Most IT and business leaders are traversing the maturity path of leveraging data to its fullest potential, and in that process they have envisioned a fully automated and governed data platform for their enterprise —one that provides a single version of the truth, is scalable, seamlessly integrates with existing infrastructure, and builds a strong foundation for AI capabilities on top.
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Large language models (LLMs) stand to redefine enterprise AI with GPT, Bard, Gemini, and Llama 2 generating human-like text and catering to knowledge management applications.
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Flow cytometry is a formidable asset for a researcher. By compartmentalizing cells based on set molecular characteristics, flow cytometry provides information on specific cell types from highly complex and populated samples. This technique analyzes thousands of cells per second, allowing researchers to collect huge data volumes in a relatively short time span.
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Clinical trial sites deal with a myriad of tasks right from patient recruitment to capturing patient data, and performing tests/procedures. In addition to facilitating patient interface, these sites also serve as the direct point-of-care for medical concerns.
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In the world of pharmaceutical manufacturing, batch processing stands as a cornerstone technique. It involves the production of large quantities of a drug, allowing for systematic and controlled processing.
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In a fast-paced world of research, laboratories face increasing pressure to innovate rapidly. Amidst this, data emerges as the ultimate tool, with big pharma companies leading the charge in utilizing AI-driven analytics for lab efficiency improvement.
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In the dynamic landscape of life sciences research, the acceleration of discoveries and breakthroughs is of paramount importance. Today, integrated assay analysis, powered by cutting-edge AI solutions, represents a pivotal leap in scientific exploration, revolutionizing the pace, depth, and efficacy of research endeavors across diverse disciplines.
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Clinical trials are at the forefront of medical advancement, playing a pivotal role in bringing new treatments and therapies to patients. However, despite their importance, patient recruitment remains a significant bottleneck in the clinical trial process.
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Patient recruitment in clinical trials has long been a challenging and time-consuming process, causing delays and increasing costs. Clinical trials come with stringent eligibility criteria, and potential participants often have reservations about safety, the time commitment required, or a simple lack of awareness about available trials.
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In the world of clinical trials, achieving real-time end-to-end visibility has become more than just a trend; it’s a critical necessity.
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