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1. Volpara Health and Invitae Have Teamed Up with the Goal to Prevent Breast Cancer

Volpara Health and Invitae (NVTA) recently announced a collaboration on an integrated solution for breast cancer prevention. Headquartered in New Zealand, Volpara Health is an AI-platform company offering a suite of digital services that streamline and improve breast cancer screening. Aimed at technicians in more than 2,000 cancer screening centers accounting for nearly one third of all mammograms in the US, Volpara’s suite of services includes workflow management tools, clinical decision support, and proprietary algorithms measuring breast density, tissue volume, and longitudinal risks.

Volpara will integrate into its software suite Invitae’s genetic information management tools. Incorporating solutions for genetic testing, genetic counseling, and patient risk-stratification, Volpara should be able to increase the value it provides to US screening centers. Importantly, Invitae and Volpara have embraced the Tyrer-Cuzick model, the premier framework for evaluating patient risks for hereditary breast cancer.

Invitae seems likely to benefit from Volpara’s distribution channels in the United States. This week, for example, the FDA approved the newest version of Volpara’s AI-software portfolio to run on Giotto and Siemens mammography instruments.

Finally, we believe Volpara and Invitae could combine de-identified datasets to bolster their machine learning capabilities. Volpara’s technology has been trained on over 40 million images from 13 million unique people across 39 different countries. Combining high-quality phenotypic data with Invitae’s extensive repository of genomic data, this collaboration could add another dimension to the prevention of breast cancer.

 

2. AlphaFold Will Include a Protein Structure Database That Could Enhance Drug Discovery

According to our estimates, analysts and investors are undervaluing R&D pipelines in the biotech industry. Alphabet’s (GOOG) AlphaFold2, a neural network (NN)-based algorithm that uses sequences to predict the 3D shape of proteins, could exacerbate the undervaluation.

A few weeks ago, Alphabet subsidiary Deep Mind announced a database of protein structures powered by AlphaFold2. Based on their amino acid sequences, the database predicts the 3D structure of roughly 350,000 proteins. Importantly, the database is open sourced and free!

Composed of thousands of linked amino acids (AAs), proteins are critical to life on earth. AAs determine protein shapes and functions. A better understanding of protein structures could lower research costs and accelerate the rate of drug discovery.

X-ray crystallography, a common experimental method for determining protein structures, is tedious, slow, and expensive. In recent decades, scientists resorted to computational biology in an attempt to overcome these obstacles but none of the algorithms proved accurate enough.

AlphaFold2, however, has demonstrated predictive accuracy that has met and sometimes exceeded high-fidelity experimental approaches. The 3D structure of hemoglobin, a well-known protein in red blood cells that transports oxygen through the body, is characterized in the database, as shown here.

Scientists at the University of Southern California (USC) hypothesize that research on protein structures could lower the cost and time to take a candidate from discovery to Investigational New Drug (IND) approval by 50%. Based on past trial throughput rates (status quo), for example, we believe pre-clinical research and development costs account for roughly 40% of commercialized drug development and could drop by more than 75%, from $240 million to $50 million per drug, thanks to predictive NN based algorithms like AlphaFold2. AlphaFold2 does not account for and incorporate inter protein interactions yet but, in our view, will improve iteratively because of its open-sourced model.

 

3. Axie Infinity Could Turbocharge Play-to-Earn Gaming

During the last ten years, free-to-play games have surfaced and changed the course of gaming around the world. The free-to-play model emerged with mobile gaming and now accounts for an estimated 80% of the estimated $175 billion in worldwide gaming revenues.

That said, the gaming ecosystem is ever evolving. Axie Infinity, a popular NFT based video game, has introduced a new genre of games that are not free-to-play but play-to-earn. Founded in 2018, Axie Infinity is a decentralized game built on the Ethereum blockchain. The goal of the game is to breed, raise, battle, and trade Axies, which are cute Pokemon-like creatures.

Sounds simple, right? Well, it’s not. Let’s break the game down to its basics: Axies and SLP.

Axies
Gameplay involves taking a team of Axies into a turns-based battle. Axies are NFTs, non-fungible tokens, or creatures with digital uniqueness, each with its own traits and characteristics, that gamers can trade in open markets. Axies range in cost, the minimum of which today is roughly $300. To play, gamers must buy at least 3 Axies.

SLP (Smooth Love Potion)
Gamers earn SLPs by winning battles. SLPs are necessary to breed new Axies, which can increase the value of teams or can be sold for profits. Currently, one SLP is worth 23 USD cents.

Enabled by the tokenization of in-game assets, we believe Axie Infinity is the foundation of an emerging economy. By breeding Axies and earning SLP, full-time players earned $1,500 on average and generated $200 million in platform fees last month alone. Notably, 40% of Axie Infinity’s 350,000 daily active users live in the Philippines, not surprising because those who lost jobs during the COVID-19 pandemic can earn more playing Axie Infinity than the $900 per month average income that they might earn otherwise.

 

4. What Are the “Promises and Perils” of CBDCs in the US?

Given the recent growth of stablecoins and digital currencies, US legislators have accelerated discussions on the potential for a US dollar-based central bank digital currency (CBDC). Issued by the central bank, a CBDC would be similar to fiat cash and intended for retail payments.

More than 80% of the world’s central banks are researching CBDCs with roughly 40% developing proofs-of-concept. Earlier this year, for example, China started a public pilot of the digital yuan which it now is testing in cross border transactions with Hong Kong, Thailand, and the UAE.

Last week in the US, the House Committee on Financial Services discussed the opportunities and risks associated with CBDCs. In the hearing, lawmakers expressed concern about the impact that the digital yuan might have on global payments and the threat it could pose to dollar dominance as the world’s reserve currency. In their view, a dollar CBDC might allay these concerns by providing a global alternative while also increasing the efficiency of domestic payments.

ARK believes that, while CBDCs might seem comparable cosmetically to cryptocurrencies like bitcoin or ether, a Fed-issued CBDC would pose more of a threat to commercial banks than to cryptocurrencies. A CBDC could eliminate the dependence on intermediaries for account management and due diligence like KYC/AML (know your customer/anti money laundering), reducing an important source of their income.

You can listen to the hearing here.