Insilico Medicine: 10 Years of TechBio Innovation

An AI Drug Discovery Company Revolutionizing Drug Development

Hello Everyone,

One of the biggest trends in Generative AI that I have been watching that isn’t being seen much or talked about by the mainstream is the impact in biotechnology, drug development and new ways of using AI in the coming biotech revolution.

According to executives working at the intersection of AI and health care, the field is on a trajectory that will see medicines completely generated by AI in the near future; according to some, within a few years at most it will become a norm in drug discovery.

Generative AI will be designing new drugs all on its own in the near future

• In the news lately, Scientists at Eli Lilly have been surprised by novel design of molecules that AI has produced as part of hypothetical drug discovery research.
• According to CNBC and others, a major precedent for AI-generated breakthroughs in biology was set in 2021 when Google’s DeepMind AI, known for its creative thinking in realms ranging from the strategy game Go to music, video, and cloud computing, came up with a novel protein called AlphaFold.
• Within a few years, experts at Lilly and Nvidia say AI will not only think up new drugs, but ones that humans could not create. There is one company featured today that is already well underway to doing this. We are talking about Insilico Medicine .

???????? Intersection of Biotech and AI

• They have developed AI platforms that utilize deep generative models, reinforcement learning, transformers, and other modern machine learning techniques for novel target discovery and the generation of novel molecular structures with desired properties.
• Insilico Medicine is developing breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system diseases, infectious diseases, autoimmune diseases, and aging-related diseases.

?? Innovation is a Global Event and Collaboration

Since 2015, Insilico Medicine has been actively developing generative AI platforms for biology, chemistry, and medicine utilizing a broad range of generative approaches ranging from generative adversarial networks (GANs), variational autoencoders (VAE), genetic algorithms, transformers, and many other approaches with algorithmic, experimental, and human-directed reinforcement learning.

?? AI Platforms will Accelerate and Improve Costs in Drug Development

Insilico Medicine's AI-designed drug ISM3412 has recently received FDA IND approval, a small molecule inhibitor of MAT2A for the potential treatment of MTAP deleted cancers designed with Insilico's generative AI platform.?

ISM3412 is a potentially best-in-class, orally available small molecule inhibitor of MAT2A that has demonstrated excellent drug-likeness with good solubility and permeability, good anti-tumor efficacy at low doses in animal models, and a favorable safety profile in preclinical studies. The molecule was designed using ligand-based AI-enabled drug design by Insilico's generative chemistry application, Chemistry42.?

This guest post is by Marina T Alamanou, PhD and her Newsletter ??, is about Science, Technology and AI Drug Discovery ??????????????????. Support the Author:

MetaphysicalCells

A newsletter about Science, Technology and AI Drug Discovery.

By Marina T Alamanou

Sample her Work:

• Japan and AI Drug Discovery Innovation
• AI-Based Drug Discovery Tools
• III: AI Drug Discovery Innovation

Let's now get into this deep dive.

Insilico Medicine: 10 Years of TechBio Innovation

An AI Drug Discovery Company Revolutionizing Drug Development

By Marina T Alamanou, PhD , April, 2024.

Quote:

“This first drug candidate that’s going to Phase 2 is a true highlight of our end-to-end approach to bridge biology and chemistry with deep learning. This is a significant milestone not only for us, but for everyone in the field of AI-accelerated drug discovery.”

Quote by Alex Zhavoronkov , PhD, Founder and CEO of Insilico Medicine.

Latest News On Insilico Medicine

?? At the American Association for Cancer Research (AACR) Annual Meeting 2024, happening April 5–10 2024 in San Diego, Insilico will show the latest fruits of their labor using AI in cancer drug discovery and development and will present five preclinical programs at poster presentations .??

?? Insilico Medicine to sponsor ARDD 2024 , the world's largest conference on aging research in the biopharmaceutical industry.

