Pharmacovigilance (PV) is experiencing a renaissance. Artificial Intelligence (AI) is no longer a futuristic concept in PV; it’s here, reshaping how we manage safety data, detect signals and maintain compliance. From automating case intake to accelerating literature screening and supporting aggregate reporting, AI promises efficiency and scalability at a time when data volumes and regulatory expectations are soaring. Yet, for all its potential, AI introduces a new challenge:
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Life Sciences | News, Analysis, Insights - HIT Consultant
Unlocking Real-World Evidence: 5 Questions to Ask Before Trusting AI-Curated RWD
In today’s pharmaceutical industry, real-world evidence (RWE) offers significant potential across all phases of the product life cycle, from trial design to product launch, from pricing and competitive reviews to evaluating the effects of switching medications.
As RWE becomes a key tool for life sciences organizations to shape clinical trial strategies, advance treatment development, and meet regulatory requirements, the quality of the underlying data and trust in how it was generated is
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The “One Shot” Cure? How Vyriad’s $85M Raise Could Replace Complex CAR-T Labs with a Single Injection
What You Should Know:
- Vyriad, Inc. has secured the final $25M of its Series B financing, bringing the total round to $85M led by Mr. Harry Stine of Stine Seed Farms, Inc.
- The funding will power the first-in-human trials of VV169, an in vivo CAR-T therapy for multiple myeloma that modifies immune cells directly inside the patient’s body. This approach eliminates the complex, expensive lab manufacturing required by current CAR-T treatments, potentially offering a scalable,
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Fragile Lifelines: How AI Can Reinforce Pharma Supply Chains
Drug shortages have surged to their highest levels in decades. In early 2024, U.S. pharmacies reported more than 323 active shortages, spanning essential generics, injectables, and even critical cancer therapies. These numbers echo findings from the American Society of Health-System Pharmacists, which tracks persistent disruptions that ripple through hospitals, pharmacies, and ultimately to patients in urgent need of care.
While the pandemic made those cracks impossible to ignore, the reality
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Why MBX Capital is Betting $100M on the Link Between Industrial Toxins and Chronic Disease
What You Should Know:
- MBX Capital has secured over $100M in capital commitments to invest in early-stage biotech and health tech companies, specifically focusing on "deep health" solutions that address diseases linked to environmental toxins and synthetic exposures.
- Backed by institutional heavyweights like Industry Ventures and the State of New York, the firm plans to deploy checks ranging from $1 million to $4 million into startups that move beyond symptom management
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Mass General Brigham Spins Out AIwithCare: New AI Tool Doubles Clinical Trial Enrollment Rates
What You Should Know:
- Mass General Brigham is announcing the spinout of AIwithCare, a company founded by researchers from the health system who developed an artificial intelligence (AI) screening tool that significantly outperformed manual screening for determining a patient’s eligibility and enrolling them in a clinical trial.
- The tool, RECTIFIER (RAG-Enabled Clinical Trial Infrastructure for Inclusion Exclusion Review), was first developed and studied by
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OpenAI-Backed Chai Discovery Raises $130M to Tackle “Undruggable” Targets with Generative AI
What You Should Know:
- Chai Discovery has secured a $130M Series B financing round, propelling its valuation to $1.3 billion just months after emerging from stealth.
- Co-led by Oak HC/FT and General Catalyst, the funding validates Chai’s proprietary AI models, which can predict biochemical interactions and design drugs for targets previously considered "undruggable."
- With backing from industry heavyweights like OpenAI and Thrive Capital, Chai is positioning itself
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Mount Sinai’s AI Tool “V2P” Predicts Disease Type from Genetic Mutations
What You Should Know:
- Scientists at the Icahn School of Medicine at Mount Sinai have developed a new artificial intelligence tool called V2P (Variant to Phenotype) that identifies not only disease-causing genetic mutations but also predicts the specific diseases they may trigger.
- Published in Nature Communications, this machine learning model improves diagnostic speed and accuracy by linking genetic variants to phenotypic outcomes, moving beyond simple "harmful vs. benign"
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Lunit and Daiichi Sankyo Partner to Accelerate Cancer Biomarker Discovery with AI
What You Should Know:
- Lunit has announced a collaboration with pharmaceutical giant Daiichi Sankyo to integrate its AI-powered Lunit SCOPE digital pathology products into two of Daiichi Sankyo's oncology pipeline programs.
- The partnership will utilize Lunit's SCOPE uIHC and SCOPE IO solutions to analyze pathology slides for quantitative data and immune phenotyping, aiming to discover novel biomarkers and improve patient stratification for clinical trials. This move underscores
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Valinor Raises $13M to Predict Clinical Trial Outcomes Using Multi-Omic AI
What You Should Know:
- Valinor has launched with $13M in seed funding to tackle one of the pharmaceutical industry's most expensive challenges: clinical trial failure led by CRV and Harpoon Ventures.
- The company uses proprietary AI models trained on matched multi-omic samples and clinical outcomes to predict how specific patient populations will respond to new therapies. This "response-first" approach aims to drastically de-risk drug development by identifying responders
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