Weekly Tech+Bio Highlights #21
ALSO: 100 Million-Cell Atlas for AI Drug Discovery, R&D Shifts in 2025, Miniprotein-based Therapeutics...
Hi! This is BiopharmaTrend’s weekly newsletter, ‘Where Tech Meets Bio,’ where we talk about technologies, breakthroughs, and great companies moving the biopharma and medtech industries forward.
If you've received it, then you either subscribed or someone forwarded it to you. If that is the case, subscribe by clicking this button:
Let’s get to this week’s topics!
Brief Insights
💰 AQEMIA secures $100M in funding, including $38M led by Cathay Innovation, to advance its generative AI-driven drug discovery platform, prepare oncology programs for clinical trials by 2025-2026, and expand globally with a new London office opening in January 2025.
🔬 IDEAYA Biosciences nominates IDE892, a PRMT5 inhibitor targeting MTAP-deleted tumors, for preclinical development, demonstrating durable responses in combination with MAT2A inhibitor IDE397, with an IND submission planned for mid-2025.
🔬 Vittoria Biotherapeutics presents preclinical data at ASH 2024 showing enhanced CAR-T cell proliferation and antitumor activity via CD5 knockout, supported by its Senza5 platform, which reduces manufacturing timelines and improves therapy durability for T-cell malignancies and other cancers.
🔬 BioAge Labs halts its STRIDES Phase 2 trial of azelaprag for obesity treatment due to liver enzyme elevations in some participants, while continuing to analyze trial data and focus on its NLRP3 inhibitor program targeting neuroinflammation, with an IND planned for late 2025.
💰 Nuvig Therapeutics secures $161M in Series B funding to advance its lead immunomodulator NVG-2089 into Phase 2 trials for autoimmune diseases like CIDP, aiming to develop safer, more effective treatments without immunosuppression.
🔬 Lantern Pharma enrolled its first patient in Taiwan for the Phase 2 Harmonic trial of LP-300 in never-smoker NSCLC, aiming to improve chemotherapy outcomes in a population with high EGFR and ALK mutations, supported by its AI-driven RADR platform.
Additionally, Lantern’s drug candidate LP-184 receives a second FDA Fast Track Designation in 2024, this time for Triple Negative Breast Cancer (TNBC), following earlier designation for Glioblastoma, recognizing its potential to address unmet needs in aggressive cancers.
🔬 NurExone Biologic announces promising preclinical results for ExoPTEN in restoring vision after optic nerve damage, showing enhanced retinal ganglion cell survival and signal recovery in a rodent model, paving the way for larger studies and potential treatments for glaucoma and optic nerve trauma.
💰 Orakl Oncology raises €11M in seed funding, led by Singular, to advance its AI-powered techbio platform, which integrates real-world patient data with ex vivo patient avatars to predict drug responses, validate targets, and optimize clinical trial outcomes for colorectal and pancreatic cancers.
🔬 Recursion Pharmaceuticals shares interim Phase 1 data for REC-617, a CDK7 inhibitor, showing a confirmed partial response in platinum-resistant ovarian cancer and stable disease in additional patients, with favorable tolerability and plans to initiate combination studies in 1H 2025.
Additionally, Recursion begins the DAHLIA trial for REC-1245, an AI-discovered RBM39 degrader targeting biomarker-enriched solid tumors and lymphoma, advancing from discovery to clinical testing in under 18 months.
💰 GE HealthCare will acquire full ownership of Nihon Medi-Physics by buying Sumitomo Chemical's 50% stake, strengthening its radiopharmaceutical portfolio in molecular imaging and expanding its presence in Asia.
💰 Antag Therapeutics raises €80M in Series A funding to develop AT-7687, a GIPR antagonist for obesity treatment, starting clinical trials in early 2025 for use alone or with GLP-1 therapies.
🔬 AI Proteins partners with Bristol Myers Squibb to develop miniprotein-based therapeutics for two targets, in a deal worth up to $400M, using AI Proteins' computational design platform.
🔬 Cherry Biotech publishes research on its CubiX skin-on-chip platform, which replicates human skin’s immune and vascular features for more accurate testing, including melanoma immunotherapies.
🔬 Vevo Therapeutics partners with Parse Biosciences to create Tahoe-100, a 100-million-cell dataset for AI-driven drug discovery, using Parse's GigaLab to analyze 1,200 drug treatments across 50 tumor models in just one month.
🔬 BIO INX launches BIORES INX, a gelatin-based DLP resin for bioprinting, offering high biocompatibility, ease of use, and compatibility with light-based bioprinting platforms, targeting advanced biofabrication applications.
🔬 Exotec partners with Hygie31 and Hartmann Group to deploy its Skypod robotic system, enhancing warehouse automation, order processing speed, and logistical efficiency for the pharmaceutical and healthcare sectors, with installations supporting scalability and improved working conditions.
🔬 TILT Biotherapeutics, reports progress on TILT-123, including successful intravenous delivery showing enhanced immune memory and identification of predictive immune markers via single-cell profiling, advancing Phase II plans for ovarian cancer and scaling manufacturing to broaden access for solid tumor treatments.
🔬 N4 Pharma announces preclinical development of N4 101, an oral TNF-alpha inhibitor using its Nuvec nanoparticle delivery system, targeting local delivery in the gut for IBD treatment, with key in vivo results expected by mid-2025.
100 Million-Cell Atlas for AI Drug Discovery
Seattle-based Parse Biosciences, a company specializing in single-cell sequencing solutions, has partnered with Vevo Therapeutics to generate Tahoe-100, the largest single-cell dataset to date, containing 100 million cells.
