Latest News On TechBio 🍍
Google DeepMind and the Fleming Initiative launched a 3️⃣-year academic fellowship at Imperial College London 🇬🇧 to support early-career researchers applying AI to antimicrobial 🦠 resistance.
✅ Insilico Medicine new funding, new publication and an interview
Last week (June 16, 2025), Insilico Medicine announced the close of its Series E financing round at a total of around 💲1️⃣2️⃣3️⃣M million (Insilico Medicine Closes Oversubscribed Series E, Bringing Total Funding to $123 Million). The funding was led by the private equity fund of Value Partners Group (HKG:0806), one of Asia’s largest independent asset management firms, alongside continued support from Insilico’s existing global backers. Additional funding came from new investors including Grand Leader.
Moreover, on 11 Insilico announced that the first patient has been dosed in a global multicenter phase 1 clinical trial (NCT06414460) to evaluate ISM3412, a potentially best-in-class, AI-empowered MAT2A inhibitor with novel structure, in patients with locally advanced and metastatic solid tumors (Insilico Medicine completes first-in-patient dosing of ISM3412, the novel MAT2A inhibitor for the treatment of locally advanced/metastatic solid tumors).
🔖 ISM3412 is an orally bioavailable, highly selective, and potent MAT2A (methionine adenosyltransferase 2A) inhibitor, empowered by Insilico’s proprietary generative chemistry platform Chemistry42, that targets cancers with MTAP deletion that is a common genetic alteration found in multiple solid tumors, including non-small cell lung cancer (NSCLC), pancreatic cancer, and bladder cancer.
🔖 MTAP deletions create a synthetic lethality vulnerability that ISM3412 exploits by inhibiting MAT2A, reducing levels of S-adenosylmethionine (SAM)—a molecule essential to cell function—and selectively killing MTAP-deficient cancer cells while sparing healthy cells.
Currently, at Insilico they have 30+ programs, discovered with continuously evolving generative AI, with hundreds of experimentally-validated AI models. For example, 🔥 Insilico’s 🆕 publication (on Nature Medicine) is reporting positive Phase IIa trial results for rentosertib a first-in-class TNIK inhibitor discovered using generative AI for the treatment of idiopathic pulmonary fibrosis (IPF) (A generative AI-discovered TNIK inhibitor for idiopathic pulmonary fibrosis: a randomized phase 2a trial).
Rentosertib is the first 🥇 clinical-stage investigational drug in which both the novel biological target 🎯 (TNIK) and the molecule 🏹 were discovered by generative AI.
Now, in a 1️⃣2️⃣-week Phase IIa study (N=71 IPF patients), rentosertib has demonstrated encouraging safety, biomarker, and efficacy results.
Alex’s Aliper, Co-founder & President of Insilico Medicine 👉 Interview 🎙️
Alex Aliper, Co-founder & President of Insilico Medicine, discusses why China 🇨🇳 is a stand-out market for pharmaceuticals and biotech, and says the company plans to invest in research to accelerate business growth and drug development.
He speaks with Annabelle Droulers on the sidelines of the SuperAI Conference in Singapore on "Bloomberg: The Asia Trade". (Source: Bloomberg)
✅ Lantern Pharma remarkable clinical observations for a patient in HARMONIC
Lantern Pharma Inc (NASDAQ: LTRN) announced on June 16, 2025 remarkable clinical observations for a patient in Lantern’s Phase 2 HARMONIC™ clinical trial (Lung Cancer Patient in Lantern Pharma’s Harmonic Trial Shows Durable Complete Response in Target Cancer Lesions with Survival Continuing for Nearly Two Years). A 7️⃣0️⃣-year-old never-smoker 🚭 with advanced non-small cell lung cancer (NSCLC) has achieved a durable complete response in their target cancer lesions following treatment with LP-300 in combination with standard-of-care chemotherapy. ✴️ Importantly, the patient continues to show sustained survival benefits after nearly two years.✴️
The patient, who had previously failed three lines of prior therapy including Keytruda (pembrolizumab) with chemotherapy, radiation therapy, and the EGFR inhibitor Tagrisso (osimertinib), initially demonstrated a partial response with a 57% reduction in tumor volume after completion of the HARMONIC™ lead-in cohort enrollment in Q3 of 2024. Subsequently, the patient demonstrated a complete response in the target cancer lesions, specifically the lung and adrenal gland lesions by Q1 of 2025.
