Martin Shkreli, out of prison for running a Ponzi scheme, now pushes Web3 thing

His latest project, Druglike, most definitely isn't in the pharmaceutical business, from which he's been banned

Martin Shkreli, released from prison in May after serving much of his seven-year prison sentence for securities fraud, on Monday announced Druglike, described as "a Web3 drug discovery software platform."

Web3 has been characterized by Tesla CEO and Twitter antagonist Elon Musk as "more marketing buzzword than reality right now" and by crypto-critic and software engineer Stephen Diehl as "a vapid marketing campaign that attempts to reframe the public’s negative associations of crypto assets into a false narrative about disruption of legacy tech company hegemony."

Web3 is notionally a more decentralized version of the internet that involves blockchain technology and cryptocurrency – famously the enabler of ransomware. This supposed decentralization has been dismissed as "an illusion."

Shkreli's press release this week emphasizes, "Druglike is a blockchain/Web3 software company and not a pharmaceutical company. Druglike is not engaged in pharmaceutical research or drug development."

That makes a certain amount of sense given that Shkreli – who was jailed in 2018 for pulling off what prosecutors said was a massive Ponzi scheme, and was dubbed a "pharma bro" for his online trolling – has been twice banned for life from the pharmaceutical industry for defrauding investors.

The initial ban was ordered by Federal District Judge Denise Cote, who oversaw a lawsuit brought by seven US states and the FTC in New York City.

In January, the court found that Shkreli violated both federal and state laws through anticompetitive conduct. He had raised the price of the anti-parasitic drug Daraprim (pyrimethamine) from $17.50 per tablet to $750 per tablet after acquiring the rights to the medication, and taken steps to prevent rival firms from making a generic version. Judge Cote banned Shkreli from the pharmaceutical industry and ordered him to pay nearly $65 million in profits.

A month later, Judge Kiyo Matsumoto of the US District Court for the Eastern District of New York, issued a second ban in a fraud case brought by the US Securities and Exchange Commission (SEC). Shkreli is barred from serving as an officer or a director of any publicly traded company for life.

The Register asked the SEC whether it considers this latest venture to be a violation of Shkreli's industry ban. An SEC spokesperson declined to comment.

In a statement, Shkreli, co-founder of Druglike, said, "We started Druglike because in our experience, traditional drug discovery software is too difficult and expensive to use." Not previously known for his pricing sensitivity, he continued, "Druglike will remove barriers to early-stage drug discovery, increase innovation and allow a broader group of contributors to share the rewards."

How will Druglike do so? Well, the Web3 venture has published a white paper [PDF] that outlines a distributed computing platform to evaluate molecular structures most likely to bind to a drug target, like a protein or enzyme. The paper compares Druglike to Folding@Home, a project that pools computational power to understand molecular interactions.

It differs in that it calls for using "Proof-of-Optimization, a novel Proof-of-Work mechanism establishing consensus by validating and rewarding solutions to function optimization problems."

Consensus algorithms are necessary to coordinate activity among decentralized compute nodes. Proof-of-Work is the energy-hungry cryptographic consensus mechanism made famous by Bitcoin. Essentially, the white paper suggests that participants will be rewarded, presumably with some cryptocurrency token, for submitting the most highly optimized solution to a particular task.

However, the paper also denies any such aspirations and insists it's purely a solicitation for public feedback. Following its summary paragraph, the paper includes a length disclaimer that asserts nothing within should be relied upon:

Legal Disclaimer: Nothing in this White Paper is an offer to sell, or the solicitation of an offer to buy, any tokens. Druglike is publishing this White Paper solely to receive feedback and comments from the public. If and when Druglike offers for sale any tokens (or a Simple Agreement for Future Tokens), it will do so through definitive offering documents, including a disclosure document and risk factors. Those definitive documents also are expected to include an updated version of this White Paper, which may differ significantly from the current version. If and when Druglike makes such an offering in the United States, the offering likely will be available solely to accredited investors.

Nothing in this White Paper should be treated or read as a guarantee or promise of how Druglike’s business or the tokens will develop or of the utility or value of the tokens. This White Paper outlines current plans, which could change at its discretion, and the success of which will depend on many factors outside Druglike’s control, including market-based factors and factors within the data and cryptocurrency industries, among others. Any statements about future events are based solely on Druglike’s analysis of the issues described in this White Paper. That analysis may prove to be incorrect.

Christoph Gorgulla, research associate at Harvard University, and corresponding author for a 2020 paper published in Nature that describes VirtualFlow, an open source drug discovery platform, told The Register in an email that the Druglike white paper has not been published in any peer-review journal and thus hasn't been evaluated by any experts in detail.

"Without such an in-depth review, it is hard to say how credible or useful this new platform is," said Gorgulla. "I would recommend waiting until the paper is published by a peer reviewed journal. The type of journal it will be published in will also tell you about the impact. Eg, if it is published in a high-impact factor journal such as Nature or Science, then it is likely a great new innovation."

Alas, to date, the paper has only been released online with a disclaimer.

Gorgulla took issue with Shkreli's assertion that "current in silico software is only accessible to large pharmaceutical companies willing to pay obnoxious licensing fees."

"This is not true," he said. "There is plenty of free software. Also the software that I have published in Nature (VirtualFlow) is free and open source." ®

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