Israeli agri-tech startup Fermata secures funding for AI-powered farming solutions
Israeli startup Fermata, founded in 2020 by bioinformatics expert Valeria Kogan, is using AI and computer vision to monitor greenhouse crops for diseases and pests. The company’s software works with standard cameras, capturing images of plants twice a day and alerting farmers to potential infestations via an app. Initially considering robotic solutions, Kogan shifted focus after consulting with farmers, realising that simpler camera-based monitoring was more effective.
Based in Israel, Fermata has gained traction by prioritising farmer needs and keeping its AI training in-house, improving model accuracy. Partnering with major agricultural firms like Bayer and Syngenta, the company has deployed over 100 cameras and continues to expand. The startup recently secured a $10 million Series A investment from Raw Ventures, its existing investor, to scale operations and work towards profitability by 2026.
Plans for growth include strengthening the sales team and expanding beyond greenhouse tomatoes into new crops. Despite AI’s previous struggles in agriculture, Fermata’s practical approach and farmer-centric model have helped it carve a niche in the industry.
Can AI really transform drug development?
The growing use of AI in drug development is dividing opinions among researchers and industry experts. Some believe AI can significantly reduce the time and cost of bringing new medicines to market, while others argue that it has yet to solve the high failure rates seen in clinical trials.
AI-driven tools have already helped identify potential drug candidates more quickly, with some companies reducing the preclinical testing period from several years to just 30 months. However, experts point out that these early successes don’t always translate to breakthroughs in human trials, where most drug failures occur.
Unlike fields such as image recognition, AI in pharmaceuticals faces unique challenges due to limited high-quality data. Experts say AI’s impact could improve if it focuses on understanding why drugs fail in trials, such as problems with dosage, safety, and efficacy. They also recommend new trial designs that incorporate AI to better predict which drugs will succeed in later stages.
While AI won’t revolutionise drug development overnight, researchers agree it can help tackle persistent problems and streamline the process. But achieving lasting results will require better collaboration between AI specialists and drug developers to avoid repeating past mistakes.
AI advances ovarian cancer detection and speeds up blood tests
AI is revolutionising medical testing, including early detection of ovarian cancer and faster identification of life-threatening infections like pneumonia. Researchers are leveraging AI to interpret complex patterns in blood tests, improving accuracy and speed in diagnosing diseases.
Dr Daniel Heller’s team at Memorial Sloan Kettering Cancer Center developed a nanotube-based blood test that uses AI to detect ovarian cancer earlier than traditional methods. Despite limited data, the technology shows promise, with further studies underway to enhance its effectiveness and expand its application.
AI is also transforming infectious disease diagnosis. California-based Karius uses AI to identify pneumonia-causing pathogens within 24 hours, cutting costs and improving treatment outcomes. Meanwhile, AstraZeneca‘s Dr Slavé Petrovski developed a platform that identifies over 120 diseases from United Kingdom biobank data. However, challenges persist, including a lack of data sharing among researchers, prompting calls for more collaborative efforts.
Cradle secures $73 million to advance AI-powered protein design
Biotech startup Cradle has raised $73 million to expand its labs and team, aiming to make AI-powered protein design more accessible. Founded in 2022, the company uses language models to analyse proteins, often described as “an alien programming language,” to suggest modifications that improve functionality, such as heat resistance or manufacturability.
Cradle’s software has gained traction among biotech and pharmaceutical companies by reducing the time and cost of experimental rounds, which can be both expensive and unpredictable. Its simple SaaS model eliminates concerns about royalties or intellectual property, offering a streamlined approach compared to competitors that co-develop drugs or processes.
Despite being a software provider, Cradle maintains a laboratory in Amsterdam to validate protein designs and build datasets to refine its models. The latest funding, led by IVP with participation from Index Ventures and Kindred Capital, will support lab expansion and further hiring. CEO Stef van Grieken aims to scale Cradle’s tools to reach a million scientists worldwide.
Google funds AI-driven scientific breakthroughs
Google has announced a $20 million fund, with an additional $2 million in cloud credits, to support researchers using AI to tackle complex scientific challenges. The initiative, unveiled by Google DeepMind CEO Demis Hassabis at the AI for Science Forum in London, is part of Google’s broader strategy to foster innovation and collaboration with academic and non-profit organisations globally.
The funding will prioritise interdisciplinary projects addressing challenges in fields such as rare disease research, experimental biology, sustainability, and materials science. Google plans to distribute the funding to approximately 15 organisations by 2026, ensuring each grant is substantial enough to drive impactful breakthroughs. The programme reflects Google’s aim to position itself as a key partner in advancing science through AI, building on successes like AlphaFold, which recently earned DeepMind leaders a Nobel Prize in Chemistry.
The move aligns with a growing trend among Big Tech firms investing heavily in AI-driven research. Amazon’s AWS recently committed $110 million to similar grants, underscoring the race to attract leading scientists and researchers into their ecosystems. Hassabis expressed hope that the initiative would inspire greater collaboration between the private and public sectors and further demonstrate AI’s transformative potential in science.
AI-powered breakthrough could revolutionise drug development
Nvidia-backed biotech firm Iambic Therapeutics has introduced Enchant, an AI model that aims to reduce the time and cost of drug development. Enchant, trained on extensive pre-clinical data, is designed to predict a drug’s early performance with impressive accuracy. In Iambic’s studies, Enchant achieved a 0.74 accuracy score in predicting drug absorption in the human body, compared to previous models which peaked at 0.58. This predictive power could help pharmaceutical companies identify promising drugs sooner, significantly cutting down on failed late-stage trials.
According to Iambic’s co-founder Fred Manby, Enchant could potentially slash development costs by half, as researchers could more accurately assess a drug’s success at the earliest stages. Nobel laureate and Iambic board member Frances Arnold also highlighted Enchant’s unique capabilities, noting that unlike models like Google DeepMind’s AlphaFold, which focus on molecular structure, Enchant evaluates pharmacokinetic and toxicity properties crucial to drug success.
With Enchant, Iambic is poised to set a new standard in the pharmaceutical industry by addressing some of the biggest hurdles in drug development, including high costs and late-stage failures. The AI technology’s rollout could mark a major shift, making drug discovery both faster and more efficient for a variety of treatments.
AstraZeneca invests $18 million in Immunai’s AI technology
AstraZeneca has struck an $18 million deal with biotechnology firm Immunai Inc. to use its AI model of the immune system, which is intended to improve the efficiency of specific cancer drug trials. This collaboration aligns with AstraZeneca’s broader strategy to harness artificial AI for drug discovery and development, building on a previous $247 million agreement with US-based Absci to create cancer-fighting antibodies.
Founded in 2018, Immunai utilises single-cell genomics and machine learning to decode the immune system and enhance the development of new therapeutics. This collaboration will concentrate on optimising clinical decision-making processes, including dose selection and biomarker identification, by leveraging Immunai’s advanced platform.
AstraZeneca will initially gain access to Immunai’s AI tools to support its cancer research efforts, with the option to extend the collaboration down the line. This flexibility allows AstraZeneca to evaluate the effectiveness of Immunai’s technology in enhancing drug trial efficiency and potentially integrate additional capabilities as the partnership progresses. According to Iker Huerga, AstraZeneca’s chief data scientist for oncology R&D, this collaboration is expected to provide valuable insights into the immune system and improve clinical decision-making processes, such as dose selection and biomarker identification. The partnership underscores AstraZeneca’s commitment to leveraging cutting-edge technologies to advance cancer treatment and drug development.