✴️ This type of complete response in the target cancer lesions is atypical for this advanced and recurrent NSCLC after multiple rounds of therapy.✴️
📢 New Publication Alert
Lantern’s latest peer-reviewed article published in Frontiers in Oncology "Clinical outcomes of DNA-damaging agents and DNA damage response inhibitors combinations in cancer: a data-driven review", presents one of the most comprehensive, quantitative reviews to date of clinical outcomes for combinations of DNA-damaging agents (DDAs) and DNA damage response inhibitors (DDRis) across multiple cancer types. While both groups of agents show promise individually, DDAs are limited by tumor resistance, and DDRis are limited by specific genetic context.
The article co-authored by Lantern’s team: Rick Fontenot, Dr Neha B., Dr. Kishor Bhatia, Dr. Reggie Ewesuedo, Dr. Marc Chamberlain, and Panna Sharma, serves as a foundation for applying ML and biomarker-driven strategies to predict and optimize synergistic DDA-DDRi combinations (by dividing them into two sections: PARP and non-PARP inhibitors)—informing both future clinical trial design and precision therapy development.
✅ Key 🗝️ Highlights from analysis of 2️⃣2️⃣1️⃣ clinical trial arms (221 DDA-DDRi combination-arm trials involving 22 DDAs and 46 DDRis) are:
📍PARP-DDAs remain the most studied combinations.
📍ATR and WEE1 inhibitors showed strong synergy with platinum-based DDAs.
📍Biomarker-driven responses were key to successful outcomes.
At Lantern, these findings directly support the development of smarter, AI-guided combinations—particularly as they advance LP-184, their DNA-damaging agent, through clinical trials in genomically defined tumors. Insights from this work help guide more targeted, data-informed approaches to future DDA-DDRi combinations.
✅ Recursion Pharmaceuticals is laying off a fifth of its workforce
Recursion Pharmaceuticals is laying off a fifth of its workforce (2️⃣0️⃣% workforce reduction is set to cost Recursion around 💲1️⃣1️⃣ million in severance fees and related costs) in connection with a previously announced streamlining of the AI biotech’s pipeline (Recursion lays off 20% of staff in wake of pipeline cutbacks). The biotech entered 2025 with around 8️⃣0️⃣0️⃣ employees as a result of “rapid headcount growth” tied to its acquisition of Exscientia in 2024
Recursion Pharmaceuticals (RXRX) just ended (Sat, June 21, 2025) the recent trading session at 💲5️⃣, 0️⃣3️⃣, demonstrating a -1.57% change from the preceding day's closing price. This move lagged the S&P 500's daily loss of 0.22%. Meanwhile, the Dow gained 0.08%, and the Nasdaq, a tech-heavy index, lost 0.51% ➡️ Recursion Pharmaceuticals (RXRX) Declines More Than Market: Some Information for Investors.
✳️ FutureHouse: Demonstrated end-to-end scientific discovery with a multi-agent system
As I already mentioned last month (May 15, 2015) ➡️ FutureHouse, an ambitious nonprofit dedicated to building an AI Scientist, has launched the FutureHouse Platform, giving researchers everywhere access to superintelligent AI agents built specifically to accelerate scientific discovery and redefine how we explore biology, chemistry, and medicine (FutureHouse Unveils Superintelligent AI Agents to Revolutionize Scientific Discovery).
The FutureHouse Platform introduces 4️⃣ deeply specialized AI agents:
Crow is a generalist agent, ideal for researchers who need quick, high-quality answers to complex scientific questions.
Falcon, the most powerful literature analysis tool in the lineup, conducts deep reviews that draw from vast open-access corpora and proprietary scientific databases like OpenTargets.
Owl, formerly known as HasAnyone, answers a surprisingly foundational question: Has anyone done this before?
Phoenix, still in experimental release, is designed to assist chemists.
Subsequently (May 20, 2025), they announced their first major discovery of a promising 🆕 treatment (ripasudil) for dry dry age-related macular degeneration (AMD), a major cause of blindness 👁️🗨️. In particular, their agents generated the hypotheses, designed the experiments, analyzed the data, iterated, even made figures for a manuscript, a first-of-a-kind in the natural sciences, in which everything that needed to be done to write the paper was done by AI agents, apart from actually conducting the physical experiments in the lab and writing the final manuscript.