?? Insilico Medicine is collaborating with SRW Laboratories on longevity research with substantial laboratory robotics validation.

Insilico Medicine ??

For this incredible startup, there are a lot of salient details.

Insilico Medicine founded by Alex (Aleksandrs Zavoronkovs) Zhavoronkov , is a company that doesn’t need introductions. The legendary Insilico Medicine—together with Exscientia , Atomwise , Recursion Pharmaceuticals , Iktos and many more—they are all considered the global leaders in the AI drug discovery space, something like Neil Armstrong and Yuri Gagarin the two greats from spaceflight and space exploration. Back to earth now, these companies have been exploring the chemical space for “drug discovery missions” doing actually great work!

Insilico Medicine (Science Park, Hong Kong, New York) was effectively born ?? in 2014 at NVIDIA GTC—a global AI conference with a focus on DL for drug discovery—and combines genomics, big data analysis and DL for in silico drug discovery. Insilico’s AI platform, Pharma.AI , it's a fully integrated drug discovery software suite that can:

1. discover new targets with PandaOmics, enabling multi-omics target discovery and deep biology analysis to considerably reduce required time. PandaOmics now uses 1.9 trillion data points drawn from over 10 million samples (such as microarrays, RNA sequencing, and proteomes) and over 40 million documents (including patents, grants, publications, and clinical trial reports).
2. design new drugs with Chemistry42, to find novel lead-like molecules through automated ML de-novo drug design and scalable engineering platform,
3. predict the outcomes of clinical trials with inClinico, enabling to predict clinical trials success rate and recognize the weak points in trial design, while adopting the best practices in the industry, and
4. in particular for biologics they offer Generative Biologics, an advanced AI-powered platform that is capable of designing and optimizing different types of biologics including peptides, nanobodies and antibodies tailored for specific targets.

In a new paper in Nature Biotechnology (A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models ) Insilico Medicine describes step-by-step the process that undertook to develop INS018_055—a small-molecule TNIK inhibitor that is currently in phase 2 trials for the treatment of the lung disease idiopathic pulmonary fibrosis—by using its proprietary AI platform, PandaOmics, to both identify a target and come up with a drug candidate to treat the disease. INS018_055 , a protein kinase inhibitor like ISM042-2-048, is the first drug discovered and designed using AI to reach the phase I clinical trial milestone.

Read the Paper

Moreover, Insilico just presented their first demo of the PreciousGPT for aging research—Insilico's lineup of AI models aimed at enabling digital -omics experiments—that includes:

• Precious1GPT: a transformer-based model with aging clock functionality for aging-related pathology research with a simple transformer regressor and transformer classifier architecture,
• Precious2GPT: a compound model combining a transformer and a diffusion architectures with omic data generation capabilities, and
• Precious3GPT: a genuinely multimodal transformer-based model trained to emulate the workflow of case-control studies, with an emphasis on chemical perturbations. Precious3GPT is a

Insilico’s AI pharma collaborations

Insilico’s AI pharma collaborations so far have been the following:

• ?? In 2017, Insilico Medicine established a collaboration with GSK to discover novel biological targets and molecules. In 2020, Insilico also launched a preclinical research program focused on finding new treatments for brain cancer, and has brought on the former global program head of GSK’s computer-aided drug discovery unit to help run it.
• ?? In November 2020, Insilico Medicine announced that Merck KGaA, Darmstadt, Germany will be the first launch partner for its flagship generative chemistry AI platform Chemistry42, and that Merck will integrate Chemistry42 into its discovery pipeline to facilitate rapid and effective drug design. Chemistry42, core part of Insilico's Pharma AI drug discovery process, is a user-friendly platform that bridges AI and ML methods with domain expertise in the fields of medicinal and computational chemistry, for the design of novel small molecules with desirable physicochemical properties.
• ?? In 2020, it was announced that Insilico Medicine teamed up with Pfizer in a deal that will see Pfizer leverage Insilico's technology to identify drug targets for a variety of diseases. Pfizer by using Insilico's technology can speed up drug discovery—and possibly slim down drug development costs in the process.?
• ?? On January 11, 2022, Shanghai Fosun Pharma —focusing on major therapeutic areas, including oncology, immunology, the "4 hypers": hypertension, hyperlipidemia, hyperglycemia and hyperuricemia and their complications, as well as central nervous system—and Insilico Medicine entered into a collaboration agreement to advance the discovery and development of four biological targets, as well as the co-development of Insilico's QPCTL program (glutaminyl-peptide cyclotransferase-like protein). Under this agreement, Insilico will receive a total upfront payment of $13M.
• ?? On March, 24, 2022 , Insilico Medicine announced it has entered into a strategic collaboration with EQRx, a company committed to developing and delivering innovative medicines to patients at radically lower prices. Under this agreement, Insilico will apply its Pharma.AI platform to advance de novo small molecule design and generation with EQRx's clinical development and commercialisation expertise.?
• ?? Moreover, in 2022 Sanofi joined forces in a collaboration with Insilico Medicine (signing a strategic research worth up to $1.2 Billion). Under the terms of the agreement, the collaboration will leverage Insilico Medicine’s AI platform, Pharma.AI , to advance drug development candidates for up to six new targets.?
• ?? In September 12, 2023, Exelixis —an oncology company innovating next-generation medicines—and Insilico Medicine announced that they have entered into an exclusive license agreement granting Exelixis global rights to develop and commercialize ISM3091, a potentially best-in-class small molecule inhibitor of USP1, which has emerged as a synthetic lethal target in the context of BRCA-mutated tumors. Accordingly, Insilico granted Exelixis an exclusive worldwide license to develop and commercialize ISM3091 (and other USP1-targeting compounds) in exchange for an upfront payment to Insilico of $80M. Exelixis located in Alameda, California, is the producer of Cometriq, a treatment approved by the FDA for medullary thyroid cancer with clinical activity in several other types of metastatic cancer.
• ?? In 2023 , Insilico and Novo Nordisk signed a collaboration agreement that will help the Danish pharma identify targets against liver fibrosis. Novo Nordisk will utilize Insilico’s AI target discovery engine, PandaOmics, in conjunction with its own drug research and development expertise, to yield new target hypotheses of interest to Novo Nordisk.
• ?? In January 2024, Menarini Group and Insilico Medicine (and Stemline Therapeutics, Inc. a wholly-owned subsidiary of the Menarini Group) entered a global exclusive license agreement for novel KAT6 inhibitor for potential breast cancer treatment and other oncology indications. The novel molecule was designed by Insilico’s R&D team with the help of its Pharma Generative AI platform, to inhibit KAT6A and block endocrine receptor (ER) at the transcriptional level, giving it the potential to overcome resistance to endocrine therapies due to mutation or ligand-independent constitutive activation of ER. Under the terms of the agreement, Stemline will provide a $12M upfront payment to Insilico. The combined value of the deal, including all development, regulatory, and commercial milestones, is over $500M, followed by royalties up to double digits.?

Major Event

?? On June 29, 2023, Insilico Medicine Filed For Hong Kong IPO .

“Insilico Medicine did not disclose details of its IPO in its filing to the Hong Kong stock exchange on Tuesday, although a report by local newspaper South China Morning Post said it’s planning to raise $200M, citing unnamed sources. The company had previously filed confidentially for a U.S. IPO to raise around $300M, Bloomberg News reported in November 2021. Insilico Medicine didn’t immediately respond to a comment request.”

• June, 29, 2023 - Hong Kong IPO.

Insilico Medicine: Time and Money

2023 was undoubtedly an important year for AI Drug Discovery and Insilico Medicine (AI’s evolving role in drug discovery and development in 2023 ) since:

• In June 2023: Insilico Medicine’s AI-drug entered phase 2 study.

