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AI Model COMET Accelerates RNA Medicine Development, Cutting Timelines from Months to Weeks

AIDrug Discovery
  • Researchers from NTU and MIT developed COMET, an AI model that predicts optimal lipid nanoparticle formulations for RNA medicine delivery, published in Nature Nanotechnology.
  • The transformer-based neural network can identify the best nanoparticle designs among millions of possibilities without extensive laboratory testing, reducing development timelines from months to weeks.
  • COMET-designed lipid nanoparticles outperformed clinically approved benchmarks in both laboratory and animal studies, demonstrating superior delivery performance.
  • The technology extends beyond pandemic preparedness to enable RNA therapies targeting specific organs and cell types for treating cancers and metabolic disorders.

AI-Designed Antibiotics Show Promise Against Drug-Resistant Gonorrhea and MRSA in Laboratory Studies

AI
  • MIT researchers used generative AI to design two novel antibiotics capable of killing drug-resistant gonorrhea and MRSA in laboratory and animal tests.
  • The AI system analyzed 36 million compounds using two innovative approaches to create completely new molecular structures distinct from existing antibiotics.
  • While promising, only two of 80 AI-generated gonorrhea treatments could be synthesized, highlighting manufacturing challenges before human clinical trials can begin.
  • Experts believe this breakthrough could herald a "second golden age" of antibiotic discovery in the fight against antimicrobial resistance.

Citizen Health Raises $30M Series A to Develop AI Advocate for Rare Disease Patients

AIRare Disease
  • Citizen Health secured $30 million in Series A funding led by 8VC to develop an AI Advocate platform for rare disease patients, bringing total funding to $44 million since December 2023.
  • The platform has built over 60 communities across 123 rare conditions and achieved a 98.3% patient data-sharing rate, with data already accepted by the FDA for regulatory submissions.
  • The company plans to launch its AI Advocate to select communities in Q3 2025, focusing on transforming fragmented healthcare into proactive, personalized patient experiences.
  • With rare diseases affecting over 400 million people globally and 95% lacking approved treatments, the platform addresses critical unmet needs in rare disease care and research.

Lantern Pharma Reports Complete Responses in Two Cancer Trials, Advances AI-Driven Pipeline

AIOncologyPrecision Medicine
  • Lantern Pharma achieved complete responses in two separate clinical trials, with LP-300 showing complete tumor response in a 70-year-old never-smoker lung cancer patient and LP-284 demonstrating complete metabolic response in a heavily pretreated lymphoma patient.
  • The company successfully completed enrollment of 65 patients in its LP-184 Phase 1a trial and established maximum tolerated dose and recommended Phase 2 dose, positioning the drug candidate for advancement to Phase 1b/2 studies.
  • Lantern narrowed its Q2 2025 GAAP net loss to $0.40 per share from $0.46 per share in Q2 2024, while maintaining disciplined cost management with $15.9 million in cash providing runway through mid-2026.

Study of LP-184 in Patients with Advanced Solid Tumors

NCT05933265RecruitingPhase 1
Lantern Pharma Inc.
Posted 6/9/2023

Oncology Experts Address Operational Challenges in Value-Based Cancer Care Implementation

AI
  • Payer-specific biosimilar mandates create significant inventory management challenges and operational inefficiencies for academic and infusion centers, requiring substantial resources to coordinate care delivery.
  • Manual prior authorization processes contribute to treatment delays and financial toxicity for both patients and healthcare institutions, highlighting the need for integrated digital solutions.
  • Healthcare systems are implementing dual approaches that maintain standardized pathway-driven care while allowing patient-specific regimen reviews through peer validation to accommodate personalized, biomarker-informed treatments.
  • AI-enabled platforms and clinical decision support tools show promise for streamlining workflows and balancing standardized pathways with individualized cancer care in rare or late-line settings.