They also introduced Robin, the first multi-agent system that fully automates the in-silico components of scientific discovery, which made this discovery. Robin is a multi-agent system that uses Crow, Falcon, and Finch, the agents on their platform, to generate novel hypotheses, plan experiments, and analyze data.
By asking Robin to find a new treatment for dry age-related macular degeneration, Robin considered the disease mechanisms associated with dry AMD, proposed a specific experimental assay that could be used to evaluate hypotheses in the wet lab, and proposed specific molecules to test.
Fast forward ⏩ (after 10 weeks: from day 1 to last day), Robin identified Ripasudil, a Rho Kinase inhibitor (ROCK inhibitor) that is approved in Japan for several other diseases, which seems very promising as potential treatment for dry AMD (no one has proposed using ROCK inhibitors to treat dry AMD so far ).
Furthermore, on June 1, 2025 FutureHouse released a 24B open-weights reasoning model, ether0, that has been trained on tasks in chemistry ⚗️ (ether0: a scientific reasoning model for chemistry), and it is particularly good at designing drug-like molecules. It takes questions in natural language, reasons in natural language, and answers with molecules. Ether0 is still a prototype and is now available as a tool for scientific agents on their platform and is available for download on Hugging Face.
✳️ Medable: new Partner Program and a digital-first Long-Term Follow-Up model for cell and gene therapy trials
On June 10, 2025, Medable unveiled its 🆕 Partner Program, designed to empower contract research organizations (CROs) and other partners with generative AI-driven, self-service eCOA build capabilities for digitally enabled clinical trials. Leveraging the Medable platform, the program eliminates traditional bottlenecks for CROs to accelerate timelines by 50% or more, while delivering administrative and financial benefits, including straightforward, up-front pricing (Medable Launches Partner Program for Faster Clinical Trial Startup, Greater Control, and Transparent Pricing).
Medable’s Partner Program allows CROs to choose from three models – self-service, managed-service, or a hybrid of both support options. It offers pricing tools, demo support for bid defense meetings, and a portfolio content library to enable reuse and scale.
Moreover, on May 28, 2025 Medable introduced its digital-first Long-Term Follow-Up (LTFU) model for cell 🧫 and gene 🧬 therapy (CGT) trials, that reduces the burden on patients and sites involved in complex CGT trials and enhances scientific integrity with sustainable data capture across the FDA-required 15-year follow-up period for certain CGTs, including those using genome-editing techniques like CRISPR-Cas9 (Medable Introduces Long-Term Follow-Up Model for Cell & Gene Therapy (CGT) Trials to Reduce Costs and Improve Patient Access).
Medable Inc, that is a leading software provider for decentralized clinical trials and eCOA technology, also announced this month its next-generation digital oncology trial offering specifically designed to reduce operational complexity for sites and sponsors while meeting vulnerable cancer patients and their caregivers where they are with accessible (Medable Releases New Digital Oncology Trial Offering to Reduce Complexity for Sites, Sponsors, Patients, and Caregivers).
✳️ DeepSeek recruits medical data labelers
DeepSeek Recruits Medical Data Labelers to label data and reduce hallucinations 🤯 in its diagnostic models:
The Chinese AI startup DeepSeek is hiring interns with medical backgrounds and AI experience to label medical data for 5️⃣0️⃣0️⃣ yuan per day.
• This initiative aims to improve the use of DeepSeek's AI models in hospitals, which are already being used by at least 3️⃣0️⃣0️⃣ hospitals in China for clinical diagnostics and medical decision support.
🟣 Sesen launches AI-assisted translation and localization for clinical trials
On June 9, 2025, Sesen, a next-generation language services company purpose-built to meet the complex demands of the life sciences industry, was launched to provide AI-assisted translation and localization for clinical trials, labeling, and regulatory submissions (Sesen Launches with a Singular Mission: Advancing Life Sciences Globally Through Specialized Language Solutions).
Specializing exclusively in translation, localization, and AI-enhanced linguistic solutions for pharmaceutical, biotechnology, medical device, CRO, and regulatory organizations, Sesen combines industry expertise with cutting-edge technology to deliver fast, accurate, and fully compliant multilingual communications across 1️⃣5️⃣0️⃣+ languages. At the core of its offering is SesenGPT, a proprietary AI engine trained on life sciences terminology and optimized for medical and regulatory content.