INS018_055 was the first AI-discovered drug to reach phase 2 trials and with traditional methods the drug candidate would have cost more than $400M and would have taken up to six years to develop. But with generative AI, it reached those objectives at one-tenth (1/10) of the cost and in one-third (1/3) of the time!

• In August 2023: Generative AI tool boasts 79% accuracy in predicting clinical trial outcomes. Insilico Medicine announced that its generative AI tool InClinico (that uses transformer-based AI models and multimodal data sources, including text, omics, trial design and drug properties) reached a significant breakthrough in predicting clinical trial outcomes, after the company trained the system on more than 55,600 phase 2 clinical trials. Insilico also noted that the platform could serve as a valuable tool for investors, supporting a 35% 9-month return on investment in a virtual trading portfolio.

However, in the article “AI in Drug Discovery in China, Hype or Hope?” published by EqualOcean, the author points out to the importance of valuable clean data (literature, large public databases and proprietary databases) but also to the importance of the experimental validation of AI algorithms in this data-intensive industry. He is actually saying that apart the problem we have with the dirty data (such as skewed data sets and biased data that the scientists need to explain that to the algorithms), there is also the problem with the experimental validation of the AI algorithms, that is impeded by two aspects:?

1. firstly, there is no universal protocol to follow about what correct validation should be, in another way to say, there is no standard in parallel when AI delivers new compounds, and?
2. secondly, the problem lies in the progress of validation itself.

In other words, we use data to train an algorithm and generate novel AI compounds, and for that reason the data set we use is intrinsically related to the numerical performance and the prospective performance of the method/model itself. Therefore, the so-called validation of the AI algorithms could just be replication of the construction process. Thereby, the scientists need to lead their own way to validate their AI algorithms/AI-generated molecules, leveraging their expertise. At the end of the day, wet-lab experiments, biological assays and clinical trials are also needed to ensure that the AI generated molecules are active both in vivo and in vitro.?

And that requires time as Alex Zhavoronkov PhD, Founder and CEO of Insilico Medicine told EqualOcean ??:

“Unlike in other areas where AI generates pictures, music or text, you get validation almost immediately because you get almost immediate feedback by looking at the picture, listening to music and reading the text.

In biology, it is not like that and you have to wait”.

In any case apart the problems with dirty data and experimental validation of algorithms, in China ?? for example effort has been made in AI drug discovery and there have been some demonstrated successful cases showing the validation of AI algorithms in drug discovery, like with the following companies: Accutar Biotech (AC0682, AC0176), Galixir (unknown), MindRank.AI (MDR001, EMDR001), Nutshell Therapeutics (NST001, NST004) and off course Insilico Medicine (ISM001-055, ISM012-077, ISM004-1057D, undisclosed).

NVIDIA and Insilico Medicine

?? Insilico was a premier member of NVIDIA Inception , a free program that provides cutting-edge startups with technical training, go-to-market support and AI platform guidance.

?? The company uses NVIDIA Tensor Core GPUs in its generative AI drug design engine, Chemistry42, to generate novel molecular structures—and was one of the first adopters of an early precursor to NVIDIA DGX systems in 2015.

?? Moreover, at Insilico they’re now using NVIDIA BioNeMo to accelerate the early drug discovery process with generative AI.

For more Quicker Cures: How Insilico Medicine Uses Generative AI to Accelerate Drug Discovery

by Renee Yao , that leads global healthcare AI startups at NVIDIA.

Insilico Medicine and Quantum Computing

Insilico Medicine, announced in a study just published that it successfully combined generative AI and quantum computing to accelerate drug discovery in order to explore lead candidate discovery in drug development. In particular, they demonstrated the potential advantages of quantum generative adversarial networks in generative chemistry, by an implicit GAN for small molecular graphs, with a variational quantum circuit (VQC) as the noise generator.