Duke-NUS Receives $1.5M to Advance AI-Powered Antifibrotic Drug Discovery Platform

AIDrug Discovery
  • 65LAB has awarded $1.5 million to Professor Enrico Petretto at Duke-NUS Medical School to advance a breakthrough Systems Genetics platform for developing first-in-class antifibrotic therapies.
  • The platform integrates computational biology with AI algorithms and quantum computing to target lung and kidney diseases that currently lack effective treatments.
  • Pre-clinical studies demonstrate at least 50% reduction in fibrosis using newly discovered molecules that block the WWP2 gene, a key driver of tissue scarring.
  • The funding aims to accelerate commercialization and foster new therapeutic companies in Singapore's growing biotech ecosystem.

St. Jude Develops AI-Powered Tool to Accelerate Dual-Target CAR-T Cell Therapy Design

CAR-TAI
  • St. Jude researchers developed a computational tool that screens thousands of tandem CAR designs in days, dramatically accelerating development of dual-target immunotherapies.
  • The AI-informed algorithm successfully optimized CAR-T cells targeting pediatric brain tumor proteins B7-H3 and IL-13Rα2, completely clearing tumors in four out of five mice.
  • The computational approach overcame key challenges in tandem CAR design, including poor surface expression and suboptimal cancer-killing ability that have limited effectiveness against solid tumors.
  • The tool can screen approximately 1,000 CAR constructs in days versus the years required for traditional laboratory-based design approaches.

Sareum Partners with Receptor.AI to Accelerate AI-Driven Discovery of Brain-Penetrating TYK2/JAK1 Inhibitors for Neuroinflammatory Diseases

AIDrug Discovery
  • Sareum Holdings has entered a strategic collaboration with AI drug discovery firm Receptor.AI to accelerate development of blood-brain barrier-permeable TYK2/JAK1 inhibitors for neuroinflammatory conditions including multiple sclerosis and Parkinson's disease.
  • The partnership builds on Sareum's previous preclinical work that identified three TYK2/JAK1 compounds with meaningful brain penetration, including one showing particularly strong levels of free drug in the brain.
  • Receptor.AI will apply its proprietary AI platform for compound discovery and optimization using virtual screening and molecular design tools, while Sareum will handle synthesis, testing, and ADMET profiling.
  • The four-month project is expected to begin imminently, with Sareum retaining ownership of all intellectual property and compounds arising from the collaboration.

Rakovina Therapeutics and NanoPalm Form Joint Venture to Advance AI-Discovered Cancer Drug kt-3283

AIOncology
  • Rakovina Therapeutics and Saudi-based NanoPalm have signed a non-binding Letter of Intent to form a joint venture focused on developing AI-discovered oncology therapeutics using advanced lipid nanoparticle delivery systems.
  • The collaboration will initially focus on kt-3283, a dual PARP-HDAC inhibitor that has demonstrated enhanced cytotoxicity in preclinical models of Ewing sarcoma, breast cancer, and ovarian cancer compared to currently approved inhibitors.
  • The joint venture will be domiciled in Saudi Arabia with global development rights, combining Rakovina's AI-powered drug discovery platform with NanoPalm's precision patterned lipid nanoparticle technology.
  • This partnership represents the first pLNP-oncology-focused biotech venture co-founded in Saudi Arabia, aligning with the Kingdom's National Biotechnology Strategy for local biotech development.

Garden Launches BLOOM AI Engine to Accelerate IP-Aware Drug Discovery

AIDrug Discovery
  • Garden has launched BLOOM, a Markush structure search engine that provides AI drug-design teams with near-instant verification of small-molecule intellectual property landscapes during the discovery process.
  • The system delivers a 32.44× speed improvement over standard search methods, reducing verification time from 1.491 ms to 0.047 ms per comparison while eliminating false positives that plague legacy approaches.
  • BLOOM integrates graph-based reasoning with patent databases to enable real-time go/no-go decisions during ideation, addressing the bottleneck between AI molecule generation and IP diligence verification.

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