Life science leaders embrace new data and al-models for precision medicine to achieve their potential

Investment in IT systems is one of the top three obstacles to precision medicine According to worldwide life science managers, unified information policies are required for the achievement of precise medicine projects.
To manage the evolving information shape, data-centric, AI-based instruments and a linked environment are critical. Precision Medicine: Creating Value for All, according to the Newsweek Vantage report, 84 percent of senior life science executives agree that precise medicine represents a new era in drug manufacturing. The research report demonstrates the need for data-centered, AI tools and a connected ecosystem in the age of precision medicine.
The patient-centered strategy needs access to more information from a wider range of sources, including sensors, wearables, and information from the actual globe; and integration, preparation, and evaluation to generate actionable insights1.
Nearly one out of three mentioned investments in IT systems, altering strategic and scientific attitudes, and altering how products and services are marketed as the top three obstacles affecting precision medicine’s achievement.
Two out of five senior life science managers surveyed acknowledge unified information approaches and access to information from the actual globe as important to medicine project inaccuracy.
It’s not just about gathering big quantities of information to truly transform drug and information creation; it’s about interpreting it and placing it to work2. Powered by artificial intelligence and supplied by industry-leading professionals, Medidata redefines clinical growth with:
• Medidata Rave Clinical CloudTM; A Life Sciences Platform to seamlessly unify information, optimize operational performance and speed up timelines for drug growth
• SHYFT (Medidata Company), which offers data analytics and real-world proof capabilities, as well as the integration of business information from third parties and real-world information sources, enabling consumers to optimize protocol design and inform decision-making
• Acorn AI (Medidata Company), which uses machine learning and AI to accelerate the delivery of actionable ideas across studies, growth, and marketing to the front lines of decision-making by using high-quality fluid information, technology, knowledge, and a flourishing environment.
The study is based on an anonymous study of 301 senior managers from organizations engaged in the growth of diagnostics and drug discovery and development (up to two levels below the C-suite). Respondents were based in the United States, the United Kingdom, Germany, and France, with positions covering a variety of operations and disciplines appropriate to precision medicine.