Building on these findings, Insilico scientists plan to integrate the hybrid quantum GAN model into Chemistry42, the company's proprietary small molecule generation engine, to further accelerate and improve its AI-driven drug discovery and development process.

Insilico’s Valuation ??

?? Insilico Medicine was valued at approximately $895M after raising $95M in July 2022, from the leading Chinese healthcare-focused firm Qiming Venture Partners and Singapore-based billionaire Eduardo Saverin's B Capital.

?? On August 10, 2022, Insilico Medicine raised additional $35M from Prosperity7 Ventures, a global VC fund by Saudi Arabia’s giant Aramco.

?? Insilico Medicine has raised a total of $401.3M.

Robots

The company also has plans to launch a fully automated AI-driven robotics lab for drug discovery.

In particular, Insilico Medicine launched a 6th generation Intelligent Robotics Drug Discovery Laboratory, in Suzhou BioBAY Industrial Park in December 2022, which is a fully automated AI-powered robotics laboratory that performs target discovery, compound screening, precision medicine development and translational research.

So far, the so-called “5th generation robotics laboratories” were full automation labs with no human bias or influence, connecting multiple processes and generating high-quality data that can be used for ML. Insilico's lab (the 6th generation) takes this process one step further by incorporating AI in decision-making and by integrating AI with automation, robotics and biological capabilities to enable a new generation of intelligent robotic labs.

The Intelligent Robotics Lab forms a closed loop by combining Pharma.AI with fully automated biological experiment functional modules. In particular, PandaOmics of Pharma.AI predicts novel targets for specific diseases and the robotics lab conducts early-stage drug discovery experiments (like target validation, high-throughput screening, hit-to-lead optimization, lead-to-preclinical candidate confirmation and translational research) through six fully automated modules including sample management and quality control, compound management, automated cell culture, high-throughput screening, high-content cell imaging and next-generation sequencing. Finally, all data generated by the Intelligent Robotics Lab complement and expand Insilico's existing data resources.

“Insilico's robotics lab has an AI brain, an automated machine body, and the limbs of various complex robots. The AI brain has been trained and verified through Insilico projects and has learned from years of experience collaborating with global pharmaceutical companies. It can carry out systematic learning based on the information provided, and assist in the decision-making of target discovery and identification. In the Intelligent Robotics Lab, the AI brain will propose potential targets and design automated experiments and workflows based on experimental results."

Alex Zhavoronkov, PhD, Founder and CEO of Insilico Medicine

“We want companies and fellow cancer researchers to see the remarkable value of AI in target and biomarker discovery and de novo drug design in developing new cancer drugs, driven by a team of cross-trained AI experts and drug developers. We hope they will leave with assurance that Insilico’s AI platform can be used to create highly optimized, potent, and efficacious molecules that can serve as potentially best-in-class therapeutic options in treatment-resistant cancers and as promising candidates for partnering.”?

Michelle Chen, PhD , chief business officer at Insilico Medicine,told GEN

Insilico Medicine and Innovation

Moreover, regarding the study published in Nature Biotechnology that presents the entire journey of INS018_055 from AI algorithms to Phase II clinical trials for the first time, Insilico developed a PaperGPT system based on ChatGPT-4 Turbo and internal LLM that provides answers related to the paper via chat functionality. For example:??

• “How notable is this study and what is important about it?”
• “Thank you for your question regarding the significance and importance of our study. The importance of this study lies in several key aspects:

To conclude, I nsilico Medicine was named Top Biotech Company in Fast Company’s 2024 World’s Most Innovative Companies List and has just appointed this month Keith Mikule, PhD, as Vice President (VP) of Business Development . Based in Boston, Dr. Mikule will work closely with Alex Zhavoronkov, PhD, founder and CEO, Feng Ren , PhD, co-CEO and Chief Scientific Officer, and Michelle Chen, PhD, Chief Business Officer, to drive business development activities and operation strategies to support Insilico's continued growth.

Thank you for your time ??

?? References: AI Drug Development Startups

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