July 2026 Crude Oil Futures (CLN26.NYM – $70.59) are a Buy under $70 for a $200+ target. Only buy futures for all cash; do not use margin.

The United States 12 Month Oil Fund, LP (USL – $39.41) is a Buy under $40 for a $100+ target.

Energy Fuels (UUUU – $7.33) will ride uranium up for years as it breaks out. Copper is next.

Click for larger graphic

UUUU is a buy under $8 for a $30 target.
Primary Risk: Uranium prices fall.

Freeport McMoRan (FCX – $39.76) CEO Richard Adkerson did an interesting fireside chat at the Jefferies Industrial Conference this afternoon (WEBINAR HERE and TRANSCRIPT HERE). He said that even with all the negative headlines about China, copper demand is holding up and inventories are extremely low. They think shortages and rationing are coming.

They are tracking other companies’ attempts to bring new mines into production and everyone is going way over budget. Freeport is very focused on controlling costs and keeping a strong balance sheet. They will only do an acquisition that offers a major strategic advantage at a low price – no bidding wars.

They are having problems recruiting workers in the US, although not overseas. They are starting to use autonomous trucks in Arizona and exploring joystick-controlled underground mining equipment.

He said Indonesia is now miming 200,000 tons of rock every day and he is “looking forward to reporting third quarter results.” FCX is a buy under $44 for a $65 target within two years.
Primary Risk: Copper prices fall.

International & Other Recommendations
It is important to hold some non-US assets, especially in China. According to the Financial Times, foreign investors dumped $12.4 billion of Chinese stocks in August, a record pace going back to 2014, as fear of economic turmoil persists. When everyone leans one way, the contrarian in you should be itching to write buy tickets.

EMQQ Emerging Markets Internet & Ecommerce ETF (EMQQ – $30.47) is a Buy under $38 for a $66 target in 12 to 18 months.

KraneShares Bosera MSCI China A Share Fund (KBA – $22.81) is a Buy under $40 for a three- to five-year hold.

Morgan Stanley China A-Share Closed-End Fund (CAF – $12.41) is a Buy under $18 for a three- to five-year hold.

KraneShares CSI China Internet Exchange-Traded Fund (KWEB – $27.67) is a Buy under $40 for a double over the next three years.
Primary Risk of all four of these: China falls into a recession.

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RIP Jimmy Buffet. Merkel cell skin cancer

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Your rethinking climate change Editor, (but see Who is behind the viral document stating that “there is no climate emergency”?) but then see (I Left Out the Full Truth to Get My Climate Change Paper Published)

Michael Murphy CFA
Founding Editor
New World Investor

All Recommendations

Priced 9/7/23. Check out the complete Portfolio page HERE.

Buys
These are the stocks everyone needs to own because transformative events are happening over the next year or two, and I expect to hold them long-term.

Tech Dominators
  Apple Computer (AAPL – $177.56) – Buy under $150 for new iPhones
  Corning (GLW – $31.52) – Buy under $33, target price $60
  Gilead Sciences (GILD – $73.94) – Buy under $80, target price $120
  Meta (META – $298.67) – Buy under $250, target price $400
  SoftBank (SFTBY – $21.35) – Buy under $25, target price $50

Small Tech
  Enovix (ENVX – $14.11) – Buy under $20; 4-year hold to $100+
  First Trust NASDAQ Cybersecurity ETF (CIBR – $46.92) – Buy under $40; 3- to 5-year hold
  Fastly (FSLY – $23.38) – Buy under $20; 2- to 5-year hold to $80+
  PagerDuty (PD – $23.42) – Buy under $30; 2- to 5-year hold
  QuickLogic (QUIK – $8.20) – Buy under $10, target price $40
  Rocket Lab (RKLB – $6.32) – Buy under $13, target price $30+
  Velo3D (VLD – $1.43) – Buy under $6, target price $50