🟣 Bayer and Scientist.com signed a multi-year extension
Bayer AG Innovation Procurement and Scientist.com have signed ✒️ (June 16, 2025) a multi-year extension that elevates Scientist.com to Bayer’s preferred global channel for sourcing external R&D services (Bayer Innovation Procurement Expands Use of Scientist.com’s AI-Powered Platform for Global R&D Procurement Orchestration). The alliance began in 2015, when Bayer adopted Scientist.com’s digital marketplace to streamline and control long-tail spend in preclinical research.
With the expansion, Scientist.com’s platform will support Bayer across the entire R&D value chain, including:
✴️ Strategic preclinical supplier management, with guided buying, rate-card compliance, and performance tracking.
✴️ Clinical development services, offering unified workflows for study execution, biomarker analysis, and central laboratory capabilities.
✴️ Real-world evidence, data analytics, health economics, and market access solutions, providing rapid access to top-tier data partners.
✴️ Crop science research, including specialized agriscience testing and regulatory studies.
🟣 S. Korea announced InnoCORE Postdoctoral Fellowship Program
On June 16, 2025, South Korea announced a major national initiative to enhance its global competitiveness in AI-convergent science and technology (AI+S&T) by launching a large-scale international postdoctoral recruitment program (Korea Launches Global AI+S&T Postdoctoral Fellowship). The Ministry of Science and ICT (MSIT), in collaboration with the country's 4️⃣ premier science and technology institutes-KAIST, GIST, DGIST, and UNIST-has officially unveiled the InnoCORE Postdoctoral Fellowship Program, a global initiative aiming to recruit 4️⃣0️⃣0️⃣ outstanding 🏇 postdoctoral 🎓 researchers.
🍉 Fauna Bio launched Fauna Brain™
Fauna Bio, a biotechnology company improving human health by leveraging animal genomics, announced on June 16, 2025 the launch of Fauna Brain™, a proprietary AI platform that represents a major evolution of Fauna Bio’s Convergence™ discovery, that is a multi-agent AI system that autonomously executes complex research tasks traditionally requiring expert teams (Fauna Bio Launches Fauna Brain™ AI Platform to Accelerate Drug Discovery Inspired by Nature’s Most Resilient Species). These include ➡️ identifying and scoring drug targets, ➡️ synthesizing supporting evidence, and ➡️ generating detailed, literature-backed concept sheets that include mechanistic rationale and risk-benefit analyses. By integrating Fauna’s internal datasets with public databases, and scientific literature, the system dramatically reduces time and cost across discovery workflows.
Early results showed that Fauna Brain can score a single target 🎯 in as little as 2️⃣.5️⃣ minutes at an average cost of ~💲0️⃣.0️⃣1️⃣. Moreover, it can screen multiple targets in parallel which even further reduces the time needed to screen the thousands of candidates. This efficiency has enabled Fauna Bio to explore far more targets, faster, and at a fraction of traditional R&D costs.
Fauna Brain is powered by Convergence™, Fauna’s broader AI platform that identifies and enriches druggable human targets based on comparative genomics insights from mammals with extreme phenotypes, such as hibernators, regenerators, and species resistant to fibrosis, cancer, or metabolic dysfunction. The system integrates data from 292 species, 24 tissues, and 21 time points, supported by more than 46 billion sequence reads and thousands of transcriptomes, proteomes, and epigenomes.
Moreover, Fauna Bio is part of the Zoonomia Consortium, featured in Science, which produced a whole-genome alignment across 2️⃣4️⃣0️⃣ mammals, giving Fauna Brain a unique vantage 💪 point for discovering conserved protective mechanisms often missed in human-only datasets.
In fact, by using its Convergence AI engines, Orca, Centaur, and Pegasus, Fauna Brain identifies protective signatures in animals, maps them to human disease pathways, and identifies the 🔝 therapeutic targets to maximize efficacy, druggability, and safety. This approach has already demonstrated translational potential: 2️⃣ Fauna Brain-prioritized targets have progressed into funded 💰 research collaborations with a large pharma partner. On December 21, 2023, Fauna Bio announced a multi-year agreement with Eli Lilly to apply Fauna's Convergence™ AI platform to support preclinical drug discovery efforts in obesity.
