Antibody Engineering & Therapeutics Content
The content provides a comprehensive collection of resources—including white papers, webinars, and brochures—focused on antibody engineering and therapeutics, covering topics such as biologics discovery challenges, antibody identification and screening, data management for biologic candidates, and software tools like Geneious Biologics, GraphPad Prism, and SnapGene to support therapeutic antibody discovery and analysis.
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The Rise of Biotech: Why Smaller Companies Are Outpacing Big Pharma on Innovation
Smaller biotech companies are increasingly outpacing big pharmaceutical firms in new molecular entity approvals due to their greater agility, willingness to take risks, and freedom to innovate despite funding challenges, with over half of upcoming blockbuster drug launches expected from first-time launchers who face higher risks but also potential for significant success.
Data-Driven R&D in Chemicals & Materials: Why an Open Platform is Essential
The webinar titled "Data-Driven R&D in Chemicals & Materials: Why an Open Platform is Essential," presented by Max Petersen of Dotmatics, discusses how a unified, open scientific data platform enhances interoperability among existing R&D IT systems, supports diverse scientific workflows, and empowers researchers in chemicals and materials industries to tackle challenges like sustainability by enabling comprehensive, strategic data access.
San Diego Happy Hour
The San Diego Happy Hour event at Farmer & The Seahorse on September 28 from 4-6pm offers attendees drinks, appetizers, networking opportunities, and presentations on Dotmatics' chemistry and biology solutions, including a customer testimonial.
AE&T 2025: Full-Stack AI for Antibody Discovery
AE&T 2025 marked a pivotal shift in antibody R&D where AI-native, full-stack discovery systems seamlessly integrated in vitro, in vivo, and in silico workflows into a unified "lab-in-a-loop," emphasizing platform-level developability and overcoming fragmented data and workflows to transform complex protein designs into reliable therapeutics beyond oncology.
Prioritizing Data Integrity in R&D: Challenges and Best Practices
The article emphasizes the critical importance of maintaining data integrity in R&D by implementing robust data governance, security, and management practices throughout the research lifecycle to ensure data accuracy, protect patient safety, uphold product efficacy, and comply with regulatory standards amid increasing digitization and evolving threats.
Reasonable Expectations, Clean Data, Collaboration: The Three Keys to AI in Drug Discovery
The article explains that while AI and machine learning have long been used in drug discovery, recent hype and massive investments have led to unrealistic expectations, emphasizing that success depends on setting reasonable goals, ensuring clean and abundant data, and fostering collaboration, as most AI-driven drug candidates remain in early development stages and face complex biological and practical challenges.