Jon Chee

NY Illumina/GRAIL lawsuit Final Part: Summation "Illumina’s directors and officers, foreseeing their non-exculpated liability in connection with their decision to close the Acquisition in spite of the EC standstill order, determined to shift that liability to Illumina at a cost of up to $100 million, made that shifting of liability a requirement before they would approve the Acquisition, and at the same time abandoned $150 million in insurance for the Company that could have funded Illumina’s financial losses associated with the Acquisition. At no time was this approved by a disinterested vote of disinterested directors or stockholders, and it was not fair to Illumina. By stripping away the Company’s insurance down to $0, while at the same doubling their D&O insurance to $300 million, Illumina’s directors and officers abandoned their fiduciary duties to the Company and left Illumina unprotected while protecting themselves at Illumina’s expense." "Prior to acquiring GRAIL, Illumina’s financials were strong, and its share price reflected that as it traded at its closing peak of $524.24 on August 16,2021. However, after the Acquisition, GRAIL acted like a millstone around Illumina’s neck, costing billions of dollars to maintain while providing no benefit to Illumina." "The Acquisition ultimately dropped Illumina’s cash balance to zero. On March 8, 2021, Illumina entered into a credit agreement with Bank of America for $750 million to help pay for the Acquisition and to keep the lights on at Illumina. When that proved insufficient to carry Illumina’s rising costs, on March 16, 2021, Illumina issued another $1 billion in notes. Less than two years later, on January 5, 2023, Illumina deemed it necessary to sign another $750 million credit agreement to “finance the working capital needs, and for general corporate or other lawful purposes, of Illumina and its subsidiaries.” Illumina has been unable to seek any other potential acquisition opportunities as it spent the bulk of its cash balances on the Acquisition." "By reason of the Director Defendants’ positions with the Company as directors, they owed the Company and its stockholders a duty of loyalty. deSouza and Dadswell owed the same duty of loyalty as Illumina officers. By closing the Acquisition, Defendants breached that duty in three ways: causing a knowing violation of the law, consciously disregarding their fiduciary duties and engaging in self-dealing."

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Here's a key difference between the biotech industry and academia that will help you integrate. Industry has a fundamentally different relationship with time than most academic systems. In general industry prioritizes being concise, clear, and efficient. Here are some examples of different relationships w/time. These are generalizations. Of course there are exceptions. 𝗘𝗺𝗮𝗶𝗹𝘀 Debating does not happen in emails. Emails are not paragraphs long. Short and to the point. Convey time, date, concrete information. Avoid polling the audience. 𝗠𝗲𝗲𝘁𝗶𝗻𝗴𝘀 Only invite people that are relevant. If it can be summarized in a memo, no meeting. If it can be summarized in a video, no meeting. Meetings that end early are a win. Rarely are meetings scheduled for > 40 min. 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 75% certain & launch > 100% certain and miss market. Your detailed plans about the future will change. Pivoting is common in response to real-world data. In strong organizations, decisions are decentralized. Delegation exists throughout the org. 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 Include only the necessary information If it isn't written down, it didn't happen. Published standards govern methods. Shorter = better. 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 Different project leads within same group. Sometimes you lead, sometimes you follow. If a project is running behind... ...extending the timeline is usually not the solution. The solution is more resources, or reduce scope. 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝗹 𝗣𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻𝘀 Define the problem statement. State the objective of the presentation or work. Communicate with as few sentences as possible. Less writing, more visuals. When asked a question, answer only that question. The common thread? Be brief, be clear, communicate effectively. #biotechnology, #biotechjobs, #scientist

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Here's an interesting use of AI in drug design: making compact proteins. ZipBio CEO Roee Farber told me his startup is shaving off the unimportant parts of proteins and using generative AI to fill in a backbone that holds the molecule together. Read more in my exclusive for Endpoints News: https://lnkd.in/eSGkhKUq #biotech #startup #drugdiscovery #drugdesign #AI #generativeAI #AIdrugdiscovery #AIdrugdesign #genetherapy #opthalmology #eyedisease #wetAMD #Eylea

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Despite the challenging fundraising environment, we are witnessing significant investments in AI-enabled drug discovery and development. Following Sanofi's recent partnership with OpenAI and Formation Bio (that some of you may remember as TrialSpark), the latter has taken a notable step by securing nearly $400M in their Series D funding round. This funding, aimed at enhancing their AI platform and in-licensing new product candidates, highlights the growing confidence in AI-driven healthcare innovations. This deal, much like the recent emergence of Xaira Therapeutics from stealth mode, highlights the latest fierce battleground among major VC funds. With A16Z backing Formation Bio, and Lightspeed and NEA investing in Xaira, the competition to lead in AI-powered biotech innovations is intensifying. Sequoia has even decided to back both ventures. #AIinHealthcare #BiotechFunding #Innovation #VentureCapital #FormationBio #XairaTherapeutics https://lnkd.in/eq6N2p4U https://lnkd.in/eNZ6vEtD