The dataset, reportedly completed in just one month, includes data from 60,000 experimental conditions, 1,200 drug treatments, and 50 tumor models. It was developed using Parse Biosciences’ GigaLab platform, which facilitates large-scale single-cell data generation.
Tahoe-100 was created to explore cellular responses to a broad range of drug treatments, enabling researchers to study diverse tumor models in detail. Vevo Therapeutics, a company focused on AI-based drug discovery, plans to integrate this data into its Mosaic platform, which uses in vivo data to better represent patient diversity in drug responses and to refine drug target identification.
Parse’s GigaLab platform was a key to building the dataset—designed for high-throughput single-cell sequencing, the platform leveraged Parse’s Evercode, a split-pool barcoding system that tags individual transcripts without requiring specialized equipment. This approach enabled large-scale data generation with high sensitivity, while avoiding common sequencing errors such as ambient RNA contamination.
The GigaLab workflow includes barcoding, library preparation, sequencing, and data analysis. It is optimized for processing over 10 million cells or nuclei in a single run, scaling up to 2.5 billion cells annually.
Anticipated R&D Shifts in 2025
On December 3, 2024, Brian Buntz outlined four key shifts anticipated in biopharma R&D for 2025, emphasizing the evolving landscape of digital and AI-driven strategies. Despite the highest clinical success rates since 2018, the industry faces declining R&D productivity, with inflation-adjusted spending rising by 44% over the past decade.
Companies like Moderna, which announced plans to cut R&D expenses by $1.1 billion, highlight the pressures to streamline operations. There’s talk of evolutionary, rather than revolutionary advances, driven by biology-first AI, digital twin adoption, and an increase in AI partnerships.
AI Pivots to Biology-First Approaches: Niven Narain, CEO of BPGbio, anticipates a shift from hype-driven AI investments to biology-first methodologies. These approaches leverage patient-derived multi-omics datasets to uncover disease causation, focusing on complex conditions such as glioblastoma and pancreatic cancer. By integrating rigorous biological data with translational models, the industry aims to meet unmet medical needs and deepen therapeutic insights.
Steady Digital Twin Adoption: Gen Li, Ph.D., CEO of Phesi, foresees growing interest in digital twins, virtual patient models based on extensive clinical data. While adoption is currently gradual, Li predicts an eventual explosion as education and awareness improve. Digital twins could replace control groups in ethically challenging trials, especially in cancer, hematology, and neurodegenerative diseases, accelerating drug development and improving trial designs.
Emergence of a Structured Digital Twin Pathway: The development of Digital Patient Profiles (DPPs) will enable earlier regulatory engagement and refined trial designs, even when full digital twin integration is not yet feasible. Specific case studies include using digital twins for G12C KRAS mutation and cGvHD trials to enhance trial efficiency. In Alzheimer’s disease trials, digital twins reduced trial durations from 18–24 months to 12 months while maintaining observational rigor. This approach has shown a 20–30% cognitive decline rate within the shortened period, indicating that even within a shorter time frame, researchers could still gather meaningful data about disease progression.
AI-Driven Partnerships and Regulatory Progress: Increased collaboration between pharma and AI-focused companies is expected (e.g. Schrödinger's agreement with Novartis), with advancements like AI-discovered drugs gaining regulatory milestones. Notable examples include Insilico Medicine’s Orphan Drug Designation for an AI-discovered molecule and GSK’s two-year acceleration of RSV drug trials using predictive modeling. These trends show a growing reliance on AI to drive innovation and efficiency in R&D.
Miniprotein-based Therapeutics
Bristol Myers Squibb has partnered with AI Proteins, a Massachusetts-based biotechnology company, to develop therapeutic miniproteins for two undisclosed targets.
Miniproteins are emerging as an alternative to traditional therapies, such as immune-targeting monoclonal antibodies and small-molecule drugs, by combining their strengths while addressing their limitations. Their compact size—ranging from 50 to 150 amino acids (usually smaller, definitions vary and are still negotiated)—enables them to penetrate barriers like the blood-brain barrier and tumor microenvironments, accessing targets that are typically out of reach for antibodies or small molecules.
Additionally, miniproteins can be engineered with precise configurations using computational models, making their development faster, more efficient, and specific to certain applications or routes of administration.
AI Proteins appears to be focused on simplifying and accelerating the creation of miniproteins, which may help with bringing this technology closer to widespread use.
The AI Proteins platform combines synthetic biology, automation, and artificial intelligence to design miniproteins with drug-like properties.
Some key features of the company’s technology:
Computational Design: Creation of miniproteins from scratch using in silico modeling.
Yeast and Phage Display: Screening systems for optimizing high-affinity binding.
Deep Mutagenesis: Comprehensive mutation analysis to refine therapeutic properties.
Automated Workflows: Integration of robotics and laboratory automation for efficient production.
Rapid Development: Miniproteins can reportedly be ready for preclinical testing in as little as 3-12 weeks.
While miniproteins are gaining attention for their potential precision, stability, and versatility, it’s worthy to note how their development intersects with an area of macrocyclic peptides. Both are being developed to address similar limitations in traditional therapies by bridging the gap between small molecules and biologics, aiming to provide solutions for previously challenging therapeutic targets.
See also: The Rise of Cyclic Peptides—Bridging the Gap in Modern Medicine
Read also:
11 Biopharma Trends to Watch in 2024