🍉 Molecule.one wins 💲1️⃣M in Standard Industries AI Challenge
Molecule.one won 💲1️⃣ in Standard Industries AI Challenge (Polish biotech Molecule.one wins $1M in Standard Industries and W. R. Grace & Co. AI Challenge for advancing AI-assisted molecular synthesis), in order to leverage AI to revolutionize fine chemical manufacturing.
Molecule.one in Poland utilizes AI to predict chemical reactions with unprecedented accuracy. They offer
Custom Synthesis supported by their proprietary chemistry tech stack and data generation capabilities, synthesizing anything from a single compound to whole libraries.
SpaceM1, a virtual library using generative models for chemistry, supported by the world’s largest chemical reaction dataset, including >100,000 proprietary reactions from their HTE Lab (the HTE lab has conducted over 100,000 reactions to date to expand their reaction conditions prediction capabilities). You can access >1T de novo drug-like molecules with unmatched diversity of chemistry and building blocks that could be synthesised in 2-6 weeks based on success-fee.
Not only are they creating this library, but they are putting it to use in terms of actually selling compounds that aren’t accessible from the big vendors (e.g. Enamine, WuXi) or marketplaces (e.g. Molport, mcule), at a cheaper cost (TechBio Spotlight - Molecule.one).
M1 RetroScore powered by CAS, a synthetic accessibility scoring tool using DL models trained on CAS chemical reaction content to predict the likelihood of synthesis for novel small molecules.
MariaAI (an LLM-based agent), an internal AI agent for synthetic chemistry built upon their core capabilities. Maria uses their proprietary tools and datasets to automate key stages of molecular synthesis, accurately and efficiently planning and ultimately carrying out the synthesis and delivery of compounds at scale.
Finally, on August 11, 2023 CAS—a division of the American Chemical Society specializing in scientific information solutions—and Molecule.one announced a strategic collaboration focused on the joint development of computer-aided synthesis design technologies to accelerate scientific breakthroughs in early-stage drug discovery and aid chemists in the discovery of novel small molecules.
🍉 Shift Bioscience announced SB000 as a powerful rejuvenating candidate across multiple cell types
Shift Bioscience, a biotechnology company that uses dataset-driven discovery to understand and manipulate cell rejuvenation, recently announced that SB000 demonstrated a powerful rejuvenating 🧝 effect across multiple cell types (SB000: a safer path to anti-aging therapies). Crucially, the gene induced this rejuvenation without activating the dangerous pluripotency pathways triggered by current approaches such as the Yamanaka Factors (OSKM).
The Yamanaka Factors, a group of four genes (OCT4, SOX2, KLF4, and MYC), have been widely studied for their ability to reverse aging at the cellular level. However, their use has been limited ⛔ by the risk of inducing pluripotency, a state in which cells can become tumorigenic. This significant safety concern has prevented OSKM from becoming a viable therapeutic strategy for many age-related diseases.
SB000 demonstrated cellular rejuvenation at both methylome and transcriptome levels across multiple cell types without evidence of pluripotency. Not only is this approach safer when compared to OSKM, but it also demonstrated comparable methylome rejuvenation, consistently across multiple cell types.
✅ SB000 reverses cellular ageing as measured by DNA methylation clocks in multiple cell types without loss of cellular identity or signs of pluripotency
✅ Study advances efforts towards next-generation rejuvenation therapeutics with applications across age-driven diseases
On October 15, 2024, Shift Bioscience raised $16M to advance cell simulation AI platform. The funding, led by BGF, with existing investors F-Prime Capital, Kindred Capital and Jonathan Milner participating will be used for the continued development of Shift Bioscience’s AI cell simulation platform, for the identification of genes that can safely rejuvenate cells to combat the effects of age-related illnesses.
So far, Shift's platform has discovered 6️⃣ gene-based interventions that reverse epigenetic age without inducing stem cell colonies, including a single-gene intervention. Shift can screen up to 2000 molecules in vitro and over a billion cocktails in silico to test for a cell-rejuvenation mechanism of action, with potential to bring forward a first-in-class therapeutics. Moreover the company is continuously improving cell aging clocks ⏰, cell simulations and active learning cycles to accelerate future discovery.
Shift was founded in 2017 by Daniel Ives and Brendan Swain. And Leonard Wossnig, CTO in LabGenius and an AI expert, is an Advisor at Shift Bioscience.
For more about Longevity:
“Rebooting Your Defenses ⚔️🛡️” by
