Why Did Alphabet Launch A Separate Company For Drug Discovery
One of last week’s top stories was the launch of Isomorphic Labs, a company exclusively dedicated to drug discovery, by Alphabet. This newly formed company has Demis Hassabis (also the CEO of DeepMind) as the founder and CEO. It may be noted that DeepMind achieved a major breakthrough in biology and medical research by devising AlphaFold2. It solved the 50-year-old grand challenge of protein folding by predicting the 3D structure of a protein to atom-level accuracy directly from its amino acid sequence. Via a brief blog, Hassabis announced the launch of Isomorphic Labs — presenting a teaser of what the company would be working on and what is that it aspires to achieve. However, not much is known about why Alphabet and DeepMind felt the need for a separate company dedicated to AI-driven drug discovery. DeepMind & Biomedical Research “One of the most important applications of AI that I can think of is in the field of biological and medical research, and it is an area I have been passionate about addressing for many years. Now the time is right to push this forward at pace, and with the dedicated focus and resources that Isomorphic Labs will bring,” Hassabi wrote in the launch blog. He added that Isomorphic Labs is a commercial venture that reimagines the drug discovery process from the first AI-first perspective — to model and understand fundamental mechanisms of life. The #AlphaFold source code has been updated and now accounts for multi-chain protein complexes – providing a significant improvement in accuracy for predicting protein interactions: https://t.co/4gyZ0loLrdGenerate predictions from your browser via: https://t.co/2Vd4itjElu pic.twitter.com/Db66KcXCRD— Google DeepMind (@GoogleDeepMind) November 2, 2021 As mentioned in the blog and other interviews, the success of various computational biology and drug research projects, especially that of AlphaFold, has been the motivation behind launching a commercial venture like Isomorphic Labs. Without taking away from other breakthroughs from DeepMind (think AlphaGo), AlphaFold has been special mainly because of the complexity of the challenge. Before it was demonstrated, researchers and experts in the field always believed that enumerating all the possible configurations of a typical protein structure before reaching the right 3D structure is a mammoth task and painfully time-consuming. In the latest advancement to the AlphaFold project, the DeepMind team has demonstrated an AI-based dynamic model of the human nuclear pore complex. This model shows how the protein scaffold and the nuclear envelope are coupled inside cells. We combined #AlphaFold and #cryoEM to build a new model of the nuclear pore complex, the largest complex in the human cell! The structure covered by the model is 15x bigger than the human ribosome and 2x bigger than old nuclear pore models. 1/7Read how: https://t.co/mCLg0hEQFr pic.twitter.com/YpUvonwVT7— Jan Kosinski (@jankosinski) October 28, 2021 This is just the very beginning, and the field of digital biology offers huge scope for AI-based research and development work. Hassabis has often spoken about the ultimate aim of solving real-world problems via the research work at DeepMind. Biology and drug discovery feature very prominently in the list. In an earlier interview, Hassabis had mentioned that billions are invested into research by Big Pharma. Since this investment is highly dependent on the quarterly earnings report, the industry has become conservative with increasing costs of failure. He opined that the upper management of these big pharma companies has persons from finance and marketing departments at the helm. Hence, naturally, the aim becomes to profit from what has already been invented rather than investing more newer (even riskier) R&D projects. Since a lot of research in the industry is product-led, one can achieve only incremental research; this is not conducive to doing ambitious research needed to achieve any breakthrough, as Hassabis noted. Several studies corroborate Hassabis’ observation. One such report by innovation foundation Nesta in 2018 noted that “the exponentially increasing cost of developing new drugs is directly reflected in low rates of return on R&D spending.” Worse, the R&D returns in biopharma are on a downward slope. While DeepMind prides itself on being a heavily research-driven organisation, since its acquisition by Google in 2014 against a deal worth $500 million, the company is betting big on product management. Hassabis also said earlier that the lab wants parent organisations — Google and Alphabet — to derive adequate benefit out of the research DeepMind is doing. For example, DeepMind’s text-to-speech model that mimics human voice, WaveNet, has been embedded in many Google devices and its own product team within Google. With the launch of Isomorphic Labs, DeepMind and Alphabet seem to aim to strike a sweet spot between research and product development, concentrating particularly on biomedical research, which has emerged as a major vertical. As the company blog mentions, Isomorphic Labs will be a commercial venture, wherein the company will partner with pharmaceutical and biomedical companies. With Hassabis at the helm of affairs, DeepMind is expected to provide and facilitate devising the company’s strategy and vision. The company will be focusing on building a multidisciplinary team with experts from the areas of AI, biology, biophysics, engineering, and medicinal chemistry. Alphabet’s Next Bet The pandemic has put focus big time on fields like biomedical engineering and AI-driven drug discovery. It is not surprising that in 2020, the private investment made in these fields rose 4.5 times than the previous year. The number will grow further to reach an estimated $71 billion by 2025. Credit: Stanford Like many other big techs, Alphabet has placed great importance in drug discovery and pharmacy. By leveraging its expertise in software, data and AI, Alphabet finds itself among the top tech companies in the world, capitalising on rising opportunities in this field by getting involved in research and development, discovery, clinical development, and patient monitoring. The approach has only become more aggressive in the recent pandemic era. It is not very surprising that Alphabet has decided to go all out in its efforts in this field by launching a separate company for drug discovery. Credit: CB Insights
Why did Alphabet and DeepMind feel the need for a separate company dedicated to AI-driven drug discovery.
Why did Alphabet and DeepMind feel the need for a separate company dedicated to AI-driven drug discovery.
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["AI", "Aim", "RAG", "R", "Go", "Git", "API", "ELT", "GAN", "AI-first"]
I am a technology journalist with AIM. I write stories focused on the AI landscape in India and around the world with a special interest in analysing its long term impact on individuals and societies. Reach out to me at shraddha.goled@analyticsindiamag.com.