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Causaly Raises $60M to Fuel Generative AI-Powered Drug Discovery

In a significant boost to the field of drug discovery, Causaly, a pioneering AI company, has secured an impressive $60 million in funding. The investment, led by prominent venture capital firms, underscores the potential of generative AI-powered technology in revolutionizing the process of identifying new drugs and advancing medical research. Causaly’s innovative approach has the potential to accelerate the development of life-saving treatments and transform the landscape of healthcare as we know it.

ICONIQ Growth, a growth-stage fund associated with the well-known investment firm, is leading the funding round for Causaly. Previous investors including Index Ventures, Marathon Venture Capital, EBRD, Pentech Ventures, and Visionaries Club are also participating. With this funding round, Causaly has now raised a total of $93 million, although the company is not disclosing its valuation.

Traditional drug discovery is a time-consuming and costly process that involves extensive experimentation and analysis of vast amounts of data. Causaly’s generative AI technology aims to streamline this process by leveraging the power of machine learning and natural language processing to analyze scientific literature and extract valuable insights. This enables researchers to identify potential drug candidates and understand the underlying mechanisms of diseases more efficiently.

 

Despite being just over six years old, Causaly already works with major players in the pharmaceutical and medical research space, including Gilead, Novo Nordisk, Regeneron, the Food and Drug Administration, and the National Institute of Environmental Health Sciences. These organizations utilize Causaly’s cloud-based platform for various stages of drug development, such as identifying research targets, determining specific biomarkers, and better understanding diseases for effective pharmaceutical and therapeutic solutions.

By leveraging Causaly’s platform, the typically lengthy process of taking an idea from target to the end of trials, with an estimated duration of 10-15 years, can be significantly reduced to just a few years. This not only saves time but also reduces the budget required for the drug development process.

Furthermore, Causaly’s platform focuses on enabling faster modeling and computations, allowing for quicker analysis of different chemical permutations and their interactions in different environments. This ultimately aims to minimize false starts and dead ends, which are common hurdles in the drug discovery process.

 

According to Kiachopoulos, the failure rate for drugs entering the market is around 90%, with only one out of every ten drugs succeeding. Developing these drugs typically costs between $1 billion and $2 billion. However, advancements in AI are providing an opportunity to improve this inefficiency. AI technology can analyze complex data in real time and even interpret images, enhancing the understanding of cell results. As a result, AI drug discovery has become a popular field among both startups and investors. For example, Recursion, an AI-based drug discovery startup, recently secured a $50 million investment from Nvidia, highlighting the significant amount of money being invested in this space.

When speaking with Kiachopoulos, he explained that his startup, Causaly, does not face significant compute power issues. This is due to the design of the platform, which was developed before the emergence of large language models like Chat GPT. While they are considering incorporating more AI capabilities into future products, it will not have a significant impact on their compute needs.

Querying AIs can be made easier with LLM. We are currently working on improving this feature. The great thing is, you don’t have to start from scratch when training an LLM. We can take what already exists and fine-tune it, which requires fewer computing resources.

 

It’s important to note that Causaly does not focus on drug discovery itself. Instead, we provide tools to other organizations in the field. This sets us apart from other startups.

Our solution is designed to assist biomedical teams, but we are not developing our own therapeutics. We operate as a SaaS-based platform, training our scientists to maximize the potential of our AI. Through strong partnerships, we are not in competition, nor do we have any plans to be.

With this latest round of funding, Caroline Xie from ICONIQ Growth is joining our board.

Caroline Xie, a general partner at ICONIQ Growth, believes that AI is driving a turning point in the sciences. She sees Causaly as a leader in providing scientists with a trusted and verifiable way to harness this power. The platform is uniquely powerful and user-oriented, delivering significant productivity gains and commercial impact for major pharmaceutical companies. ICONIQ Growth is excited to support the Causaly team as they revolutionize scientific evidence discovery, visualization, and collaboration across multiple industries.

Carlos Gonzalez-Cadenas, a partner at Index Ventures, recognizes Causaly as a real-life application of AI that empowers scientists to tackle major challenges. Already adopted by leading pharmaceutical companies, Causaly is actively accelerating biomedical research. The technology has made a significant impact on R&D, as evidenced by the increasing investment from research organizations.

 

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