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I'm delighted to share news of this new AI-focused drug discovery company, Xaira, built on foundational technology from David Baker and led by Marc Tessier-Lavigne. The company applies AI tools to unlock opportunities in drug discovery for aspects of biology that we believe are not readily obtainable with conventional methods. I co-led NEA's investment in Xaira, along with my NEA partner and the firm’s co-CEO Mohamad Makhzoumi, and I will be joining Xaira’s board. Our enthusiasm for Xaira based on our belief that applying AI and large language models to biology holds immense promise and is still in its early stages. Currently, the application of AI to biology relies on model architectures borrowed from the tech world. A lack of well-curated clinical training sets hinders building and training these models effectively. This limits the advancement of AI in solving biological problems compared to other fields. Xaira aims to bridge this gap. We now have a clear understanding of the data needed to answer fundamental biological questions. By iterating on leading life science models and using focused perturbation data generated through our large-scale experiments, Xaira will generate data specifically suited to building advanced model architectures that are optimized for biology -- and hopefully, unlock therapeutic opportunities for patients who are not being optimally served by existing therapeutics.

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#Biopharma and #Ai and #ChatGPT ban: - #Biopharma Caution: The biopharma industry is cautious about #AI implementation in workflows. - #Employee Ban: More than half of life sciences companies have banned employees from using #ChatGPT, including 65% of the top 20 Big Pharmas. - #Data #Security Concerns: July The bans are mainly due to concerns about sensitive data leaks to competitors. - #Incident Reference: A #bug in ChatGPT last year allowed some users to see others' chat histories, raising security concerns. - #Lack of #Training: Less than 60% of companies have provided guidelines on safe ChatGPT use, though 15% plan to. - #Regular Use: Despite bans, over half of life sciences professionals use ChatGPT a few times a month, and over a quarter use it weekly or daily. - #AI #Perception: 83% of surveyed professionals consider AI technology to be overrated. - #AI #Adoption: Despite skepticism, many companies are actively using AI, with only 8% not adopting it and 10% claiming to lead in AI adoption. Is this action towards #ai in #Biophrma justified? Is it recommended? What about updating #biopharma #ai #literacy and #adoption to benefit? What about advancing the regulation #ai #applications in #biopharma?

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Announcing: AgingBiotech.info /therapeutics (direct link: https://lnkd.in/gRk_J7bP) a new (beta version) table attempting to list most (potentially) therapeutic interventions against aging that are already available, primarily supplements & already-approved drugs but also including lifestyle factors & other categories (eg environmental interventions). The goal is not to pass judgement on whether each works or to rank them all comprehensively but rather to take each & summarize several ways to evaluate it that others have already put forward plus links to as many useful sources for more info as easy to include. I'm launching this without it being comprehensively filled out on the assumption that it's better to release the substantial info already collected since many of the purported therapeutics are commonly discussed & even commonly used already, but in many cases by people who have not looked at very many sources of info about them. Many people are experimenting with personal use & some doctors are recommending some of these aging interventions despite that scientific understanding of many is woefully incomplete. What data & analysis exists is not easy to collect---there's no central place to quickly find links to much of the relevant papers & data. This table is meant to be an initial effort to be one such place, to be a jumping off point to allow people & doctors to quickly find many relevant papers & results for any given therapeutic commonly discussed as an aging/longevity intervention. The overall philosophy of this website is that amazing things are coming based on technologies in development but not yet available and based on science not even yet worked out in academia (& so not yet even in biotech development). Understandably, some people do not want to wait, but one should be cautious about over-interpreting early data on drugs & supplements w.r.t. longevity. This table is meant mostly as a way to aid deep dives to educate on the full extent of data available. This is basically a bunch of jumping off points meant to be more helpful to peruse first before just typing one version of the name of some therapeutic into Google. This is absolutely not a recommended "stack", nor a direct endorsement. FWIW, my own personal sense is that almost all the drugs & supplements here don't have enough evidence yet for most people to adopt them (especially to try to achieve super-physiological levels) and that by far the most important column is the who-needs-it column called "best diagnostics/biomarkers to determine individual need & to titrate dose", for which there are woefully inadequate answers for most things. I think a lot of people overestimate how much good many supplement or drug molecules will do & simultaneously my sense is that the lifestyle stuff is woefully underestimated & underutilized, & mostly safer. Hope this is useful to some people. Those who want to help fill in the missing details should reach out directly.

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