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Moderna Partners with IBM to Advance mRNA Drug Discovery Through Quantum Computing and AI

AIDrug Discovery
  • Moderna has formed a strategic partnership with IBM to leverage quantum computing and generative artificial intelligence for advancing mRNA medicine discovery and development.
  • The collaboration aims to deepen understanding of mRNA molecular behavior, refine molecular structures, and improve lipid nanoparticle delivery systems used in mRNA therapeutics.
  • Moderna joins a growing group of pharmaceutical companies including Biogen and Bayer that are embracing quantum computing technologies to accelerate drug discovery processes.
  • The partnership positions Moderna to harness quantum computing's potential to investigate larger molecules and solve previously intractable problems in mRNA research.

ImmunoPrecise's LENSai Platform Achieves X-Ray Crystallography-Level Epitope Mapping Accuracy in Hours

AI
  • ImmunoPrecise Antibodies' LENSai platform matched the performance of x-ray crystallography in epitope mapping using sequence data alone, achieving predictive scores of AUC 0.79-0.89 while reducing turnaround time from weeks to hours.
  • The AI-powered platform demonstrated true generalization by accurately predicting binding sites on 17 previously unseen antibody-antigen complexes, proving it can work beyond its training data without requiring expensive wet-lab experiments.
  • This breakthrough addresses critical industry challenges where over 95% of drug candidates fail before reaching the clinic, offering pharmaceutical companies a faster, more cost-effective method for antibody discovery and development.

Kouper Emerges from Stealth with $10M to Transform Hospital Discharge Care Transitions

AI
  • Kouper launched with $10 million in funding from General Catalyst, 25Madison, and CVS Health Ventures to address care transition failures that cost the U.S. over $53 billion annually in avoidable readmissions.
  • The AI-powered platform integrates directly with hospitals to track patients in real-time after discharge, automating scheduling and surfacing red flags without adding workload for clinical teams.
  • Early health system partners including LifePoint, Henry Ford Health, and Ascension Saint Thomas have reported over 50% increase in patient engagement and 60% improvement in follow-up appointment rates.
  • The company can deploy its platform in under four weeks and is working with several leading health systems to scale its transitions of care infrastructure nationwide.

Digital Health Technologies and AI Show Promise for Transforming Lysosomal Storage Disorder Care in Europe

AI
  • A pioneering European initiative led by Professor Maurizio Scarpa explores integrating digital health innovations including AI, telemedicine, and connected care technologies into care pathways for Lysosomal Storage Disorders.
  • The project aims to address significant challenges in LSD care including delayed diagnoses, fragmented care pathways, and limited access to specialist care through digital health transformations.
  • Digital health technologies offer transformative opportunities to enable earlier intervention, enhance care coordination, and empower patients and healthcare providers with innovative tools.
  • The initiative emphasizes the need for continued generation of high-quality clinical evidence, health economic impact assessment, and multi-stakeholder engagement to optimize care pathways and clinical outcomes.

Insilico Medicine Secures $123 Million Series E Funding to Advance AI-Driven Drug Discovery Pipeline

AIDrug Discovery
  • Insilico Medicine closed an oversubscribed Series E financing round totaling $123 million, led by Value Partners Group, to advance its AI-driven drug discovery platform and clinical pipeline.
  • The company has built a pipeline of over 30 assets with 10 receiving IND clearance, including rentosertib for idiopathic pulmonary fibrosis currently in Phase 2a trials.
  • Insilico filed for its third Hong Kong IPO attempt in 2025, following previous filings in September 2024, amid growing investor interest in AI biotech companies.
  • The funding will support clinical validation of AI-driven drug programs and further development of the company's Pharma.AI platform and automated laboratory capabilities.

AI-Powered Pathology: Transforming Cancer Diagnostics and Precision Oncology

AIOncology
  • AI technology is poised to revolutionize cancer diagnostics by improving accuracy, efficiency, and workflow, while handling tedious tasks that pathologists find challenging or time-consuming.
  • Experts emphasize that AI will not replace pathologists but rather serve as a powerful tool that can provide insights beyond human capability, potentially predicting treatment responses better than current methods.
  • The integration of AI in pathology faces challenges including the need for digitized slides, regulatory hurdles, and ethical considerations, though it promises to standardize diagnoses and reduce disparities in cancer care globally.

Dawn Health Secures €11.5 Million to Expand Pharma-Focused Digital Health Platform

AIReal World EvidenceOncologyRare Disease
  • Copenhagen-based Dawn Health has raised €11.5 million from existing investors to scale its regulatory-grade digital health platform designed specifically for pharmaceutical companies.
  • The platform, already utilized by industry leaders like Merck and Novartis, supports patients with conditions including oncology, multiple sclerosis, and rare pediatric diseases through AI-driven symptom tracking and clinical integration.
  • This funding will accelerate Dawn Health's SaaS delivery model, product development, and international expansion as the company aims to become the global leader in pharmaceutical digital health solutions.

NewLimit Secures $130M Series B to Advance Epigenetic Reprogramming for Age Reversal

AI
• Biotechnology startup NewLimit, co-founded by Coinbase CEO Brian Armstrong, has raised $130 million in Series B funding led by Kleiner Perkins to develop therapies that reverse cellular aging.
• The company has developed three prototype medicines that can reprogram liver cells, demonstrating in laboratory experiments that aged cells can regain youthful characteristics in processing fat and alcohol.
• NewLimit combines AI-driven analysis with large-scale genomics in its "Discovery Engine," which tests thousands of reprogramming combinations on human cells to identify potential age-reversing treatments.

Algorae Pharmaceuticals Partners with Peter MacCallum Cancer Centre to Validate AI-Predicted Drug Combinations

AIDrug DiscoveryOncology
  • Algorae Pharmaceuticals has partnered with the Victorian Centre for Functional Genomics at Peter MacCallum Cancer Centre to validate AI-predicted drug synergies using high-throughput screening technology.
  • The collaboration will test 24 drug candidates, including 21 AI-generated compounds, across four cancer cell lines: glioblastoma, pancreatic ductal adenocarcinoma, invasive breast carcinoma, and prostate carcinoma.
  • Full dataset from the screening program is expected within six months, with successful validation potentially accelerating regulatory pathways and creating opportunities for pharmaceutical partnerships.

Federal Circuit Ruling Limits Patent Protection for Machine Learning Applications, Highlights Trade Secret Alternative

AI
  • The Federal Circuit in Recentive Analytics v. Fox Corp. ruled that applying generic machine learning techniques to known problems without technical innovation is insufficient for patent eligibility under Section 101.
  • The court emphasized that simply automating human tasks with machine learning or improving speed and efficiency does not render claims patent eligible without underlying technological improvements.
  • The decision may drive companies toward trade secret protection for AI innovations, as trade secrets offer broader protection for machine learning applications including training data, model weights, and configuration methods.
  • Patent applicants in the machine learning space must now clearly demonstrate technical improvements to the ML models themselves rather than merely claiming new applications of existing techniques.

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