$20-for-$1
  Akebia Biotherapeutics (AKBA – $1.21) – Buy under $2, target $20
  Aptose Biosciences (APTO – $3.83) – Buy under $10, ultimate target $300
  Compass Pathways (CMPS – $9.62) – Buy under $20, hold a long time for a 10x return
  Inovio (INO – $0.45) – Buy under $7, hold a long time
  Invitae (NVTA – $0.90) – Buy under $10, first target $50, then $100+
  Medicenna (MDNA – $0.32) – Buy under $3, first target $20, then maybe $40
  ScyNexis (SCYX – $3.16) – Buy under $3, target price $20, then $50
  TG Therapeutics (TGTX – $11.29) – Buy under $12 for buyout at $30+

Inflation
  A Short-Sale or REO House – ($415,400) – Hold
  Bag of Junk Silver – ($23.26) – hold through silver bull market
  Sprott Gold Miners ETF (SGDM – $24.09) – Buy under $28, target price $50
  Sprott Junior Gold Miners ETF (SGDJ – $27.00) – Buy under $39, target price $100
  Sprott Physical Gold and Silver Trust (CEF – $17.95) – Buy under $18, target price $30
  Global X Silver Miners ETF (SIL – $24.92) – Buy under $30, target price $50
  Coeur Mining (CDE – $2.25) – Buy under $5, target price $20
  First Majestic Mining (AG – $5.60) – Buy under $11, next target price $23
  Paramount Gold Nevada (PZG – $0.32) – Buy under $1, first target price $10
  Sandstorm Gold (SAND – $5.17) – Buy under $10, target price $25
  Sprott Inc. (SII – $32.83) – Buy under $40, target price $70

Cryptocurrencies
  Bitcoin (BTC-USD – $26,308.66) – Buy
  Grayscale Bitcoin Trust (GBTC – $19.30) – Buy
  Ethereum (ETH-USD – $1,644.56) – Buy
  Grayscale Ethereum Trust (ETHE – $11.56) – Buy

Commodities
  Crude Oil Futures – July 2026 (CLN26.NYM – $70.59) – Buy under $70; $200+ target
  United States 12 Month Oil Fund, LP (USL – $39.41) – Buy under $40; $100+ target
  EQT (EQT – $41.76) – Buy under $35; $70 first target
  Energy Fuels (UUUU – $7.33) – Buy under $8; $30 target
  Freeport McMoRan (FCX – $39.76) – Buy under $44; $65 target within two years

International & Other Recommendations
  EMQQ Emerging Markets Internet & Ecommerce ETF (EMQQ – $30.47) – Buy under $38 for a $66 target in 12 to 18 months
  KraneShares Bosera MSCI China A Share Fund (KBA – $22.81) – Buy under $40 for a three- to five-year hold
  Morgan Stanley China A-Shares Fund (CAF – $12.41) – Buy under $18 for a three- to five-year hold
  KraneShares CSI China Internet ETF (KWEB – $27.67) – Buy under $40 for a double over the next three years
  Acreage Holdings (ACRDF – $0.36) – Buy under $2 for the Canopy Growth merger
  Mongolia Growth Group (MNGGF – $0.89) – Buy under $1.30; long-term hold

Holds
These are holds but not sells – yet. They could get moved back to one of the buy categories if their prices drop or outlook improves, or they could become sell recommendations in the future.
  Arch Therapeutics (ARTH – $0.55) – Hold for buyout

Publisher: GwynRose LLC, 5348 Vegas Drive, Suite 868, Las Vegas, NV 89108

New World Investor does not act as a personal investment adviser or advocate the purchase or sale of any security or investment for any specific individual. The recommendations and analysis presented to members are for the exclusive use of members. Members should be aware that investment markets have inherent risks and there can be no guarantee of future profits. Likewise, past performance does not assure future results. Recommendations are subject to change at any time. Nothing in this presentation should be considered personalized investment advice. No communication to you by Michael Murphy or any of our employees or contractors should be deemed as personalized investment advice.

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